Harvard Business Review (Fall 2019 Special Issue)

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Build the Workforce You Need How to Hire the Right People and KeepThem Engaged

Fall 2019 HBR.org

The Best of HBR Insights on: Better People Analytics, Desirable Benefits, Adapting Your Workforce, and More!

FROM THE EDITORS

Winning the War for Talent

Y

our organization’s success has never been more dependent on people— those with the technical and leadership skills to carry you into the future. How will you compete? Companies are rushing to reinvent their talent management to become more responsive and flexible. In “HR Goes Agile,” Peter Cappelli and Anna Tavis describe where we’re seeing the biggest changes, such as performance appraisals, which many companies now conduct on a project basis rather than on an annual cycle. HR’s growing investment in data and analytics also means that at many companies these changes are being measured and honed in real time. But beware the limits of what your data can tell you, especially about diversity, Facebook’s Maxine Williams reminds us in “Numbers Take Us Only So Far.” In a hot talent market, recruiting the most sought-after employees requires creativity— and the newest technologies. From social media channels to bespoke talent pools, Erica Dhawan suggests approaches for targeting skeptical Millennials in “Recruiting Strategies for a Tight Talent Market.” And while machine learning offers big promises of personalized and efficient talent screening, Ben Dattner and his coauthors warn of the pitfalls in “The Legal and Ethical Implications of Using AI in Hiring.”

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Your hiring situation becomes more dire if you can’t also retain—and retrain—the workforce you have. Employees don’t necessarily require ever-more-expensive benefits, though: They’re also looking for flexible hours, paid vacation, and other more-accessible perks. And reskilling also helps keep employees engaged and loyal. In “Your Workforce Is More Adaptable Than You Think,” HBS professor Joseph Fuller and his colleagues describe the many benefits that accrue to companies that work together to retrain the talent pool. Finally, the massive shift to gig work has employers worried about what employment itself will look like in the future. Will organizations lose top talent—and valuable institutional knowledge—as employees choose to come and go? Will they find it increasingly hard to hire emerging leaders as Millennials eschew traditional jobs and flit between part-time roles? In “Myths of the Gig Economy, Corrected,” David Jolley offers a more nuanced view on whether we’re all about to go freelance (hint: we aren’t). Whether you’re a CEO, a hiring manager, or a team leader, understanding how the talent market is evolving will help you attract and keep the people you need. —The Editors

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Culled by the editors of Harvard Business Review from the magazine’s rich archives, these articles are written by some of the world’s leading management scholars and practitioners. To help busy leaders apply the concepts, they are accompanied by “Idea in Brief” summaries.

Contents TODAY’S TALENT MANAGEMENT

HOW RECRUITING WORKS NOW

HR Goes Agile | 10

Your Approach to Hiring Is All Wrong | 50

Peter Cappelli and Anna Tavis

One Bank’s Agile Team Experiment | 18 Dominic Barton, Dennis Carey, and Ram Charan

Reinventing Performance Management | 22 Marcus Buckingham and Ashley Goodall

Better People Analytics | 30 Paul Leonardi and Noshir Contractor

“Numbers Take Us Only So Far” | 40 Maxine Williams

Is HR the Most AnalyticsDriven Function? | 46

Peter Cappelli

Navigating Talent Hot Spots | 58

Recruiting Strategies for a Tight Talent Market | 72 Erica Dhawan

How Recruiters Can Stay Relevant in the Age of LinkedIn | 74 Atta Tarki and Ken Kanara

William Kerr

Data Science Can’t Fix Hiring (Yet) | 66 Peter Cappelli

The Legal and Ethical Implications of Using AI in Hiring | 67 Ben Dattner, Tomas Chamorro-Premuzic, Richard Buchband, and Lucinda Schettler

Expanding the Pool | 70 Dane E. Holmes JOANNA ŁAWNICZAK

Thomas H. Davenport

How to Develop a Data-Savvy HR Department | 47 Nigel Guenole and Sheri L. Feinzig

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COVER ILLUSTRATION BY GETTY IMAGES

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Your Workforce Is More Adaptable Than You Think | 76 Joseph B. Fuller, Judith K. Wallenstein, Manjari Raman, and Alice de Chalendar

Talent Management and the Dual-Career Couple | 82 Jennifer Petriglieri

The Most Desirable Employee Benefits | 90 Kerry Jones

Co-Creating the Employee Experience | 93

Why I Encourage My Best Employees to Consider Outside Job Offers | 97 Ryan Bonnici

Never Say Goodbye to a Great Employee | 99 Tammy Erickson

UNDERSTANDING THE GIG ECONOMY Thriving in the Gig Economy | 100 Gianpiero Petriglieri, Susan Ashford, and Amy Wrzesniewski

Myths of the Gig Economy, Corrected | 106 David Jolley

What Motivates Gig Economy Workers | 107 Alex Rosenblat

Performance Management in the Gig Economy | 109

A conversation with Diane Gherson by Lisa Burrell

Jon Younger and Norm Smallwood

Your Company Needs a Better Retention Plan for Working Parents | 96

Executive Summaries | 112

Daisy Wademan Dowling

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TODAY’S TALENT MANAGEMENT

HR Goes Agile by Peter Cappelli and Anna Tavis

A Originally published in March–April 2018

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GILE ISN’T JUST for tech any-

more. It’s been working its way into other areas and functions, from product development to manufacturing to marketing— and now it’s transforming how organizations hire, develop, and manage their people. You could say HR is going “agile lite,” applying the general principles without adopting all the tools and protocols from the tech world. It’s a move away from a rules- and planning-based approach toward a simpler and faster model driven by feedback from participants. This new paradigm has really taken off in the area of performance management. (In a 2017 Deloitte survey, 79% of global executives rated agile performance management as a high organizational priority.) But other HR processes are starting to change too. In many companies that’s happening gradually, almost organically, as a spillover from IT, where more than 90% of organizations already use agile practices. At the Bank of Montreal (BMO), for example, the shift began as tech employees joined cross-functional product-development teams to

ILLUSTRATION BY LLOYD MILLER

TODAY’S TALENT MANAGEMENT HR GOES AGILE

make the bank more customer focused. The business side has learned agile principles from IT colleagues, and IT has learned about customer needs from the business. One result is that BMO now thinks about performance management in terms of teams, not just individuals. Elsewhere the move to agile HR has been faster and more deliberate. GE is a prime example. Seen for many years as a paragon of management through control systems, it switched to FastWorks, a lean approach that cuts back on top-down financial controls and empowers teams to manage projects as needs evolve. The changes in HR have been a long time coming. After World War II, when manufacturing dominated the industrial landscape, planning was at the heart of human resources: Companies recruited lifers, gave them rotational assignments to support their development, groomed them years in advance to take on bigger and bigger roles, and tied their raises directly to each incremental move up the ladder. The bureaucracy was the point: Organizations wanted their talent practices to be rules-based and internally consistent so that they could reliably meet five-year (and sometimes 15year) plans. That made sense. Every other aspect of companies, from core businesses to administrative functions, took the long view in their goal setting, budgeting, and operations. HR reflected and supported what they were doing. By the 1990s, as business became less predictable and companies needed to acquire new skills fast, that traditional approach began to bend— but it didn’t quite break. Lateral hiring from the outside—to get more flexibility—replaced a good deal of the internal development and promotions. “Broadband” compensation gave managers greater latitude to reward people for growth and achievement within roles. For the most part, though, the old model persisted. Like other functions, HR was still built around the long term. Workforce and succession planning carried on, even though changes in the economy and in the business often rendered those plans irrelevant. Annual appraisals continued, despite almost universal dissatisfaction with them. Now we’re seeing a more sweeping transformation. Why is this the moment for it? Because rapid innovation has become a strategic imperative for most companies, not just a subset. To get it, businesses have looked to Silicon Valley and to software companies in particular, emulating their agile practices for managing projects. So top-down

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planning models are giving way to nimbler, userdriven methods that are better suited for adapting in the near term, such as rapid prototyping, iterative feedback, team-based decisions, and taskcentered “sprints.” As BMO’s chief transformation officer, Lynn Roger, puts it, “Speed is the new business currency.” With the business justification for the old HR systems gone and the agile playbook available to copy, people management is finally getting its long-awaited overhaul too. In this article we’ll illustrate some of the profound changes companies are making in their talent practices and describe the challenges they face in their transition to agile HR.

Where We’re Seeing the Biggest Changes Because HR touches every aspect—and every employee—of an organization, its agile transformation may be even more extensive (and more difficult) than the changes in other functions. Companies are redesigning their talent practices in the following areas: Performance appraisals. When businesses adopted agile methods in their core operations, they dropped the charade of trying to plan a year or more in advance how projects would go and when they would end. So in many cases the first traditional HR practice to go was the annual performance review, along with employee goals that “cascaded” down from business and unit objectives each year. As individuals worked on shorter-term projects of various lengths, often run by different leaders and organized around teams, the notion that performance feedback would come once a year, from one boss, made little sense. They needed more of it, more often, from more people. An early-days CEB survey suggested that people actually got less feedback and support when their employers dropped annual reviews. However, that’s because many companies put nothing in their place. Managers felt no pressing need to adopt a new feedback model and shifted their attention to other priorities. But dropping appraisals without a plan to fill the void was of course a recipe for failure. Since learning that hard lesson, many organizations have switched to frequent performance assessments, often conducted project by project. This change has spread to a number of industries,

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Idea in Brief including retail (Gap), big pharma (Pfizer), insurance (Cigna), investing (OppenheimerFunds), consumer products (P&G), and accounting (all Big Four firms). It is most famous at GE, across the firm’s range of businesses, and at IBM. Overall, the focus is on delivering more-immediate feedback throughout the year so that teams can become nimbler, “course-correct” mistakes, improve performance, and learn through iteration—all key agile principles. In user-centered fashion, managers and employees have had a hand in shaping, testing, and refining new processes. For instance, Johnson & Johnson offered its businesses the chance to participate in an experiment: They could try out a new continual-feedback process, using a customized app with which employees, peers, and bosses could exchange comments in real time. The new process was an attempt to move away from J&J’s event-driven “five conversations” framework (which focused on goal setting, career discussion, a midyear performance review, a yearend appraisal, and a compensation review) and toward a model of ongoing dialogue. Those who tried it were asked to share how well everything worked, what the bugs were, and so on. The experiment lasted three months. At first only 20% of the managers in the pilot actively participated. The inertia from prior years of annual appraisals was hard to overcome. But then the company used training to show managers what good feedback could look like and designated “change champions” to model the desired behaviors on their teams. By the end of the three months, 46% of managers in the pilot group had joined in, exchanging 3,000 pieces of feedback. Regeneron Pharmaceuticals, a fast-growing biotech company, is going even further with its appraisals overhaul. Michelle Weitzman-Garcia, Regeneron’s head of workforce development, argued that the performance of the scientists working on drug development, the product supply group, the field sales force, and the corporate functions should not be measured on the same cycle or in the same way. She observed that these employee groups needed varying feedback and that they even operated on different calendars. So the company created four distinct appraisal processes, tailored to the various groups’ needs. The research scientists and postdocs, for example, crave metrics and are keen on assessing competencies, so they meet with managers twice a year for

competency evaluations and milestones reviews. Customer-facing groups include feedback from clients and customers in their assessments. Although having to manage four separate processes adds complexity, they all reinforce the new norm of continual feedback. And Weitzman-Garcia says the benefits to the organization far outweigh the costs to HR. Coaching. The companies that most effectively adopt agile talent practices invest in sharpening managers’ coaching skills. Supervisors at Cigna go through “coach” training designed for busy managers: It’s broken into weekly 90-minute videos that can be viewed as people have time. The supervisors also engage in learning sessions, which, like “learning sprints” in agile project management, are brief and spread out to allow individuals to reflect and test-drive new skills on the job. Peer-topeer feedback is incorporated in Cigna’s manager training too: Colleagues form learning cohorts to share ideas and tactics. They’re having the kinds of conversations companies want supervisors to have with their direct reports, but they feel freer to share mistakes with one another, without the fear of “evaluation” hanging over their heads. DigitalOcean, a New York–based start-up focused on software as a service (SaaS) infrastructure, engages a full-time professional coach onsite to help all managers give better feedback to employees and, more broadly, to develop internal coaching capabilities. The idea is that once one experiences good coaching, one becomes a better coach. Not everyone is expected to become a great coach—those in the company who prefer coding to coaching can advance along a technical career track—but coaching skills are considered central to a managerial career. P&G, too, is intent on making managers better coaches. That’s part of a larger effort to rebuild training and development for supervisors and enhance their role in the organization. By simplifying the performance review process, separating evaluation from development discussions, and eliminating talent calibration sessions (the arbitrary horse trading between supervisors that often comes with a subjective and politicized ranking model), P&G has freed up a lot of time to devote to employees’ growth. But getting supervisors to move from judging employees to coaching them in their day-to-day work has been a challenge in P&G’s tradition-rich culture. So the company has invested heavily in training

THE REASON FOR THE SHIFT Companies’ core businesses and functions have largely replaced long-range planning models with nimbler methods that allow them to adapt and innovate more quickly. HR is starting to use agile talent practices to reflect and support what the rest of the organization is doing.

THE AREAS OF TRANSFORMATION Organizations are radically changing how they manage performance and evaluate talent, what skills they emphasize and develop, how they approach recruitment and rewards, and what they do to facilitate learning.

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supervisors on topics such as how to establish employees’ priorities and goals, how to provide feedback about contributions, and how to align employees’ career aspirations with business needs and learning and development plans. The bet is that building employees’ capabilities and relationships with supervisors will increase engagement and therefore help the company innovate and move faster. Even though the jury is still out on the companywide culture shift, P&G is already reporting improvements in these areas, at all levels of management. Teams. Traditional HR focused on individuals— their goals, their performance, their needs. But now that so many companies are organizing their work project by project, their management and talent systems are becoming more team focused. Groups are creating, executing, and revising their goals and tasks with scrums—at the team level, in the moment, to adapt quickly to new information as it comes in. (“Scrum” may be the best-known term in the agile lexicon. It comes from rugby, where players pack tightly together to restart play.) They are also taking it upon themselves to track their own progress, identify obstacles, assess their leadership, and generate insights about how to improve performance. In that context, organizations must learn to contend with: Multidirectional feedback. Peer feedback is essential to course corrections and employee development in an agile environment, because team members know better than anyone else what each person is contributing. It’s rarely a formal process, and comments are generally directed to the employee, not the supervisor. That keeps input constructive and prevents the undermining of colleagues that sometimes occurs in hypercompetitive workplaces. But some executives believe that peer feedback should have an impact on performance evaluations. Diane Gherson, IBM’s head of HR, explains that “the relationships between managers and employees change in the context of a network [the collection of projects across which employees work].” Because an agile environment makes it practically impossible to “monitor” performance in the old sense, managers at IBM solicit input from others to help them identify and address issues early on. Unless it’s sensitive, that input is shared in the team’s daily stand-up meetings and captured in an app. Employees may choose

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whether to include managers and others in their comments to peers. The risk of cutthroat behavior is mitigated by the fact that peer comments to the supervisor also go to the team. Anyone trying to undercut colleagues will be exposed. In agile organizations, “upward” feedback from employees to team leaders and supervisors is highly valued too. The Mitre Corporation’s not-for-profit research centers have taken steps to encourage it, but they’re finding that this requires concentrated effort. They started with periodic confidential employee surveys and focus groups to discover which issues people wanted to discuss with their managers. HR then distilled that data for supervisors to inform their conversations with direct reports. However, employees were initially hesitant to provide upward feedback—even though it was anonymous and was used for development purposes only—because they weren’t accustomed to voicing their thoughts about what management was doing. Mitre also learned that the most critical factor in getting subordinates to be candid was having managers explicitly say that they wanted and appreciated comments. Otherwise people might worry, reasonably, that their leaders weren’t really open to feedback and ready to apply it. As with any employee survey, soliciting upward feedback and not acting on it has a diminishing effect on participation; it erodes the hard-earned trust between employees and their managers. When Mitre’s new performance-management and feedback process began, the CEO acknowledged that the research centers would need to iterate and make improvements. A revised system for upward feedback will roll out this year. Because feedback flows in all directions on teams, many companies use technology to manage the sheer volume of it. Apps allow supervisors, coworkers, and clients to give one another immediate feedback from wherever they are. Crucially, supervisors can download all the comments later on, when it’s time to do evaluations. In some apps, employees and supervisors can score progress on goals; at least one helps managers analyze conversations on project management platforms like Slack to provide feedback on collaboration. Cisco uses proprietary technology to collect weekly raw data, or “breadcrumbs,” from employees about their peers’ performance. Such tools enable managers to see fluctuations in individual performance over time, even within teams. The apps don’t pro-

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WHY INTUIT’S TRANSITION TO AGILE ALMOST STALLED OUT vide an official record of performance, of course, and employees may want to discuss problems face-to-face to avoid having them recorded in a file that can be downloaded. We know that companies recognize and reward improvement as well as actual performance, however, so hiding problems may not always pay off for employees. Frontline decision rights. The fundamental shift toward teams has also affected decision rights: Organizations are pushing them down to the front lines, equipping and empowering employees to operate more independently. But that’s a huge behavioral change, and people need support to pull it off. Let’s return to the Bank of Montreal example to illustrate how it can work. When BMO introduced agile teams to design some new customer services, senior leaders weren’t quite ready to give up control, and the people under them were not used to taking it. So the bank embedded agile coaches in business teams. They began by putting everyone, including high-level executives, through “retrospectives”—regular reflection and feedback sessions held after each iteration. These are the agile version of after-action reviews; their purpose is to keep improving processes. Because the retrospectives quickly identified concrete successes, failures, and root causes, senior leaders at BMO immediately recognized their value, which helped them get on board with agile generally and loosen their grip on decision making. Complex team dynamics. Finally, since the supervisor’s role has moved away from just managing individuals and toward the much more complicated task of promoting productive, healthy team dynamics, people often need help with that, too. Cisco’s special Team Intelligence unit provides that kind of support. It’s charged with identifying the company’s best-performing teams, analyzing how they operate, and helping other teams learn how to become more like them. It uses an enterprisewide platform called Team Space, which tracks data on team projects, needs, and achievements to both measure and improve what teams are doing within units and across the company. Compensation. Pay is changing as well. A simple adaptation to agile work, seen in retail companies such as Macy’s, is to use spot bonuses to recognize contributions when they happen rather than rely solely on end-of-year salary increases. Research and practice have shown that compensation works best as a motivator when it comes as soon as possible after the desired behavior. Instant

The financial services division at Intuit began shifting to agile in 2009—but four years went by before that became standard operating procedure across the company. What took so long? Leaders started with a “waterfall” approach to change management, because that’s what they knew best. It didn’t work. Spotty support from middle management, part-time commitments to the team leading the transformation, scarce administrative resources, and an extended planning cycle all put a big drag on the rollout. Before agile could gain traction throughout the organization, the transition team needed to take an agile approach to becoming agile and managing the change. Looking back, Joumana Youssef, one of Intuit’s strategic-change leaders, identifies several critical discoveries that changed the course— and the speed—of the transformation: • Focus on early adopters. Don’t waste time trying to convert naysayers. • Form “triple-S” (small, stable, self-managed) teams, give them ownership of their work, and hold them accountable for their commitments. • Quickly train leaders at all levels in agile methods. Agile teams need to be fully supported to self-manage. • Expect that changing frontline and middle management will be hard, because people in those roles need time to acclimate to “servant leadership,” which is primarily about coaching and supporting employees rather than monitoring them. • Stay the course. Even though agile change is faster than a waterfall approach, shifting your organization’s mindset takes persistence.

rewards reinforce instant feedback in a powerful way. Annual merit-based raises are less effective, because too much time goes by. Patagonia has actually eliminated annual raises for its knowledge workers. Instead the company adjusts wages for each job much more frequently, according to research on where market rates are going. Increases can also be allocated when employees take on more-difficult projects or go above and beyond in other ways. The company retains a budget for the top 1% of individual contributors, and supervisors can make a case for any contribution that merits that designation, including contributions to teams.

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TODAY’S TALENT MANAGEMENT HR GOES AGILE

Compensation is also being used to reinforce agile values such as learning and knowledge sharing. In the start-up world, for instance, the online clothing-rental company Rent the Runway dropped separate bonuses, rolling the money into base pay. CEO Jennifer Hyman reports that the bonus program was getting in the way of honest peer feedback. Employees weren’t sharing constructive criticism, knowing it could have negative financial consequences for their colleagues. The new system prevents that problem by “untangling the two,” Hyman says. DigitalOcean redesigned its rewards to promote equitable treatment of employees and a culture of collaboration. Salary adjustments now happen twice a year to respond to changes in the outside labor market and in jobs and performance. More important, DigitalOcean has closed gaps in pay for equivalent work. It’s deliberately heading off internal rivalry, painfully aware of the problems in hypercompetitive cultures (think Microsoft and Amazon). To personalize compensation, the firm maps where people are having impact in their roles and where they need to grow and develop. The data on individuals’ impact on the business is a key factor in discussions about pay. Negotiating to raise your own salary is fiercely discouraged. And only the top 1% of achievement is rewarded financially; otherwise, there is no merit-pay process. All employees are eligible for bonuses, which are based on company performance rather than individual contributions. To further support collaboration, DigitalOcean is diversifying its portfolio of rewards to include nonfinancial, meaningful gifts, such as a Kindle loaded with the CEO’s “best books” picks. How does DigitalOcean motivate people to perform their best without inflated financial rewards? Matt Hoffman, its vice president of people, says it focuses on creating a culture that inspires purpose and creativity. So far that seems to be working. The

latest engagement survey, via Culture Amp, ranks DigitalOcean 17 points above the industry benchmark in satisfaction with compensation. Recruiting. With the improvements in the economy since the Great Recession, recruiting and hiring have become more urgent—and more agile. To scale up quickly in 2015, GE’s new digital division pioneered some interesting recruiting experiments. For instance, a cross-functional team works together on all hiring requisitions. A “head count manager” represents the interests of internal stakeholders who want their positions filled quickly and appropriately. Hiring managers rotate on and off the team, depending on whether they’re currently hiring, and a scrum master oversees the process. To keep things moving, the team focuses on vacancies that have cleared all the hurdles—no req’s get started if debate is still ongoing about the desired attributes of candidates. Openings are ranked, and the team concentrates on the toppriority hires until they are completed. It works on several hires at once so that members can share information about candidates who may fit better in other roles. The team keeps track of its cycle time for filling positions and monitors all open requisitions on a kanban board to identify bottlenecks and blocked processes. IBM now takes a similar approach to recruitment. Companies are also relying more heavily on technology to find and track candidates who are well suited to an agile work environment. GE, IBM, and Cisco are working with the vendor Ascendify to create software that does just this. The IT recruiting company HackerRank offers an online tool for the same purpose. Learning and development. Like hiring, L&D had to change to bring new skills into organizations more quickly. Most companies already have a suite of online learning modules that employees can access on demand. Although helpful for those

“Upward” feedback from employees to team leaders is valued in agile organizations. But it takes work—people aren’t used to voicing opinions about management. 16 HBR Special Issue

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who have clearly defined needs, this is a bit like giving a student the key to a library and telling her to figure out what she must know and then learn it. Newer approaches use data analysis to identify the skills required for particular jobs and for advancement and then suggest to individual employees what kinds of training and future jobs make sense for them, given their experience and interests. IBM uses artificial intelligence to generate such advice, starting with employees’ profiles, which include prior and current roles, expected career trajectory, and training programs completed. The company has also created special training for agile environments—using, for example, animated simulations built around a series of “personas” to illustrate useful behaviors, such as offering constructive criticism. Traditionally, L&D has included succession planning—the epitome of top-down, long-range thinking, whereby individuals are picked years in advance to take on the most crucial leadership roles, usually in the hope that they will develop certain capabilities on schedule. The world often fails to cooperate with those plans, though. Companies routinely find that by the time senior leadership positions open up, their needs have changed. The most common solution is to ignore the plan and start a search from scratch. But organizations often continue doing long-term succession planning anyway. (About half of large companies have a plan to develop successors for the top job.) Pepsi is one company taking a simple step away from this model by shortening the time frame. It provides brief quarterly updates on the development of possible successors—in contrast to the usual annual updates—and delays appointments so that they happen closer to when successors are likely to step into their roles.

Ongoing Challenges To be sure, not every organization or group is in hot pursuit of rapid innovation. Some jobs must remain largely rules based. (Consider the work that accountants, nuclear control-room operators, and surgeons do.) In such cases agile talent practices may not make sense. And even when they’re appropriate, they may meet resistance—especially within HR. A lot of processes have to change for an organization to move away from a planning-based, “waterfall”

model (which is linear rather than flexible and adaptive), and some of them are hardwired into information systems, job titles, and so forth. The move toward cloud-based IT, which is happening independently, has made it easier to adopt app-based tools. But people issues remain a sticking point. Many HR tasks, such as traditional approaches to recruitment, onboarding, and program coordination, will become obsolete, as will expertise in those areas. Meanwhile, new tasks are being created. Helping supervisors replace judging with coaching is a big challenge not just in terms of skills but also because it undercuts their status and formal authority. Shifting the focus of management from individuals to teams may be even more difficult, because team dynamics can be a black box to those who are still struggling to understand how to coach individuals. The big question is whether companies can help managers take all this on and see the value in it. The HR function will also require reskilling. It will need more expertise in IT support—especially given all the performance data generated by the new apps—and deeper knowledge about teams and hands-on supervision. HR has not had to change in recent decades nearly as much as have the line operations it supports. But now the pressure is on, and it’s coming from the operating level, which makes it much harder to cling to old talent practices. HBR Reprint R1802B

Peter Cappelli is the George W. Taylor Professor of Management at the Wharton School and the director of its Center for Human Resources. His most recent book is Will College Pay Off? A Guide to the Most Important Financial Decision You’ll Ever Make (PublicAffairs, 2015). Anna Tavis is a clinical associate professor of human capital management at New York University and the Perspectives editor at People + Strategy, a journal for HR executives.

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HBR Special Issue 17

TODAY’S TALENT MANAGEMENT

One Bank’s Agile Team Experiment How ING revamped its retail operation by Dominic Barton, Dennis Carey, and Ram Charan

W Originally published in March–April 2018

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HEN WEB AND mobile

technologies disrupted the banking industry, consumers became more and more aware of what they could do for themselves. They quickly embraced what Ralph Hamers, CEO of the global banking group ING, calls “banking on the go.” By 2014 about 40% of all interactions with ING retail customers were coming in through mobile apps. (Now the figure is closer to 60%—and branch visits and calls to contact centers have dropped below 1%.)Even then mobile customers expected easy access to up-to-date information whenever and wherever they logged in. For instance, someone who started a loan transaction during the train ride home from work wanted to be able to continue it on a desktop that night. “Our customers were spending most of their online time on platforms like Facebook and Netflix,” says Hamers. “Those set the standard for user experience.” That meant ING needed to become nimbler and more user-focused to serve its 30 million–plus customers across the world at every point in their financial journeys. So Hamers worked with Nick Jue, then the CEO of ING’s Netherlands group, to launch a pilot transformation in the headquarters of ING’s largest unit, its Dutch retail operations. The first step was to help other senior leaders

and the board envision a new agile, team-based system for deploying, developing, and assessing talent. (ING had already adopted agile and scrum methodologies in its Dutch IT unit, but those ways of working were new to other parts of the organization.) Hamers and his leadership team then met with people at tech companies they admired, learning how their talent systems enabled better customer service. By the spring of 2015 the headquarters of ING Netherlands, home to some 3,500 full-time employees, had replaced most of its traditional structure with a fluid, agile organization composed of tribes, squads, and chapters. Thirteen tribes were created to address specific domains, such as mortgage services, securities, and private banking. Each tribe contains up to 150 people. (Employees in sales, service, and support functions work outside this structure—in smaller customer-loyalty teams, for instance—but they collaborate with the tribes.) And each has a lead who establishes priorities, allocates budgets, and ensures that knowledge and insights are shared both within and across tribes. The tribe lead has one other critical responsibility: to create, with input from tribe members, selfsteering squads of nine or fewer people to address specific customer needs by delivering and maintaining new products and services. These squads are cross-disciplinary—typically, a mix of marketing specialists, data analysts, user-experience

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Tribes, Squads, and Chapters ING’s new agile system for deploying talent and managing performance organizes people by domain, customer need, and function. After experimenting with this structure in its Dutch retail unit, the company decided to roll it out more broadly.

Tribe A collection of squads focused on the same domain— for instance, private banking or mortgage services

Tribe lead Establishes priorities, allocates budgets, and coordinates with other tribes to ensure knowledge sharing

Squad A self-steering, crossfunctional group of nine or fewer people charged with meeting a specific customer need; either disbands when that need has been addressed or turns to a new one

Chapter lead

Chapter The members of a given discipline, such as UX or data analytics; they develop expertise and knowledge across squads

Oversees coaching and performance management; responsible for tracking and sharing best practices

Product owner

Agile coach

Squad member (but not leader); coordinates squad activities and sets priorities

Works with individuals and squads on collaboration and iterative problem solving

SOURCE ING

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HBR Special Issue 19

TODAY’S TALENT MANAGEMENT ONE BANK’S AGILE TEAM EXPERIMENT

Working in small, cross-functional units, squads can resolve issues far more quickly than in the past.

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designers, IT engineers, and product specialists. One squad member is designated the “product owner,” responsible for coordinating activities and setting priorities. The squad stays together as long as is required to meet the customer need from start to finish—whether it is, for example, improving user experience on the mobile app or building a particular feature. Some tasks are completed in two weeks; others might take 18 months. Sometimes the squads disband and the members join other ones. Most often, however, squads that are working well stay together and move on to address other customer needs. By working in such small units and with colleagues from various disciplines, squad members can quickly resolve issues that might previously have bounced from department to department. Information sharing is encouraged through mechanisms such as scrums and daily stand-ups—the kinds of gatherings you’d find at a tech start-up. Seeing a project through from start to finish gives each squad a sense of ownership and connection to the customer. Implementing an agile talent system doesn’t mean embracing chaos. In fact, a system that’s well designed observes clearly defined rules and safeguards to ensure institutional stability. Every tribe, for example, has a couple of agile coaches to help squads and individuals collaborate effectively in an environment where employees are encouraged to solve problems on the ground rather than pass them on to someone else. Although you might think adapting would be most difficult for long-term bank employees, that’s not so, according to ING Netherlands CIO Peter Jacobs. Many of them “adapted even more quickly and more readily than the younger generation,” he says, perhaps because their expertise now has more impact than in the past, when so many sign-offs were required. Then there are the chapters, which coordinate members of the same discipline—data analytics, say, or systems processes—who are scattered among squads. Chapter leads are responsible for tracking and sharing best practices and for such things as professional development and performance reviews. Think of chapters as a way of retaining the helpful parts of traditional management even while dispensing with time-consuming handoffs and bureaucracy. Regular assessments are built into the system. Every two weeks squads review their work. Says Hamers, “They get to decide how they will

continue to improve the product for our customers, or if they want to ‘fail fast.’” (Learning from failure is applauded.) Squads also do a thorough self-assessment after completing any engagement, and tribes perform quarterly business reviews (QBRs), looking at their biggest successes and failures, reviewing their most important learnings, and articulating goals for the next three months. These safeguards help counter what Vincent van den Boogert, the current CEO of ING Netherlands (and part of the team that launched the new organizational structure), sees as the two biggest challenges of a squad-based system. One is the possibility that self-empowered squads responding primarily to the needs of customers might embark on changes that aren’t in sync with company strategy. The QBRs mitigate that risk. The second challenge is somewhat counterintuitive. Selfevaluating squads are sometimes content with the incremental improvements they make every two weeks. The QBRs help in that regard, too, because top management uses them to formulate and reinforce stretch goals. More than two years in, Hamers considers the talent experiment a big success. Customer satisfaction and employee engagement are both up, and ING is quicker to market with new products. So the bank has started to roll out this new way of working to the roughly 40,000 employees outside its home country. For Hamers, the change can’t come soon enough. The apps for each of ING’s 13 retail markets vary in appearance, design, and function. Hamers wants to make things much simpler so that any customer, anywhere, will encounter the same ING. “Tech companies have one platform across the globe,” he says. “No matter where you use Netflix, Facebook, or Google, you get the same service. ING must do the same. That is the only way we will bring all our customers along into the future of banking.” HBR Reprint R1802B

Dominic Barton is a senior partner at McKinsey & Company. Dennis Carey is the vice chairman of Korn Ferry. Ram Charan has been an adviser to the CEOs of some of the world’s biggest corporations and their boards. They are the coauthors of Talent Wins: The New Playbook for Putting People First (Harvard Business Review Press, 2018).

TODAY’S TALENT MANAGEMENT

Reinventing Performance Management How one company is rethinking peer feedback and the annual review, and trying to design a system to fuel improvement by Marcus Buckingham and Ashley Goodall

A

T DELOITTE we’re redesigning

our performance management system. This may not surprise you. Like many other companies, we realize that our current process for evaluating the work of our people—and then training them, promoting them, and paying them accordingly—is increasingly out of step with our objectives. In a public survey Deloitte conducted recently, more than half the executives questioned (58%) believe that their current performance manage-

ILLUSTRATION BY LLOYD MILLER

ment approach drives neither employee engagement nor high performance. They, and we, are in need of something nimbler, real-time, and more individualized—something squarely focused on fueling performance in the future rather than assessing it in the past. What might surprise you, however, is what we’ll include in Deloitte’s new system and what we won’t. It will have no cascading objectives, no once-a-year reviews, and no 360-degreefeedback tools. We’ve arrived at a very different and much simpler design for managing people’s

Originally published in April 2015

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HBR Special Issue 23

TODAY’S TALENT MANAGEMENT REINVENTING PERFORMANCE MANAGEMENT

We tallied the number of hours the organization was spending on performance management and found that creating the ratings consumed close to 2 million hours a year.

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performance. Its hallmarks are speed, agility, one-size-fits-one, and constant learning, and it’s underpinned by a new way of collecting reliable performance data. This system will make much more sense for our talent-dependent business. But we might never have arrived at its design without drawing on three pieces of evidence: a simple counting of hours, a review of research in the science of ratings, and a carefully controlled study of our own organization.

Counting and the Case for Change More than likely, the performance management system Deloitte has been using has some characteristics in common with yours. Objectives are set for each of our 65,000-plus people at the beginning of the year; after a project is finished, each person’s manager rates him or her on how well those objectives were met. The manager also comments on where the person did or didn’t excel. These evaluations are factored into a single year-end rating, arrived at in lengthy “consensus meetings” at which groups of “counselors” discuss hundreds of people in light of their peers. Internal feedback demonstrates that our people like the predictability of this process and the fact that because each person is assigned a counselor, he or she has a representative at the consensus meetings. The vast majority of our people believe the process is fair. We realize, however, that it’s no longer the best design for Deloitte’s emerging needs: Once-a-year goals are too “batched” for a real-time world, and conversations about year-end ratings are generally less valuable than conversations conducted in the moment about actual performance. But the need for change didn’t crystallize until we decided to count things. Specifically, we tallied the number of hours the organization was spending on performance management—and found that completing the forms, holding the meetings, and creating the ratings consumed close to 2 million hours a year. As we studied how those hours were spent, we realized that many of them were eaten up by leaders’ discussions behind closed doors about the outcomes of the process. We wondered if we could somehow shift our investment of time from talking to ourselves about ratings to talking to our people about their performance and careers—from a focus on the past to a focus on the future.

The Science of Ratings Our next discovery was that assessing someone’s skills produces inconsistent data. Objective as I may try to be in evaluating you on, say, strategic thinking, it turns out that how much strategic thinking I do, or how valuable I think strategic thinking is, or how tough a rater I am significantly affects my assessment of your strategic thinking. How significantly? The most comprehensive research on what ratings actually measure was conducted by Michael Mount, Steven Scullen, and Maynard Goff and published in the Journal of Applied Psychology in 2000. Their study—in which 4,492 managers were rated on certain performance dimensions by two bosses, two peers, and two subordinates—revealed that 62% of the variance in the ratings could be accounted for by individual raters’ peculiarities of perception. Actual performance accounted for only 21% of the variance. This led the researchers to conclude (in How People Evaluate Others in Organizations, edited by Manuel London): “Although it is implicitly assumed that the ratings measure the performance of the ratee, most of what is being measured by the ratings is the unique rating tendencies of the rater. Thus ratings reveal more about the rater than they do about the ratee.” This gave us pause. We wanted to understand performance at the individual level, and we knew that the person in the best position to judge it was the immediate team leader. But how could we capture a team leader’s view of performance without running afoul of what the researchers termed “idiosyncratic rater effects”?

Putting Ourselves Under the Microscope We also learned that the defining characteristic of the very best teams at Deloitte is that they are strengths oriented. Their members feel that they are called upon to do their best work every day. This discovery was not based on intuitive judgment or gleaned from anecdotes and hearsay; rather, it was derived from an empirical study of our own high-performing teams. Our study built on previous research. Starting in the late 1990s, Gallup performed a multiyear examination of high-performing teams that eventually involved more than 1.4 million employees, 50,000 teams, and 192 organizations. Gallup asked both high- and lower-performing teams questions on numerous subjects, from mission and purpose

HBR.ORG

Idea in Brief to pay and career opportunities, and isolated the questions on which the high-performing teams strongly agreed and the rest did not. It found at the beginning of the study that almost all the variation between high- and lower-performing teams was explained by a very small group of items. The most powerful one proved to be “At work, I have the opportunity to do what I do best every day.” Business units whose employees chose “strongly agree” for this item were 44% more likely to earn high customer satisfaction scores, 50% more likely to have low employee turnover, and 38% more likely to be productive. We set out to see whether those results held at Deloitte. First we identified 60 high-performing teams, which involved 1,287 employees and represented all parts of the organization. For the control group, we chose a representative sample of 1,954 employees. To measure the conditions within a team, we employed a six-item survey. When the results were in and tallied, three items correlated best with high performance for a team: “My coworkers are committed to doing quality work,” “The mission of our company inspires me,” and “I have the chance to use my strengths every day.” Of these, the third was the most powerful across the organization. All this evidence helped bring into focus the problem we were trying to solve with our new design. We wanted to spend more time helping our people use their strengths—in teams characterized by great clarity of purpose and expectations—and we wanted a quick way to collect reliable and differentiated performance data. With this in mind, we set to work.

subtle shift in our approach. Rather than asking more people for their opinion of a team member (in a 360-degree or an upward-feedback survey, for example), we found that we will need to ask only the immediate team leader—but, critically, to ask a different kind of question. People may rate other people’s skills inconsistently, but they are highly consistent when rating their own feelings and intentions. To see performance at the individual level, then, we will ask team leaders not about the skills of each team member but about their own future actions with respect to that person. At the end of every project (or once every quarter for long-term projects) we will ask team leaders to respond to four future-focused statements about each team member. We’ve refined the wording of these statements through successive tests, and we know that at Deloitte they clearly highlight differences among individuals and reliably measure performance. Here are the four:

THE PROBLEM

1. Given what I know of this person’s performance,

THE SOLUTION

and if it were my money, I would award this person the highest possible compensation increase and bonus [measures overall performance and unique value to the organization on a five-point scale from “strongly agree” to “strongly disagree”].

Deloitte’s new approach separates compensation decisions from day-to-day performance management, produces better insight through quarterly or perproject “performance snapshots,” and relies on weekly check-ins with managers to keep performance on course.

2. Given what I know of this person’s performance, I would always want him or her on my team [measures ability to work well with others on the same five-point scale].

Not just employees but their managers and even HR departments are by now questioning the conventional wisdom of performance management, including its common reliance on cascading objectives, backward-looking assessments, once-a-year rankings and reviews, and 360-degreefeedback tools.

THE GOAL Some companies have ditched the rankings and even annual reviews, but they haven’t found better solutions. Deloitte resolved to design a system that would fairly recognize varying performance, have a clear view into performance anytime, and boost performance in the future.

3. This person is at risk for low performance [identifies problems that might harm the customer or the team on a yes-or-no basis].

Radical Redesign We began by stating as clearly as we could what performance management is actually for, at least as far as Deloitte is concerned. We articulated three objectives for our new system. The first was clear: It would allow us to recognize performance, particularly through variable compensation. Most current systems do this. But to recognize each person’s performance, we had to be able to see it clearly. That became our second objective. Here we faced two issues— the idiosyncratic rater effect and the need to streamline our traditional process of evaluation, project rating, consensus meeting, and final rating. The solution to the former requires a

4. This person is ready for promotion today [measures potential on a yes-or-no basis]. In effect, we are asking our team leaders what they would do with each team member rather than what they think of that individual. When we aggregate these data points over a year, weighting each according to the duration of a given project, we produce a rich stream of information for leaders’ discussions of what they, in turn, will do—whether it’s a question of succession planning, development paths, or performance-pattern analysis. Once a quarter the organization’s leaders can use the new data to review a targeted subset

In effect, we are asking our team leaders what they would do with each team member rather than what they think of that individual. FALL 2019

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TODAY’S TALENT MANAGEMENT REINVENTING PERFORMANCE MANAGEMENT

of employees (those eligible for promotion, for example, or those with critical skills) and can debate what actions Deloitte might take to better develop that particular group. In this aggregation of simple but powerful data points, we see the possibility of shifting our 2-million-hour annual investment from talking about the ratings to talking about our people—from ascertaining the facts of performance to considering what we should do in response to those facts. In addition to this consistent—and countable— data, when it comes to compensation, we want to factor in some uncountable things, such as the difficulty of project assignments in a given year and contributions to the organization other than formal projects. So the data will serve as the starting point for compensation, not the ending point. The final determination will be reached either by a leader who knows each individual personally or by a group of leaders looking at an entire segment of our practice and at many data points in parallel. We could call this new evaluation a rating, but it bears no resemblance, in generation or in use, to the ratings of the past. Because it allows us to quickly capture performance at a single moment in time, we call it a performance snapshot.

The Third Objective

In the end, it’s not the particular number we assign to a person that’s the problem; rather, it’s the fact that there is a single number. 26 HBR Special Issue

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Two objectives for our new system, then, were clear: We wanted to recognize performance, and we had to be able to see it clearly. But all our research, all our conversations with leaders on the topic of performance management, and all the feedback from our people left us convinced that something was missing. Is performance management at root more about “management” or about “performance”? Put differently, although it may be great to be able to measure and reward the performance you have, wouldn’t it be better still to be able to improve it? Our third objective therefore became to fuel performance. And if the performance snapshot was an organizational tool for measuring it, we needed a tool that team leaders could use to strengthen it. Research into the practices of the best team leaders reveals that they conduct regular checkins with each team member about near-term work. These brief conversations allow leaders to set expectations for the upcoming week, review priorities, comment on recent work, and provide

course correction, coaching, or important new information. The conversations provide clarity regarding what is expected of each team member and why, what great work looks like, and how each can do his or her best work in the upcoming days— in other words, exactly the trinity of purpose, expectations, and strengths that characterizes our best teams. Our design calls for every team leader to check in with each team member once a week. For us, these check-ins are not in addition to the work of a team leader; they are the work of a team leader. If a leader checks in less often than once a week, the team member’s priorities may become vague and aspirational, and the leader can’t be as helpful— and the conversation will shift from coaching for near-term work to giving feedback about past performance. In other words, the content of these conversations will be a direct outcome of their frequency: If you want people to talk about how to do their best work in the near future, they need to talk often. And so far we have found in our testing a direct and measurable correlation between the frequency of these conversations and the engagement of team members. Very frequent check-ins (we might say radically frequent check-ins) are a team leader’s killer app. That said, team leaders have many demands on their time. We’ve learned that the best way to ensure frequency is to have check-ins be initiated by the team member—who more often than not is eager for the guidance and attention they provide—rather than by the team leader. To support both people in these conversations, our system will allow individual members to understand and explore their strengths using a self-assessment tool and then to present those strengths to their teammates, their team leader, and the rest of the organization. Our reasoning is twofold. First, as we’ve seen, people’s strengths generate their highest performance today and the greatest improvement in their performance tomorrow, and so deserve to be a central focus. Second, if we want to see frequent (weekly!) use of our system, we have to think of it as a consumer technology—that is, designed to be simple, quick, and above all engaging to use. Many of the successful consumer technologies of the past several years (particularly social media) are sharing technologies, which suggests that most of us are consistently interested in ourselves—our own insights, achievements, and impact. So

HBR.ORG

Performance Intelligence In an early proof of concept of the redesigned system, executives in one large practice area at Deloitte called up data from project managers to consider important talent-related decisions. In the charts below, each dot represents an individual; decision makers could click on a dot to see the person’s name and details from his or her “performance snapshots.” WHAT ARE TEAM LEADERS TELLING US? First the group looked at the whole story. This view plotted all the members of the practice according to how much their various project managers agreed with two statements: “I would always want this person on my team” (y axis) and “I would give this person the highest possible compensation” (x axis). The axes are the same for the other three screens.

HOW WOULD THIS DATA HELP DETERMINE PAY? Next the data was filtered to look only at individuals at a given job level. A fundamental question for performance management systems is whether they can capture enough variation among people to fairly allocate pay. A data distribution like this offers a starting point for broader discussion.

5

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Level 6 Level 5 Level 4 Level 3 Level 2 Level 1

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Level 4 5

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HOW WOULD IT HELP GUIDE PROMOTIONS? This view was filtered to show individuals whose team leaders responded “yes” to the statement “This person is ready for promotion today.” The data supports objectivity in annual executive discussions about advancement.

HOW WOULD IT HELP ADDRESS LOW PERFORMANCE? This view was filtered to show individuals whose team leaders responded “yes” to the statement “This person is at risk of low performance.” As the upper right of this screen shows, even high performers can slip up—and it’s important that the organization help them recover.

5

5

Candidate for accelerated promotion

Not performing to expectations

4 But may not be eligible this year

Work style is 4 disruptive to the team—start remediation

3

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Tracking toward promotion

Team leaders’ 2 scores vary significantly 1

1

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Confirm eligibility according to work history and other metrics

Investigate discrepancies 3

4

A blip in otherwise high performance

1 5

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2

May need clarity on new responsibilities— address through coaching 3 4 5

SOURCE DELOITTE

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HBR Special Issue 27

TODAY’S TALENT MANAGEMENT REINVENTING PERFORMANCE MANAGEMENT

HOW DELOITTE BUILT A RADICALLY SIMPLE PERFORMANCE MEASURE One of the most important tools in our redesigned performance management system is the “performance snapshot.” It lets us see performance quickly and reliably across the organization, freeing us to spend more time engaging with our people. Here’s how we created it.

1

The Criteria We looked for measures that met three criteria. To neutralize the idiosyncratic rater effect, we wanted raters to rate their own actions, rather than the qualities or behaviors of the ratee. To generate the necessary range, the questions had to be phrased in the extreme. And to avoid confusion, each one had to contain a single, easily understood concept. We chose one about pay, one about teamwork, one about poor performance, and one about promotion. Those categories may or may not be right for other organizations, but they work for us.

2

The Rater We were looking for someone with vivid experience of the individual’s performance and whose subjective judgment we felt was important. We agreed that team leaders are closest to the performance of ratees and, by virtue of their roles, must exercise subjective judgment. We could have included functional managers, or even ratees’ peers, but we wanted to start with clarity and simplicity.

is, the questions should collectively test an underlying theory and make it possible to find correlations with outcomes measured in other ways, such as engagement surveys.)

4

Frequency At Deloitte we live and work in a project structure, so it makes sense for us to produce a performance snapshot at the end of each project. For longerterm projects we’ve decided that quarterly is the best frequency. Our goal is to strike the right balance between tying the evaluation as tightly as possible to the experience of the performance and not overburdening our team leaders, lest survey fatigue yield poor data.

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Transparency We’re experimenting with this now. We want our snapshots to reveal the real-time “truth” of what our team leaders think, yet our experience tells us that if they know that team members will see every data point, they may be tempted to sugarcoat the results to avoid difficult conversations. We know that we’ll aggregate an individual’s Testing snapshot scores into an annual composite. We then tested that our questions But what, exactly, should we share at year’s would produce useful data. Validity end? We want to err on the side of shartesting focuses on their difficulty (as revealed ing more, not less—to aggregate snapshot by mean responses) and the range of rescores not only for client work but also for sponses (as revealed by standard deviations). internal projects, along with performance We knew that if they consistently yielded a metrics such as hours and sales, in the contight cluster of “strongly agree” responses, text of a group of peers—so that we can give we wouldn’t get the differentiation we were our people the richest possible view of where looking for. Construct validity and criterionthey stand. Time will tell how close to that related validity are also important. (That ideal we can get.

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we want this new system to provide a place for people to explore and share what is best about themselves.

Transparency This is where we are today: We’ve defined three objectives at the root of performance management—to recognize, see, and fuel performance. We have three interlocking rituals to support them—the annual compensation decision, the quarterly or per-project performance snapshot, and the weekly check-in. And we’ve shifted from a batched focus on the past to a continual focus on the future, through regular evaluations and frequent check-ins. As we’ve tested each element of this design with ever-larger groups across Deloitte, we’ve seen that the change can be an evolution over time: Different business units can introduce a strengths orientation first, then more-frequent conversations, then new ways of measuring, and finally new software for monitoring performance. (See the exhibit “Performance Intelligence.”) But one issue has surfaced again and again during this work, and that’s the issue of transparency. When an organization knows something about us, and that knowledge is captured in a number, we often feel entitled to know it—to know where we stand. We suspect that this issue will need its own radical answer. In the first version of our design, we kept the results of performance snapshots from the team member. We did this because we knew from the past that when an evaluation is to be shared, the responses skew high—that is, they are sugarcoated. Because we wanted to capture unfiltered assessments, we made the responses private. We worried that otherwise we might end up destroying the very truth we sought to reveal. But what, in fact, is that truth? What do we see when we try to quantify a person? In the world of sports, we have pages of statistics for each player; in medicine, a three-page report each time we get blood work done; in psychometric evaluations, a battery of tests and percentiles. At work, however, at least when it comes to quantifying performance, we try to express the infinite variety and nuance of a human being in a single number. Surely, however, a better understanding comes from conversations—with your team leader about how you’re doing, or between leaders as they

consider your compensation or your career. And these conversations are best served not by a single data point but by many. If we want to do our best to tell you where you stand, we must capture as much of your diversity as we can and then talk about it. We haven’t resolved this issue yet, but here’s what we’re asking ourselves and testing: What’s the most detailed view of you that we can gather and share? How does that data support a conversation about your performance? How can we equip our leaders to have insightful conversations? Our question now is not What is the simplest view of you? but What is the richest?

Our question now is not What is the simplest view of you? but What is the richest?

OVER THE PAST few years the debate about performance management has been characterized as a debate about ratings—whether or not they are fair, and whether or not they achieve their stated objectives. But perhaps the issue is different: not so much that ratings fail to convey what the organization knows about each person but that as presented, that knowledge is sadly one-dimensional. In the end, it’s not the particular number we assign to a person that’s the problem; rather, it’s the fact that there is a single number. Ratings are a distillation of the truth—and up until now, one might argue, a necessary one. Yet we want our organizations to know us, and we want to know ourselves at work, and that can’t be compressed into a single number. We now have the technology to go from a small data version of our people to a big data version of them. As we scale up our new approach across Deloitte, that’s the issue we want to solve next. HBR Reprint R1504B

Marcus Buckingham is the head of People + Performance research at the ADP Research Institute. Ashley Goodall is the senior vice president of leadership and team intelligence at Cisco Systems. They are the authors of Nine Lies About Work: A Freethinking Leader’s Guide to the Real World (Harvard Business Review Press, 2019).

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TODAY’S TALENT MANAGEMENT

Better People Analytics Measure who they know, not just who they are. by Paul Leonardi and Noshir Contractor

“We have charts and graphs to back us up. So f *** off.”

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EW HIRES in Google’s people

Originally published in November–December 2018

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analytics department began receiving a laptop sticker with that slogan a few years ago, when the group probably felt it needed to defend its work. Back then people analytics—using statistical insights from employee data to make talent management decisions—was still a provocative idea with plenty of skeptics who feared it might lead companies to reduce individuals to numbers. HR collected data on workers, but the notion that it could be actively mined to understand and manage them was novel— and suspect. Today there’s no need for stickers. More than 70% of companies now say they consider people analytics to be a high priority. The field even has celebrated case studies, like Google’s Project Oxygen, which uncovered the practices of the tech giant’s best managers and then used them in coaching sessions to improve the work of

low performers. Other examples, such as Dell’s experiments with increasing the success of its sales force, also point to the power of people analytics. But hype, as it often does, has outpaced reality. The truth is, people analytics has made only modest progress over the past decade. A survey by Tata Consultancy Services found that just 5% of big-data investments go to HR, the group that typically manages people analytics. And a recent study by Deloitte showed that although people analytics has become mainstream, only 9% of companies believe they have a good understanding of which talent dimensions drive performance in their organizations. What gives? If, as the sticker says, people analytics teams have charts and graphs to back them up, why haven’t results followed? We believe it’s because most rely on a narrow approach to data analysis: They use data only about individual people, when data about the interplay among people is equally or more important. People’s interactions are the focus of an emerging discipline we call relational analytics. By

ILLUSTRATION BY LLOYD MILLER

TODAY’S TALENT MANAGEMENT BETTER PEOPLE ANALYTICS

Most people analytics teams rely on a narrow approach to data analysis. They use data only about individual people, when data about the interplay among people is equally or more important.

incorporating it into their people analytics strategies, companies can better identify employees who are capable of helping them achieve their goals, whether for increased innovation, influence, or efficiency. Firms will also gain insight into which key players they can’t afford to lose and where silos exist in their organizations. Fortunately, the raw material for relational analytics already exists in companies. It’s the data created by email exchanges, chats, and file transfers—the digital exhaust of a company. By mining it, firms can build good relational analytics models. In this article we present a framework for understanding and applying relational analytics. And we have the charts and graphs to back us up.

Relational Analytics: A Deeper Definition To date, people analytics has focused mostly on employee attribute data, of which there are two kinds: • Trait: facts about individuals that don’t change, such as ethnicity, gender, and work history.

Ideation Signature FOCUS: Individual PREDICTS: Which employees will come up with good ideas

• State: facts about individuals that do change, such as age, education level, company tenure, value of received bonuses, commute distance, and days absent. The two types of data are often aggregated to identify group characteristics, such as ethnic makeup, gender diversity, and average compensation. Attribute analytics is necessary but not sufficient. Aggregate attribute data may seem like relational data because it involves more than one person, but it’s not. Relational data captures, for example, the communications between two people in different departments in a day. In short, relational analytics is the science of human social networks. Decades of research convincingly show that the relationships employees have with one another— together with their individual attributes—can explain their workplace performance. The key is finding “structural signatures”: patterns in the data that correlate to some form of good (or bad) performance. Just as neurologists can identify structural signatures in the brain’s networks that predict bipolar disorder and schizophrenia, and chemists can look at the structural signatures of a liquid and predict its kinetic fragility, organizational leaders can look at structural signatures in their companies’ social networks and predict how, say, creative or effective individual employees, teams, or the organization as a whole will be.

The Six Signatures of Relational Analytics Drawing from our own research and our consulting work with companies, as well as from a large body of other scholars’ research, we have identified six structural signatures that should form the bedrock of any relational analytics strategy. Let’s look at each one in turn.

Ideation

Purple shows low constraint: He communicates with people in several other networks besides his own, which makes him more likely to get novel information that will lead to good ideas. Orange, who communicates only with people within his network, is less likely to generate ideas, even though he may be creative.

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Most companies try to identify people who are good at ideation by examining attributes like educational background, experience, personality, and native intelligence. Those things are important, but they don’t help us see people’s access to information from others or the diversity of their sources of information—both of which are arguably even more important. Good

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Idea in Brief idea generators often synthesize information from one team with information from another to develop a new product concept. Or they use a solution created in one division to solve a problem in another. In other words, they occupy a brokerage position in networks. The sociologist Ronald Burt has developed a measure that indicates whether someone is in a brokerage position. Known as constraint, it captures how limited a person is when gathering unique information. Study after study, across populations as diverse as bankers, lawyers, analysts, engineers, and software developers, has shown that employees with low constraint—who aren’t bound by a small, tight network of people— are more likely to generate ideas that management views as novel and useful. In one study, Burt followed the senior leaders at a large U.S. electronics company as they applied relational analytics to determine which of 600plus supply chain managers were most likely to develop ideas that improved efficiency. They used a survey to solicit such ideas from the managers and at the same time gather information on their networks. Senior executives then scored each of the submitted ideas for their novelty and potential value. The only attribute that remotely predicted whether an individual would generate a valuable idea was seniority at the company, and its correlation wasn’t strong. Using the ideation signature— low constraint—was far more powerful: Supply chain managers who exhibited it in their networks were significantly more likely to generate good ideas than managers with high constraint. A study Paul did at a large software development company bolsters this finding. The company’s R&D department was a “caveman world.” Though it employed more than 100 engineers, on average each one talked to only five other people. And those five people typically talked only to one another. Their contact with other “caves” was limited. Such high-constraint networks are quite common in organizations, especially those that do specialized work. But that doesn’t mean lowconstraint individuals aren’t hiding in plain sight. At the software company, relational analytics was able to pinpoint a few engineers who did span multiple networks. Management then generated a plan for encouraging them to do what they were naturally inclined to, and soon saw a significant

increase in both the quantity—and quality—of ideas they proposed for product improvements.

Influence Developing a good idea is no guarantee that people will use it. Similarly, just because an executive issues a decree for change, that doesn’t mean employees will carry it out. Getting ideas implemented requires influence. But influence doesn’t work the way we might assume. Research shows that employees are not most influenced, positively or negatively, by the company’s senior leadership. Rather, it’s people in less formal roles who sway them the most. If that’s the case, executives should just identify the popular employees and have them persuade their coworkers to get on board with new initiatives, right? Wrong. A large medical device manufacturer that Paul worked with tried that approach when it was launching new compliance policies. Hoping to spread positive perceptions about them, the change management team shared the policies’ virtues with the workers who had been rated influential by the highest number of colleagues. But

THE CHALLENGE To bring the performance of people analytics up—and in line with the hype—companies need to do more than analyze data on demographic attributes.

THE SOLUTION Employ relational analytics, which examines data on how people interact, to find out who has good ideas, who is influential, what teams will get work done on time, and more.

THE RAW MATERIAL Companies can mine their “digital exhaust”—data created by employees every day in their digital transactions, such as emails, chats, and file collaboration—for insights into their workforce.

Influence Signature FOCUS: Individual PREDICTS: Which employees will change others’ behavior

Though she connects to only two people, purple is more influential than orange, because purple’s connections are better connected. Purple shows higher aggregate prominence. Orange may spread ideas faster, but purple can spread ideas further because her connections are more influential.

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Influence doesn’t work the way we might assume. Research shows that employees are not most influenced by the company’s senior leadership. Rather, it’s people in less formal roles who sway them the most.

six months later employees still weren’t following the new procedures. Why? A counterintuitive insight from relational analytics offers the explanation: Employees cited as influential by a large number of colleagues aren’t always the most influential people. Rather, the greatest influencers are people who have strong connections to others, even if only to a few people. Moreover, their strong connections in turn have strong connections of their own with other people. This means influencers’ ideas can spread further. The structural signature of influence is called aggregate prominence, and it’s computed by measuring how well a person’s connections are connected, and how well the connections’ connections are connected. (A similar logic is used by search engines to rank-order search results.) In each of nine divisions at the medical device manufacturer, relational analytics identified the five individuals who had the highest aggregate prominence scores. The company asked for their thoughts on the new policies. About three-quarters viewed them favorably. The firm provided facts that would allay fears of the change

Efficiency Signature FOCUS: Team PREDICTS: Which teams will complete projects on time

The purple team members are deeply connected with one another—showing high internal density. This indicates that they work well together. And because members’ external connections don’t overlap, the team has high external range, which gives it greater access to helpful outside resources.

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to them as well as to the influencers who didn’t like the policies—and then waited for the results. Six months later more than 75% of the employees in those nine divisions had adopted the new compliance policies. In contrast, only 15% of employees had adopted them in the remaining seven affected divisions, where relational analytics had not been applied.

Efficiency Staffing a team that will get work done efficiently seems as if it should be simple. Just tap the people who have the best relevant skills. Attribute analytics can help identify skilled people, but it won’t ensure that the work gets done on time. For that, you need relational analytics measuring team chemistry and the ability to draw on outside information and expertise. Consider the findings of a study by Ray Reagans, Ezra Zuckerman, and Bill McEvily, which analyzed more than 1,500 project teams at a major U.S. contract R&D firm. Hypothesizing that the ability to access a wide range of information, perspectives, and resources would improve team performance, the researchers compared the effect of demographic diversity on teams’ results with the effect of team members’ social networks. One issue was that diversity at the firm had only two real variables, tenure and function. (The other variables—race, gender, and education—were consolidated within functions.) Nevertheless, the results showed that diversity in those two areas had little impact on performance. Turning to the relational data, though, offered better insight. The researchers found that two social variables were associated with higher performance. The first was internal density, the amount of interaction and interconnectedness among team members. High internal density is critical for building trust, taking risks, and reaching agreement on important issues. The second was the external range of team members’ contacts. On a team that has high external range, each member can reach outside the team to experts who are distinct from the contacts of other members. That makes the team better able to source vital information and secure resources it needs to meet deadlines. The structural signature for efficient teams is therefore high internal density plus high external range.

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At the R&D firm the teams that had this signature completed projects much faster than teams that did not. The researchers estimated that if 30% of project teams at the firm had internal density and external range just one standard deviation above the mean, it would save more than 2,200 labor hours in 17 days—the equivalent of completing nearly 200 additional projects.

Innovation Signature FOCUS: Team PREDICTS: Which teams will innovate effectively

Innovation Teams with the efficiency signature would most likely fail as innovation units, which benefit from some disagreement and strife. What else makes for a successful team of innovators? You might think that putting your highest-performing employees together would produce the best results, but research suggests that it might have negative effects on performance. And while the conventional wisdom is that teams are more creative when they comprise members with different points of view, research also indicates that demographic diversity is not a good predictor of team innovation success. In our experience, even staffing an innovation team with ideators often produces no better than average performance. But if you turn to relational analytics, you can use the same variables you use for team efficiency—internal density and external range— to create promising innovation teams. The formula is a bit different, though: The innovation signature is high external range and low internal density. That is, you still want team members with wide, nonoverlapping social networks (influential ones, if possible) to source diverse ideas and information. But you do not want a tight-knit team. Why? Greater interaction within a team results in similar ways of thinking and less discord. That’s good for efficiency but not for innovation. The most innovative teams have disagreements and discussion—sometimes even conflict—that generate the creative friction necessary to produce breakthroughs. The high external range is needed not just to bring in ideas but also to garner support and buy-in. Innovation teams have to finance, build, and sell their ideas, so well-connected external contacts who become the teams’ champions can have a big impact on their success.

Purple team members aren’t deeply interconnected; their team has low internal density. This suggests they’ll have different perspectives and more-productive debates. The members also have high external range, or wide, diverse connections, which will help them gain buy-in for their innovations.

For several years, Paul worked with a large U.S.-based automobile company that was trying to improve its product-development process. Each of its global product-development centers had a team of subject-matter experts focused on that challenge. The program leader noted, “We are very careful about who we select. We get the people with the right functional backgrounds, who have consistently done innovative work, and we make sure there is a mix of them from different backgrounds and that they are different ages.” In other words, the centers used attribute analytics to form teams. Managers at a new India center couldn’t build a demographically diverse team, however: All the center’s engineers were roughly the same age, had similar backgrounds, and were about the same rank. So the manager instead chose engineers who had worked on projects with different offices and worked in different areas of the center—creating a team that naturally had a higher external range. It so happened that such a team showed lower internal density as well. Its members felt free to debate, and they ran tests to resolve differences of opinion. Once they found a new procedure, they went back to their external connections, using

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If 30% of project teams at the firm had internal density and external range just one standard deviation above the mean, it would save more than 2,200 labor hours in 17 days.

them as influencers who could persuade others to validate their work. After three years the India center’s team was producing more process innovations than any of the other teams. After five years it had generated almost twice as many as all the other teams combined. In response, the company began supplementing its attribute analytics with relational analytics to reconfigure the innovation teams at its other locations.

Silos Everyone hates silos, but they’re natural and unavoidable. As organizations develop deep areas of expertise, almost inevitably functions, departments, and divisions become less and less able to work together. They don’t speak the same technical language or have the same goals. We assess the degree to which an organization is siloed by measuring its modularity. Most simply, modularity is the ratio of communication within a group to communication outside the group. When the ratio of internal to external

Silo Signature FOCUS: Organization PREDICTS: Whether an organization is siloed

communication is greater than 5:1, the group is detrimentally siloed. One of the most strikingly siloed organizations we’ve encountered was a small not-forprofit consumer advocacy group, which wanted to understand why traffic on its website had declined. The 60 employees at its Chicago office were divided among four departments: business development, operations, marketing and PR, and finance. Typical of silos, each department had different ideas about what was going on. Analysis showed that all four departments exceeded the 5:1 ratio of internal to external contacts. The most extreme case was operations, with a ratio of 13:1. Of course, operations was the department with its finger most squarely on the pulse of consumers who visited the site. It sat on a trove of data about when and why people came to the site to complain about or praise companies. Other departments didn’t even know that operations collected that data. And operations didn’t know that other departments might find it useful. To fix the problem, the organization asked specific employees in each department to become liaisons. They instituted a weekly meeting at which managers from all departments got together to talk about their work. Each meeting was themed, so lower-level employees whose work related to the theme also were brought into the discussions. In short, the not-for-profit engineered higher external range into its staff. As a result, operations learned that marketing and PR could make hay out of findings that linked a growing volume of complaints in a specific industry to certain weather patterns and seasons. Because operations employees learned that such insights would be useful, they began to analyze their data in new ways.

Vulnerability

Each color indicates a department. People within the departments are deeply connected, but only one or two people in any department connect with people in other departments. The groups’ modularity—the ratio of internal to external communication—is high.

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Although having people who can help move information and insights from one part of the organization to another is healthy, an overreliance on those individuals can make a company vulnerable. Take the case of an employee we’ll call Arvind, who was a manager in the packaging division at one of the world’s top consumer goods companies. He was a connector who bridged several divisions. He talked regularly with counterparts and suppliers across the world. But on the organizational chart, Arvind was nobody special: just a midlevel manager who was good at his job.

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Capture Your Company’s Digital Exhaust Once you understand the six structural signatures that form the basis of relational analytics, it’s relatively easy to act on the insights they provide. Often, the fixes they suggest aren’t complex: Set up cross-functional meetings, enable influential people, retain your Arvinds. Why, then, don’t most companies use relational analytics for performance management? There are two reasons. The first is that many network analyses companies do are little more than pretty pictures of nodes and edges. They don’t identify the patterns that predict performance. The second reason is that most organizations don’t have information systems in place to capture relational data. But all companies do have a crucial hidden resource: their digital exhaust—

Vulnerability Signature FOCUS: Organization PREDICTS: Which employees the organization can’t afford to lose

r lie pp any Su mp Co

Companies are at risk of losing employees like Arvind because no obvious attribute signals their importance, so firms don’t know what they’ve got until it’s gone. Without Arvind, the packaging division would lack robustness. Networks are robust when connections can be maintained if you remove nodes—employees—from it. In this case, if Arvind left the company, some departments would lose all connection with other departments and with suppliers. It wasn’t that Arvind was irreplaceable. He just wasn’t backed up. The company didn’t realize that no other nodes were making the necessary network connections he provided. That made it vulnerable: If Arvind was out sick or on vacation, work slowed. If Arvind decided that he didn’t like one of the suppliers and stopped interacting with it, work slowed. And if Arvind had too much on his plate and couldn’t keep up with his many connections, work also slowed. On the day Noshir came to show the company this vulnerability in the packaging division, he entered a boardroom filled with cakes and sweets. A senior executive happily told him that the firm was throwing a party for Arvind. He was retiring. Noshir’s jaw dropped. The party went on, but after learning how important Arvind was, the company worked out a deal to retain him for several more years and, in the meantime, used relational analytics to do some succession planning so that multiple people could take on his role.

Green is a critical external supplier to company departments blue, purple, and orange. Six people at the company have relationships with green, but 30 people rely on those relationships—which puts the company at risk. If blue’s one connection to green leaves, for example, the department will be cut off from the supplier. While his title may not reflect his importance, that employee is vital to information flow.

the logs, e-trails, and contents of everyday digital activity. Every time employees send one another emails in Outlook, message one another on Slack, like posts on Facebook’s Workplace, form teams in Microsoft Teams, or assign people to project milestones in Trello, the platforms record the interactions. This information can be used to construct views of employee, team, and organizational networks in which you can pick out the structural signatures we’ve discussed. For several years we’ve been developing a dashboard that captures digital exhaust in real time from these various platforms and uses relational analytics to help managers find the right employees for tasks, staff teams for efficiency and innovation, and identify areas in the organization that are siloed and vulnerable to turnover. Here are some of the things we’ve learned in the process:

Passive collection is easier on employees. To gather relational data, companies typically survey employees about whom they interact with. Surveys take time, however, and the answers can

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WHAT ABOUT EMPLOYEE PRIVACY? Relational analytics changes the equation when it comes to the privacy of employee data. When employees actively provide information about themselves in hiring forms, surveys, and the like, they know their company has and can use it. But they may not even realize that the passive collection of relational data—such as whom they chat with on Slack or when they were copied on email—is happening or that such information is being analyzed. Job one for companies is to be transparent. If they’re going to amass digital exhaust, they should ask employees to sign an agreement indicating they understand that their patterns of interaction on company-owned tools will be tracked for the purposes of analyzing the organization’s social networks. Full disclosure with employee consent is the only option. We’ve found some additional moves leaders can make to get ahead of privacy concerns: First, give employees whatever relational data you collect about them. We recommend providing it at least annually. The data can include a map of the employee’s own network and benchmarks. For example, a report could provide an employee with her constraint score (which shows how inbred someone’s social network is) and the average constraint score of employees in her department. That score could then be at the center of a mentoring discussion.

vary in accuracy (some employees are just guessing). Also, to be truly useful, relational data must come from everyone at the company, not just a few people. As an executive at a large financial services company told us, “If I gave each of my 15,000 employees a survey that takes half an hour to do, we’ve just lost a million dollars in productivity. And what if their relationships change in a month?

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Second, be clear about the depth of relational analytics you intend to invest in. The level that is most basic—and the least prone to privacy concerns—is generic pattern analysis. The analysis might show, for example, that marketing is a silo but not identify specific individuals that contribute to that silo. Or the analysis could show that a certain percentage of teams have the signature for innovation but not identify which teams. The second level identifies which specific employees in a company have certain kinds of networks. Scores may provide evidence-based predictions about employee behavior—such as who is likely to be an influencer or whose departure would make an organization vulnerable. Although this level of analysis provides more value to the company, it singles particular employees out. The highest level pairs relational analytics with machine learning. In this scenario, companies collect data about whom employees interact with and about the topics they discuss. Firms examine the content of emails and posts on social-networking sites to identify who has expertise in what domains. This information provides the most specific guidance for leaders—for example, about who is likely to develop good ideas in certain areas. This most advanced level obviously also comes with the most privacy concerns, and senior leadership must develop deeply considered strategies to deal with them.

Will we have to do it again at a cost of an additional $1 million in people hours?” Company-collected relational data, however, creates new challenges. Although most employment contracts give firms the right to record and monitor activities conducted on company systems, some employees feel that the passive collection of relational data is an invasion of privacy.

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This is not a trivial concern. Companies need clear HR policies about the gathering and analysis of digital exhaust that help employees understand and feel comfortable with it. (See the sidebar “What About Employee Privacy?”)

Behavioral data is a better reflection of reality. As we’ve noted, digital exhaust is less biased than data collected through surveys. For instance, in surveys people may list connections they think they’re supposed to interact with, rather than those they actually do interact with. And because every employee will be on at least several communication platforms, companies can map networks representing the entire workforce, which makes the analysis more accurate. Also, not all behaviors are equal. Liking someone’s post is different from working on a team with someone for two years. Copying someone on an email does not indicate a strong relationship. How all those individual behaviors are weighted and combined matters. This is where machinelearning algorithms and simulation models are helpful. With a little technical know-how (and with an understanding of which structural signatures predict what performance outcomes), setting up those systems is not hard to do. Constant updating is required. Relationships are dynamic. People and projects come and go. To be useful, relational data must be timely. Using digital exhaust in a relational analytics model addresses that need. Additionally, collecting relational data over time gives analysts more choices about what to examine. For example, if an employee was out on maternity leave for several months, an analyst can exclude that time period from the data or decide to aggregate a larger swath of data. If a company was acquired in a particular year, an analyst can compare relational data from before and after the deal to chart how the company’s vulnerabilities may have changed.

moves analytic insights closer to the managers who need them. As one executive at a semiconductor chip firm told us, “I want my managers to have the data to make good decisions about how to use their employees. And I want them to be able to do it when those decision points happen, not later.”

PEOPLE ANALYTICS is a new way to make evidence-based decisions that improve organizations. But in these early days, most companies have been focused on the attributes of individuals, rather than on their relationships with other employees. Looking at attributes will take firms only so far. If they harness relational analytics, however, they can estimate the likelihood that an employee, a team, or an entire organization will achieve a performance goal. They can also use algorithms to tailor staff assignments to changes in employee networks or to a particular managerial need. The best firms, of course, will use relational analytics to augment their own decision criteria and build healthier, happier, and moreproductive organizations. HBR Reprint R1806E

It wasn’t that Arvind was irreplaceable. He just wasn’t backed up. The company didn’t realize that no one else was making the network connections he provided. If Arvind was out sick or on vacation, work slowed.

Paul Leonardi is the Duca Family Professor of Technology Management at the University of California, Santa Barbara, and advises companies about how to use social network data and new technologies to improve performance and employee well-being. Twitter: @pleonardi1. Noshir Contractor is the Jane S. and William J. White Professor of Behavioral Sciences at Northwestern University, where he directs the Science of Networks in Communities (SONIC) group, which helps organizations understand and leverage networks. Twitter: @noshir.

Analyses need to be close to decision makers. Most companies rely on data scientists to cull insights related to talent and performance management. That often creates a bottleneck, because there aren’t enough data scientists to address all management queries in a timely manner. Plus, data scientists don’t know the employees they are running analyses on, so they cannot put results into context. Dashboards are key. A system that identifies structural signatures and highlights them visually

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“Numbers Take Us Only So Far” Facebook’s global director of diversity explains why stats alone won’t solve the problem of organizational bias. by Maxine Williams

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WAS ONCE EVICTED from an apartment

because I was black. I had secured a lovely place on the banks of Lake Geneva through an agent and therefore hadn’t met the owner in person before signing the lease. Once my family and I moved in and the color of my skin was clear to see, the landlady asked us to leave. If she had known that I was black, I was told, she would never have rented to me. Terrible as it felt at the time, her directness was useful to me. It meant I didn’t have to scour the facts looking for some other, nonracist rationale for her sudden rejection. Many people have been denied housing, bank loans, jobs, promotions, and more because of their race. But they’re rarely told that’s the reason, as I was—particularly in the workplace. For one thing, such discrimination is illegal. For another, executives tend to think—and have a strong desire to believe—that they’re hiring and promoting people fairly when they aren’t. (Research shows that individuals who view themselves as

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objective are often the ones who apply the most unconscious bias.) Though managers don’t cite or (usually) even perceive race as a factor in their decisions, they use ambiguous assessment criteria to filter out people who aren’t like them, research by Kellogg professor Lauren Rivera shows. People in marginalized racial and ethnic groups are deemed more often than whites to be “not the right cultural fit” or “not ready” for high-level roles; they’re taken out of the running because their “communication style” is somehow off the mark. They’re left only with lingering suspicions that their identity is the real issue, especially when decision makers’ bias is masked by good intentions. I work in the field of diversity. I’ve also been black my whole life. So I know that underrepresented people in the workplace yearn for two things: The first is to hear that they’re not crazy to suspect, at times, that there’s a connection between negative treatment and bias. The second is to be offered institutional support. The first need has a clear path to fulfillment. When we encounter colleagues or friends who have been mistreated and who believe that their identity may be the reason, we should acknowledge that it’s fair to be suspicious. There’s no leap of faith here—numerous studies show how pervasive such bias still is. But how can we address the second need? In an effort to find valid, scalable ways to counteract or reverse bias and promote diversity, organizations are turning to people analytics—a relatively new field in business operations and talent management that replaces gut decisions with data-driven practices. People analytics aspires to be “evidence based.” And for some HR issues—such as figuring out how many job interviews are needed to assess a candidate, or determining how employees’ work commutes affect their job satisfaction—it is. Statistically significant findings have led to some big changes in organizations. Unfortunately, companies that try to apply analytics to the challenges of underrepresented groups at work often complain that the relevant data sets don’t include enough people to produce reliable insights—the sample size, the n, is too small. Basically they’re saying, “If only there were more of you, we could tell you why there are so few of you.” Companies have access to more data than they realize, however. To supplement a small n, they can venture out and look at the larger context in which they operate. But data volume alone won’t

give leaders the insight they need to increase diversity in their organizations. They must also take a closer look at the individuals from underrepresented groups who work for them—those who barely register on the analytics radar.

Supplementing the N Nonprofit research organizations are doing important work that sheds light on how bias shapes hiring and advancement in various industries and sectors. For example, a study by the Ascend Foundation showed that in 2013 white men and white women in five major Silicon Valley firms were 154% more likely to become executives than their Asian counterparts were. And though both race and gender were factors in the glass ceiling for Asians, race had 3.7 times the impact that gender did. It took two more years of research and analysis— using data on several hundred thousand employees, drawn from the EEOC’s aggregation of all Bay Area technology firms and from the individual reports of 13 U.S. tech companies—before Ascend determined how bias affected the prospects of blacks and Hispanics. Among those groups it again found that, overall, race had a greater negative impact than gender on advancement from the professional to the executive level. In the Bay Area white women fared worse than white men but much better than all Asians, Hispanics, and blacks. Minority women faced the biggest obstacle to entering the executive ranks. Black and Hispanic women were severely challenged by both their low numbers at the professional level and their lower chances of rising from professional to executive. Asian women, who had more representation at the professional level than other minorities, had the lowest chances of moving up from professional to executive. An analysis of national data found similar results. By analyzing industry or sector data on underrepresented groups—and examining patterns in hiring, promotions, and other decisions about talent—we can better manage the problems and risks in our own organizations. Tech companies may look at the Ascend reports and say, “Hey, let’s think about what’s happening with our competitors’ talent. There’s a good chance it’s happening here, too.” Their HR teams might then add a layer of career tracking for women of color, for example, or create training programs for managing diverse teams.

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Idea in Brief Another approach is to extrapolate lessons from other companies’ analyses. We might look, for instance, at Red Ventures, a Charlotte-based digital media company. Red Ventures is diverse by several measures. (It has a Latino CEO, and about 40% of its employees are people of color.) But that doesn’t mean there aren’t problems to solve. When I met with its top executives, they told me they had recently done an analysis of performance reviews at the firm and found that internalized stereotypes were having a negative effect on black and Latino employees’ self-assessments. On average, members of those two groups rated their performance 30% lower than their managers did (whereas white male employees scored their performance 10% higher than their managers did). The study also uncovered a correlation between racial isolation and negative self-perception. For example, people of color who worked in engineering generally rated themselves lower than those who worked in sales, where there were more blacks and Latinos. These patterns were consistent at all levels, from junior to senior staff. In response, the HR team at Red Ventures trained employees in how to do self-assessments, and that has started to close the gap for blacks and Latinos (who more recently rated themselves 22% lower than their managers did). Hallie Cornetta, the company’s VP of human capital, explained that the training “focused on the importance of completing quantitative and qualitative self-assessments honestly, in a way that shows how employees personally view their performance across our five key dimensions, rather than how they assume their manager or peers view their performance.” She added: “We then shared tangible examples of what ‘exceptional’ versus ‘solid’ versus ‘needs improvement’ looks like in these dimensions to remove some of the subjectivity and help minority—and all— employees assess with greater direction and confidence.”

Getting Personal Once we’ve gone broader by supplementing the n, we can go deeper by examining individual cases. This is critical. Algorithms and statistics do not capture what it feels like to be the only black or Hispanic team member or the effect that marginalization has on individual employees and the group as a whole. We must talk openly with people, one-

on-one, to learn about their experiences with bias, and share our own stories to build trust and make the topic safe for discussion. What we discover through those conversations is every bit as important as what shows up in the aggregated data. An industry colleague, who served as a lead on diversity at a tech company, broke it down for me like this: “When we do our employee surveys, the Latinos always say they are happy. But I’m Latino, and I know that we are often hesitant to rock the boat. Saying the truth is too risky, so we’ll say what you want to hear—even if you sit us down in a focus group. I also know that those aggregated numbers where there are enough of us for the n to be significant don’t reflect the heterogeneity in our community. Someone who is light-skinned and grew up in Latin America in an upper-middle-class family probably is very happy and comfortable indeed. Someone who is darker-skinned and grew up working-class in America is probably not feeling that same sense of belonging. I’m going to spend time and effort trying to build solutions for the ones I know are at a disadvantage, whether the data tells me that there’s a problem with all Latinos or not.” This is a recurring theme. I spoke with 10 diversity and HR professionals at companies with head counts ranging from 60 to 300,000, all of whom are working on programs or interventions for the people who don’t register as “big” in big data. They rely at least somewhat on their own intuition when exploring the impact of marginalization. This may seem counter to the mission of people analytics, which is to remove personal perspective and gut feelings from the talent equation entirely. But to discover the effects of bias in our organizations—and to identify complicating factors within groups, such as class and colorism among Latinos and others—we need to collect and analyze qualitative data, too. Intuition can help us find it. The diversity and HR folks described using their “spidey sense” or knowing there is “something in the water”—essentially, understanding that bias is probably a factor, even though people analytics doesn’t always prove causes and predict outcomes. Through conversations with employees—and sometimes through focus groups, if the resources are there and participants feel it’s safe to be honest—they reality-check what their instincts tell them, often drawing on their own experiences with bias. One colleague said, “The combination of qualitative and quantitative data

THE PROBLEM Despite executives’ belief that they hire and promote fairly, we know that people have been denied jobs and advancement because of their race. Managers often use ambiguous assessment criteria to filter out people who are not like them, and those in marginalized racial and ethnic groups are deemed more often than whites to be “not the right cultural fit” or “not ready” for high-level roles. Organizations need to find valid, scalable ways to counteract or reverse the biases behind these choices and to promote diversity.

PEOPLE ANALYTICS People analytics offers some help by replacing gut decisions with data-driven practices. But not everyone registers on this radar—particularly not underrepresented groups. Hence organizations are left basically saying: “If only there were more of you, we could tell you why there are so few of you.”

THE SOLUTION When the numbers for an underrepresented group are too small to study in your organization, the author suggests including research on that population from the larger industry or context, learning from the experiences of other firms, and doing qualitative research into individual cases within your company. Because no single research method captures all the layers of bias, companies like Facebook are building crossfunctional teams to face and address such challenges.

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is ideal, but at the end of the day there is nothing that data will tell us that we don’t already know as black people. I know what my experience was as an African-American man who worked for 16 years in roles that weren’t related to improving diversity. It’s as much heart as head in this work.”

A Call to Action The proposition at the heart of people analytics is sound—if you want to hire and manage fairly, gut-based decisions are not enough. However, we have to create a new approach, one that also works for small data sets—for the marginalized and the underrepresented. Here are my recommendations: First, analysts must challenge the traditional minimum confident n, pushing themselves to look beyond the limited hard data. They don’t have to prove that the difference in performance ratings between blacks and whites is “statistically significant” to help managers understand the impact of bias in performance reviews. We already know from the breadth and depth of social science research about bias that it is pervasive in the workplace and influences ratings, so we can combine those insights with what we hear and see on the ground and simply start operating as if bias exists in our companies. We may have to place a higher value on the experiences shared by five or 10 employees—or look more carefully at the descriptive data, such as head counts for underrepresented groups and average job satisfaction scores cut by race and gender—to examine the impact of bias at a more granular level. In addition, analysts should frequently provide confidence intervals—that is, guidance on how much managers can trust the data if the n’s are too small to prove statistical significance. When managers get that information, they’re more likely to make changes in their hiring and management practices, even if they believe—as most do—that they are already treating people fairly. Suppose, for example, that as Red Ventures began collecting data on self-assessments, analysts had a 75% confidence level that blacks and Latinos were underrating themselves. The analysts could then have advised managers to go to their minority direct reports, examine the results from that performance period, and determine together whether the self-reviews truly reflected their contributions. It’s a simple but collaborative way to address implicit

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bias or stereotyping that you’re reasonably sure is there while giving agency to each employee. Second, companies also need to be more consistent and comprehensive in their qualitative analysis. Many already conduct interviews and focus groups to gain insights on the challenges of the underrepresented; some even do textual analysis of written performance reviews, exit interview notes, and hiring memos, looking for language that signals bias or negative stereotyping. But we have to go further. We need to find a viable way to create and process more-objective performance evaluations, given the internalized biases of both employees and managers, and to determine how those biases affect ratings. This journey begins with educating all employees on the real-life impact of bias and negative stereotypes. At Facebook we offer a variety of training programs with an emphasis on spotting and counteracting bias, and we keep reinforcing key messages post-training, since we know these muscles take time to build. We issue reminders at critical points to shape decision making and behavior. For example, in our performance evaluation tool, we incorporate prompts for people to check word choice when writing reviews and self-assessments. We remind them, for instance, that terms like “cultural fit” can allow bias to creep in and that they should avoid describing women as “bossy” if they wouldn’t describe men who demonstrated the same behaviors that way. We don’t yet have data on how this is influencing the language used—it’s a new intervention—but we will be examining patterns over time. Perhaps above all, HR and analytics departments must value both qualitative and quantitative expertise and apply mixed-method approaches everywhere possible. At Facebook we’re building cross-functional teams with both types of specialists, because no single research method can fully capture the complex layers of bias that everyone brings to the workplace. We view all research methods as trying to solve the same problem from different angles. Sometimes we approach challenges from a quantitative perspective first, to uncover the “what” before looking to the qualitative experts to dive into the “why” and “how.” For instance, if the numbers showed that certain teams were losing or attracting minority employees at higher rates than others (the “what”), we might conduct interviews, run focus groups, or analyze text from company surveys to understand

Algorithms and statistics do not capture what it feels like to be the only black or Hispanic member of a team. the “why,” and pull out themes or lessons for other parts of the company. In other scenarios we might reverse the order of those steps. For example, if we repeatedly heard from members of one social group that they weren’t seeing their peers getting recognized at the same rate as people in other groups, we could then investigate whether numerical trends confirmed those observations, or conduct statistical analyses to figure out which organizational circumstances were associated with employees’ being more or less likely to get recognized. Cross-functional teams also help us reap the benefits of cognitive diversity. Working together stretches everyone, challenging team members’ own assumptions and biases. Getting to absolute “whys” and “hows” on any issue, from recruitment to engagement to performance, is always going to be tough. But we believe that with this approach, we stand the best chance of making improvements across the company. As we analyze the results of Facebook’s Pulse survey, given twice a year to employees, and review Performance Summary Cycle inputs, we’ll continue to look for signs of problems as well as progress.

EVIDENCE OF DISCRIMINATION or unfair outcomes may not be as certain or obvious in the workplace as it was for me the time I was evicted from my apartment. But we can increase our certainty, and it’s essential that we do so. The underrepresented people at our companies are not crazy to perceive biases working against them, and they can get institutional support. HBR Reprint R1706L

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Quick Takes

Is HR the Most Analytics-Driven Function? by Thomas H. Davenport

I HAVE ARGUED over the past decade that the HR function has the potential to become one of the leaders in analytics. The key word, I thought, was potential. Not anymore. A recent global survey on which I collaborated with Oracle suggests that HR is right up there with the most analytical functions in business—and even a bit ahead of a quantitatively oriented function such as finance. Many

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HR departments are using advanced analytical methods like predictive and prescriptive models, and even artificial intelligence. This is a big change from a decade ago, when I began to study the use of talent analytics. (Jeanne Harris, Jeremy Shapiro, and I published the HBR article “Competing on Talent Analytics” in 2010.) At that time, the only really sophisticated HR

analytics capability we uncovered was at Google and perhaps Harrah’s (now Caesars). There was a fair amount of reporting going on, but not much prediction. Few HR organizations even had a dedicated analytics person. “HR analytics” typically meant a debate about how many employees the organization had or the best way to measure employee engagement. Even before the new survey results came out, I suspected that things were different today. Most large companies have at least a small talent, people, workforce, or HR analytics group. Many conferences are devoted to the topic. It’s common for organizations today to model workforce growth, attrition, engagement, and other key variables. The survey involved 1,510 respondents from 23 countries across five continents. It included senior managers, directors, and vice presidents

from HR (61%), finance (28%), and general management (10%). I helped design, analyze, and report on the survey. All the executives were from companies with $100 million in revenue or more. While HR is obviously moving in an analytical direction, I did not expect the high level of sophisticated analytical activity in the survey. Here are some highlights: • Fifty-one percent of HR respondents said that they could perform predictive or prescriptive analytics, whereas only 37% of finance respondents could undertake these more advanced forms of analytics. • Eighty-nine percent agreed or agreed strongly that “my HR function is highly skilled at using data to determine future workforce plans currently (for example, talent needed),” and only 1% disagreed. • Ninety-four percent agreed that “we are able to predict the likelihood of turnover in critical roles with a high degree of confidence currently.” • Ninety-four percent also agreed that “we have accurate, real-time insight into our employees’ career development goals currently.” • When asked “Which of the following analytics are you using?” artificial intelligence received the highest response, with 31%. When asked for further detail on how respondents

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HR is more comfortable with advanced analytics than finance.

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were using AI, the most common responses were “identifying at-risk talent through attrition modeling,” “predicting high-performing recruits,” and “sourcing best-fit candidates with résumé analysis.” This level of self-assessed capability for HR analytics was high in almost every geography and every specific question, but it was somewhat lower in Asian, European, and Australian organizations. It was generally highest in the U.S., the Middle East, and Latin America. Across industries, it was lowest in hospitality, travel, and leisure as well as media and entertainment. Particularly high industries included financial services, energy and utilities, professional services, and wholesale distribution. Why is HR more comfortable with advanced analytics than finance, which has always been a function based on numbers? I have noted for years that financial organizations and the CFOs who lead them have found it difficult to move past descriptive analytics and reporting—which they do very well—to moreadvanced analytics. There are certainly exceptions to this rule, but it helps explain why the growth of advanced analytics has been faster in HR. But no business function stands alone with regard to data and analytics. One reason that Oracle surveyed both HR and finance executives is that those two functions have an increasing need to collaborate. Workforce expenditures are often among an organization’s highest costs, and a company’s financial situation will dictate fluctuations in the size and makeup of the workforce. The survey found high levels of collaboration and

mutual respect between HR and finance, and a growing need for collaboration. For example, 82% of respondents agreed or strongly agreed, and only 5% disagreed, that “integrating HR and finance data is a top priority for us this year”; however, several interviews conducted after the survey revealed that there is still much opportunity for greater sharing of data and collaboration on analytics. Of course, not everything is rosy in the world of HR analytics. I was quite interested to see that the function’s use of analytical tools surpasses the ability to interpret and act on them. When respondents were asked about the area of analytical skills for HR that “most needed to develop or improve,” the highestranking choice was “acting on data and analytics to solve issues.” “Cultivating quantitative analysis and reasoning skills” and “advising business leaders by telling a story with data” also ranked highly. My experience is that these skills are equally lacking in other functions. Perhaps it is another sign of HR’s analytical maturity that it is facing the same human skill shortages that have long bedeviled analytics users across companies. Originally published on HBR.org April 18, 2019

HBR Reprint H04WQI Thomas H. Davenport is the President’s Distinguished Professor in Management and Information Technology at Babson College, a research fellow at the MIT Initiative on the Digital Economy, and a senior adviser at Deloitte Analytics. He is the author of 20 management books, most recently Only Humans Need Apply: Winners and Losers in the Age of Smart Machines (HarperBusiness, 2016) and The AI Advantage: How to Put the Artificial Intelligence Revolution to Work (MIT Press, 2018).

How to Develop a Data-Savvy HR Department by Nigel Guenole and Sheri L. Feinzig

TO CREATE an analytical culture in your organization, you need to nurture the right mindset among your employees. And that starts with creating a culture of analytics in your HR department. How can senior leaders help HR develop a culture in which people think analytically? First, you need to understand the different levels of comfort with analytics in HR; then you need to decide your approach to hiring and building expertise at each of the different levels.

Understanding Your Current Levels of HR Analytics Expertise Our research for the book The Power of People showed that HR professionals can be broadly categorized into one of three

groups with respect to their current analytical capability: Analytically savvy: formally trained in analytics techniques and adept at working with data and interpreting analyses Analytically willing: openminded about analytics and ready, able, and willing to learn, though lacking formal training in data analysis

Analytically resistant: skeptical and dismissive of the value of a data-based approach, preferring instead to rely on intuition You can gauge the comfort levels with analytics in HR by checking for specific skills when hiring and by monitoring engagement with learning opportunities. Once you understand the different levels of analytical comfort and expertise

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that exist within your HR team, you can determine how to hire and develop each type of HR professional.

plexity enhances the chance that the analytically willing will be able to extract meaning from analytical information.

Assign workers responsibility for analytics evangelism, and reinforce this in performance objectives.

Developing Analytical Capability

Hiring for Analytical Capability Roles that require producing analytical information demand analytically savvy workers, whereas roles that involve interpreting and working with analytical information require analytically willing workers. You can assess whether workers are analytically savvy by examining formal qualifications and administering well-designed psychometric tests that measure general mental ability, which is a good predictor of performance because high scores indicate workers can acquire job-related knowledge more quickly. You should also consider less traditional evidence of learning beyond formal education, such as massive open online courses (MOOCs) provided by companies such as Coursera or edX. For analytically willing workers, consider personality tests that measure “investment” traits like openness to experience. Investment traits describe the tendency to engage in complex thinking. Because analytical information can be complex, comfort with com-

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The key to developing capability among existing workers is to provide engaging learning opportunities to workers at all levels of expertise: Analytically savvy. Keep these workers’ skills up-to-date by providing opportunities for advanced training; encourage participation in meetups, online-user groups, and forums; and support participation in professional groups and conferences. Assign them responsibility for analytics evangelism, and reinforce this in performance objectives. Each evangelist should mentor one colleague who is less analytically capable. If you don’t have analytically savvy people on your team, hiring a few will help establish an analytical culture. Analytically willing. Provide a foundational education on HR analytics by requiring all HR staff to complete an online course about the basics of workforce analytics, such as Wharton’s Coursera HR Analytics Module, which can be completed in just four weeks with a commitment of one to two hours per week. The analytically willing should then put their learning into practice by applying the techniques to their day-to-day work. These expectations can be incorporated as explicit goals in performance management systems.

Analytically resistant. Focus on how analytics can enhance these employees’ personal effectiveness. Pair

them with analytically savvy colleagues to use data and analytics to solve a problem they are struggling with. If they decline these opportunities, ask them why they are reluctant or what they are struggling with. The ultimate goal is not necessarily to transform the analytically resistant into data experts, but to have them see the value in analytics and ideally embrace it as a path to success.

Personalize Learning, and Deliver It at Scale Analytically related learning opportunities for all HR professionals can be managed with a Netflix-style online learning system, such as IBM’s Your Learning platform. With platforms like Your Learning, you can curate content targeted at each level of comfort with analytics. HR departments can set learning goals for workers that suggest how many hours of learning they’re expected to complete in a given period. A good benchmark for this would be 60 hours per year, the average at IBM. You can designate analytical skills as “hot skills” for HR professionals, and as people acquire more of these skills, increase their compensation to reflect their enhanced capabilities. It is important to pay close attention to the feedback learners provide and modify the content on the basis of what’s most effective. For instance, learners can be encouraged to tag content, and tags should be visible to content designers and other learners. This enables social learning where new course participants learn from past participants’ experiences and allows design-

ers to improve the content as they go. By monitoring and rewarding learner progress, firms can recompose the skills of their workforce. A good way to reward progress is via digital credentialing with a system like Credly, which allows workers to share their learning success with badges on social platforms such as LinkedIn. A more data-savvy HR function is entirely achievable. By understanding the levels of analytics capability in your HR team today, hiring for critical skills to fill gaps, and providing ongoing, targeted, and engaging learning opportunities, organizations will be well positioned to realize the promise of analytics in HR. Originally published on HBR.org October 11, 2018

HBR Reprint H04L1I Nigel Guenole is the director of research for the Institute of Management at Goldsmiths, University of London; an executive consultant at IBM; and the chief science adviser to Podium Assessment Systems. He is a coauthor, with Sheri L. Feinzig and Jonathan Ferrar, of The Power of People: Learn How Successful Organizations Use Workforce Analytics to Improve Business Performance (Pearson FT Press, 2017). Sheri L. Feinzig is a director at IBM Talent Management Consulting and Smarter Workforce Institute and has more than 20 years’ experience in HR research, organizational change management, and business transformation. She is a coauthor, with Nigel Guenole and Jonathan Ferrar, of The Power of People: Learn How Successful Organizations Use Workforce Analytics to Improve Business Performance (Pearson FT Press, 2017).

HOW RECRUITING WORKS NOW

Your Approach to Hiring Is All Wrong Outsourcing and algorithms won’t get you the people you need. by Peter Cappelli

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USINESSES HAVE NEVER done

as much hiring as they do today. They’ve never spent as much money doing it. And they’ve never done a worse job of it. For most of the post–World War II era, large corporations went about hiring this way: Human resources experts prepared a detailed job analysis to determine what tasks the job required and what attributes a good candidate should have. Next they did a job evaluation to determine how the job fit into the organizational chart and how much it should pay, especially compared with other jobs. Ads were posted, and applicants applied. Then came the task of sorting through the applicants. That included skills tests, reference checks, maybe personality and IQ tests, and extensive interviews to learn more about

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them as people. William H. Whyte, in The Organization Man, described this process as going on for as long as a week before the winning candidate was offered the job. The vast majority of nonentry-level openings were filled from within. Today’s approach couldn’t be more different. Census data shows, for example, that the majority of people who took a new job last year weren’t searching for one: Somebody came and got them. Companies seek to fill their recruiting funnel with as many candidates as possible, especially “passive candidates,” who aren’t looking to move. Often employers advertise jobs that don’t exist, hoping to find people who might be useful later on or in a different context. The recruiting and hiring function has been eviscerated. Many U.S. companies—about 40%, according to research by Korn Ferry—have outsourced much if not all of the hiring process to “recruitment process outsourcers,” which in turn use subcontractors, typically in India and the Philippines. The subcontractors scour LinkedIn and social media to find potential candidates. They sometimes contact them directly to see whether they can be persuaded to apply for a position and negotiate the salary they’re willing to accept. (The recruiters get incentive pay if they negotiate the amount down.) To hire programmers, for example, these subcontractors can scan websites that programmers might visit, trace their “digital exhaust” from cookies and other user-tracking measures to identify who they are, and then examine their curricula vitae. At companies that still do their own recruitment and hiring, managers trying to fill open positions are largely left to figure out what the jobs require and what the ads should say. When applications come—always electronically—applicant-tracking software sifts through them for key words that the hiring managers want to see. Then the process moves into the Wild West, where a new industry of vendors offer an astonishing array of smartsounding tools that claim to predict who will be a good hire. They use voice recognition, body language, clues on social media, and especially machine learning algorithms—everything but tea leaves. Entire publications are devoted to what these vendors are doing. The big problem with all these new practices is that we don’t know whether they actually produce satisfactory hires. Only about a third of U.S. companies report that they monitor whether their hir-

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ing practices lead to good employees; few of them do so carefully, and only a minority even track cost per hire and time to hire. Imagine if the CEO asked how an advertising campaign had gone, and the response was “We have a good idea how long it took to roll out and what it cost, but we haven’t looked to see whether we’re selling more.” Hiring talent remains the number one concern of CEOs in the most recent Conference Board Annual Survey; it’s also the top concern of the entire executive suite. PwC’s 2017 CEO survey reports that chief executives view the unavailability of talent and skills as the biggest threat to their business. Employers also spend an enormous amount on hiring—an average of $4,129 per job in the United States, according to Society for Human Resource Management estimates, and many times that amount for managerial roles—and the United States fills a staggering 66 million jobs a year. Most of the $20 billion that companies spend on human resources vendors goes to hiring. Why do employers spend so much on something so important while knowing so little about whether it works?

Where the Problem Starts Survey after survey finds employers complaining about how difficult hiring is. There may be many explanations, such as their having become very picky about candidates, especially in the slack labor market of the Great Recession. But clearly they are hiring much more than at any other time in modern history, for two reasons. The first is that openings are now filled more often by hiring from the outside than by promoting from within. In the era of lifetime employment, from the end of World War II through the 1970s, corporations filled roughly 90% of their vacancies through promotions and lateral assignments. Today the figure is a third or less. When they hire from outside, organizations don’t have to pay to train and develop their employees. Since the restructuring waves of the early 1980s, it has been relatively easy to find experienced talent outside. Only 28% of talent acquisition leaders today report that internal candidates are an important source of people to fill vacancies—presumably because of less internal development and fewer clear career ladders. Less promotion internally means that hiring efforts are no longer concentrated on entry-level

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Idea in Brief jobs and recent graduates. (If you doubt this, go to the “careers” link on any company website and look for a job opening that doesn’t require prior experience.) Now companies must be good at hiring across most levels, because the candidates they want are already doing the job somewhere else. These people don’t need training, so they may be ready to contribute right away, but they are much harder to find. The second reason hiring is so difficult is that retention has become tough: Companies hire from their competitors and vice versa, so they have to keep replacing people who leave. Census and Bureau of Labor Statistics data shows that 95% of hiring is done to fill existing positions. Most of those vacancies are caused by voluntary turnover. LinkedIn data indicates that the most common reason employees consider a position elsewhere is career advancement—which is surely related to employers’ not promoting to fill vacancies. The root cause of most hiring, therefore, is drastically poor retention. Here are some simple ways to fix that:

Track the percentage of openings filled from within. An adage of business is that we manage what we measure, but companies don’t seem to be applying that maxim to tracking hires. Most are shocked to learn how few of their openings are filled from within—is it really the case that their people can’t handle different and bigger roles?

Require that all openings be posted internally. Internal job boards were created during the dot-com boom to reduce turnover by making it easier for people to find new jobs within their existing employer. Managers weren’t even allowed to know if a subordinate was looking to move within the company, for fear that they would try to block that person and he or she would leave. But during the Great Recession employees weren’t quitting, and many companies slid back to the old model whereby managers could prevent their subordinates from moving internally. JR Keller, of Cornell University, has found that when managers could fill a vacancy with someone they already had in mind, they ended up with employees who performed more poorly than those hired when the job had been posted and anyone could apply. The commonsense explanation for this is that few enterprises really know what talent and capabilities they have. Recognize the costs of outside hiring. In addition to the time and effort of hiring, my col-

league Matthew Bidwell found, outside hires take three years to perform as well as internal hires in the same job, while internal hires take seven years to earn as much as outside hires are paid. Outside hiring also causes current employees to spend time and energy positioning themselves for jobs elsewhere. It disrupts the culture and burdens peers who must help new hires figure out how things work. None of this is to suggest that outside hiring is necessarily a bad idea. But unless your company is a Silicon Valley gazelle, adding new jobs at a furious pace, you should ask yourself some serious questions if most of your openings are being filled from outside. A different approach for dealing with retention (which seems creepy to some) is to try to determine who is interested in leaving and then intervene. Vendors like Jobvite comb social media and public sites for clues, such as LinkedIn profile updates. Measuring “flight risk” is one of the most common goals of companies that do their own sophisticated HR analytics. This is reminiscent of the early days of job boards, when employers would try to find out who was posting résumés and either punish them or embrace them, depending on leadership’s mood. Whether companies should be examining social media content in relation to hiring or any other employment action is a challenging ethical question. On one hand, the information is essentially public and may reveal relevant information. On the other hand, it is invasive, and candidates are rarely asked for permission to scrutinize their information. Hiring a private detective to shadow a candidate would also gather public information that might be relevant, yet most people would view it as an unacceptable invasion of privacy.

THE PROBLEM Employers continue to hire at a high rate and spend enormous sums to do it. But they don’t know whether their approaches are effective at finding and selecting good candidates.

THE ROOT CAUSES Businesses focus on external candidates and don’t track the results of their approaches. They often use outside vendors and high-tech tools that are unproven and have inherent flaws.

THE SOLUTION Return to filling most positions by promoting from within. Measure the results produced by vendors and new tools, and be on the lookout for discrimination and privacy violations.

The Hiring Process When we turn to hiring itself, we find that employers are missing the forest for the trees: Obsessed with new technologies and driving down costs, they largely ignore the ultimate goal: making the best possible hires. Here’s how the process should be revamped: Don’t post “phantom jobs.” It costs nothing to post job openings on a company website, which are then scooped up by Indeed and other online companies and pushed out to potential job seekers around the world. Thus it may be unsurprising that

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some of these jobs don’t really exist. Employers may simply be fishing for candidates. (“Let’s see if someone really great is out there, and if so, we’ll create a position for him or her.”) Often job ads stay up even after positions have been filled, to keep collecting candidates for future vacancies or just because it takes more effort to pull the ad down than to leave it up. Sometimes ads are posted by unscrupulous recruiters looking for résumés to pitch to clients elsewhere. Because these phantom jobs make the labor market look tighter than it really is, they are a problem for economic policy makers as well as for frustrated job seekers. Companies should take ads down when jobs are filled.

Design jobs with realistic requirements. Figuring out what the requirements of a job should be—and the corresponding attributes candidates must have—is a bigger challenge now, because so many companies have reduced the number of internal recruiters whose function, in part, is to push back on hiring managers’ wish lists. (“That job doesn’t require 10 years of experience,” or “No one with all those qualifications will be willing to accept the salary you’re proposing to pay.”) My earlier research found that companies piled on job requirements, baked them into the applicanttracking software that sorted résumés according to binary decisions (yes, it has the key word; no, it doesn’t), and then found that virtually no applicants met all the criteria. Trimming recruiters, who have expertise in hiring, and handing the process over to hiring managers is a prime example of being penny-wise and pound-foolish.

Reconsider your focus on passive candidates. The recruiting process begins with a search for experienced people who aren’t looking to move. This is based on the notion that something may be wrong with anyone who wants to leave his or her current job. (Of the more than 20,000 talent professionals who responded to a LinkedIn survey in 2015, 86% said their recruiting organizations focused “very much so” or “to some extent” on passive candidates; I suspect that if anything, that

number has since grown.) Recruiters know that the vast majority of people are open to moving at the right price: Surveys of employees find that only about 15% are not open to moving. As the economist Harold Demsetz said when asked by a competing university if he was happy working where he was: “Make me unhappy.” Fascinating evidence from the LinkedIn survey cited above shows that although self-identified “passive” job seekers are different from “active” job seekers, it’s not in the way we might think. The number one factor that would encourage the former to move is more money. For active candidates the top factor is better work and career opportunities. More active than passive job seekers report that they are passionate about their work, engaged in improving their skills, and reasonably satisfied with their current jobs. They seem interested in moving because they are ambitious, not because they want higher pay. Employers spend a vastly disproportionate amount of their budgets on recruiters who chase passive candidates, but on average they fill only 11% of their positions with individually targeted people, according to research by Gerry Crispin and Chris Hoyt, of CareerXroads. I know of no evidence that passive candidates become better employees, let alone that the process is costeffective. If you focus on passive candidates, think carefully about what that actually gets you. Better yet, check your data to find out. Understand the limits of referrals. The most popular channel for finding new hires is through employee referrals; up to 48% come from them, according to LinkedIn research. It seems like a cheap way to go, but does it produce better hires? Many employers think so. It’s hard to know whether that’s true, however, given that they don’t check. And research by Emilio Castilla and colleagues suggests otherwise: They find that when referrals work out better than other hires, it’s because their referrers look after them and essentially onboard them. If a referrer leaves before the

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new hire begins, the latter’s performance is no better than that of nonreferrals, which is why it makes sense to pay referral bonuses six months or so after the person is hired—if he or she is still there. A downside to referrals, of course, is that they can lead to a homogeneous workforce, because the people we know tend to be like us. This matters greatly for organizations interested in diversity, since recruiting is the only avenue allowed under U.S. law to increase diversity in a workforce. The Supreme Court has ruled that demographic criteria cannot be used even to break ties among candidates. Measure the results. Few employers know which channel produces the best candidates at the lowest cost because they don’t track the outcomes. Tata is an exception: It has long done what I advocate. For college recruiting, for example, it calculates which schools send it employees who perform the best, stay the longest, and are paid the lowest starting wage. Other employers should follow suit and monitor recruiting channels and employees’ performance to identify which sources produce the best results. Persuade fewer people to apply. The hiring industry pays a great deal of attention to “the funnel,” whereby readers of a company’s job postings become applicants, are interviewed, and ultimately are offered jobs. Contrary to the popular belief that the U.S. job market is extremely tight right now, most jobs still get lots of applicants. Recruiting and hiring consultants and vendors estimate that about 2% of applicants receive offers. Unfortunately, the main effort to improve hiring—virtually always aimed at making it faster and cheaper—has been to shovel more applicants into the funnel. Employers do that primarily through marketing, trying to get out the word that they are great places to work. Whether doing this is a misguided way of trying to attract better hires or just meant to make the organization feel more desirable isn’t clear. Much better to go in the other direction: Create a smaller but better-qualified applicant pool to improve the yield. Here’s why: Every applicant costs you money—especially now, in a labor market where applicants have started to “ghost” employers, abandoning their applications midway through the process. Every application also exposes a company to legal risk, because the company has obligations to candidates (not to discriminate, for example) just as it does to employees. And collect-

ing lots of applicants in a wide funnel means that a great many of them won’t fit the job or the company, so employers have to rely on the next step of the hiring process—selection—to weed them out. As we will see, employers aren’t good at that. Once people are candidates, they may not be completely honest about their skills or interests— because they want to be hired—and employers’ ability to find out the truth is limited. More than a generation ago the psychologist John Wanous proposed giving applicants a realistic preview of what the job is like. That still makes sense as a way to head off those who would end up being unhappy in the job. It’s not surprising that Google has found a way to do this with gamification: Job seekers see what the work would be like by playing a game version of it. Marriott has done the same, even for low-level employees. Its My Marriott Hotel game targets young people in developing countries who may have had little experience in hotels to show them what it’s like and to steer them to the recruiting site if they score well on the game. The key for any company, though, is that the preview should make clear what is difficult and challenging about the work as well as why it’s fun so that candidates who don’t fit won’t apply. It should be easy for candidates to learn about a company and a job, but making it really easy to apply, just to fill up that funnel, doesn’t make much sense. During the dot-com boom Texas Instruments cleverly introduced a preemployment test that allowed applicants to see their scores before they applied. If their scores weren’t high enough for the company to take their applications seriously, they tended not to proceed, and the company saved the cost of having to process their applications. If the goal is to get better hires in a cost-effective manner, it’s more important to scare away candidates who don’t fit than to jam more candidates into the recruiting funnel. Test candidates’ standard skills. How to determine which candidates to hire—what predicts who will be a good employee—has been rigorously studied at least since World War I. The personnel psychologists who investigated this have learned much about predicting good hires that contemporary organizations have since forgotten, such as that neither college grades nor unstructured sequential interviews (hopping from office to office) are a good predictor, whereas past performance is.

PROTECTING AGAINST DISCRIMINATION Finding out whether your practices result in good hires is not only basic to good management but the only real defense against claims of adverse impact and discrimination. Other than white males under age 40 with no disabilities or work-related health problems, workers have special protections under federal and state laws against hiring practices that may have an adverse impact on them. As a practical matter, that means if members of a particular group are less likely to be recruited or hired, the employer must show that the hiring process is not discriminatory. The only defense against evidence of adverse impact is for the employer to show that its hiring practices are valid—that is, they predict who will be a good employee in meaningful and statistically significant ways—and that no alternative would predict as well with less adverse impact. That analysis must be conducted with data on the employer’s own applicants and hires. The fact that the vendor that sold you the test you use has evidence that it was valid in other contexts is not sufficient.

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Interviews are where biases most easily show up, because interviewers usually decide on the fly what to ask of whom and how to interpret the answer.

Since it can be difficult (if not impossible) to glean sufficient information about an outside applicant’s past performance, what other predictors are good? There is remarkably little consensus even among experts. That’s mainly because a typical job can have so many tasks and aspects, and different factors predict success at different tasks. There is general agreement, however, that testing to see whether individuals have standard skills is about the best we can do. Can the candidate speak French? Can she do simple programming tasks? And so forth. But just doing the tests is not enough. The economists Mitchell Hoffman, Lisa B. Kahn, and Danielle Li found that even when companies conduct such tests, hiring managers often ignore them—and when they do, they get worse hires. The psychologist Nathan Kuncel and colleagues discovered that even when hiring managers use objective criteria and tests, applying their own weights and judgment to those criteria leads them to pick worse candidates than if they had used a standard formula. Only 40% of employers, however, do any tests of skills or general abilities, including IQ. What are they doing instead? Seventy-four percent do drug tests, including for marijuana use; even employers in states where recreational use is now legal still seem to do so.

Be wary of vendors bearing high-tech gifts. Into the testing void has come a new group of entrepreneurs who either are data scientists or have them in tow. They bring a fresh approach to the hiring process—but often with little understanding of how hiring actually works. John Sumser, of HRExaminer, an online newsletter that focuses on HR technology, estimates that on average, companies get five to seven pitches every day—almost all of them about hiring—from vendors using data science to address HR issues. These vendors have all sorts of cool-sounding assessments, such as computer games that can be scored to predict who will be a good hire. We don’t know whether any of these actually lead to better hires, because few of them are validated against actual job performance. That aside, these assessments have spawned a counterwave of vendors who help candidates learn how to score well on them. Lloyds Bank, for example, developed a virtual-reality-based assessment of candidate potential, and JobTestPrep offers to teach potential candidates how to do well on it. Especially for IT and technical jobs, cheating on skills tests and even video interviews (where colleagues off

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camera give help) is such a concern that eTeki and other specialized vendors help employers figure out who is cheating in real time. Revamp your interviewing process. The amount of time employers spend on interviews has almost doubled since 2009, according to research from Glassdoor. How much of that increase represents delays in setting up those interviews is impossible to tell, but it provides at least a partial explanation for why it takes longer to fill jobs now. Interviews are arguably the most difficult technique to get right, because interviewers should stick to questions that predict good hires—mainly about past behavior or performance that’s relevant to the tasks of the job—and ask them consistently across candidates. Just winging it and asking whatever comes to mind is next to useless. More important, interviews are where biases most easily show up, because interviewers do

The Grass Is Always Greener... Organizations are much more interested in external talent than in their own employees to fill vacancies. TOP CHANNELS FOR QUALITY HIRES Employee referrals

48% Third-party websites or online job boards

46 Social or professional networks

40 Third-party recruiters or staffing firms

34 Internal hires

28 Based on a 2017 survey of 3,973 talent-acquisition decision makers who work in corporate HR departments and are LinkedIn members. Source: LinkedIn

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usually decide on the fly what to ask of whom and how to interpret the answer. Everyone knows some executive who is absolutely certain he knows the one question that will really predict good candidates (“If you were stranded on a desert island…”). The sociologist Lauren Rivera’s examination of interviews for elite positions, such as those in professional services firms, indicates that hobbies, particularly those associated with the rich, feature prominently as a selection criterion. Interviews are most important for assessing “fit with our culture,” which is the number one hiring criterion employers report using, according to research from the Rockefeller Foundation. It’s also one of the squishiest attributes to measure, because few organizations have an accurate and consistent view of their own culture—and even if they do, understanding what attributes represent a good fit is not straightforward. For example, does the fact that an applicant belonged to a fraternity reflect experience working with others or elitism or bad attitudes toward women? Should it be completely irrelevant? Letting someone with no experience or training make such calls is a recipe for bad hires and, of course, discriminatory behavior. Think hard about whether your interviewing protocols make any sense and resist the urge to bring even more managers into the interview process.

Recognize the strengths and weaknesses of machine learning models. Culture fit is another area into which new vendors are swarming. Typically they collect data from current employees, create a machine learning model to predict the attributes of the best ones, and then use that model to hire candidates with the same attributes. As with many other things in this new industry, that sounds good until you think about it; then it becomes replete with problems. Given the best performers of the past, the algorithm will almost certainly include white and male as key variables. If it’s restricted from using that category, it will come up with attributes associated with being a white male, such as playing rugby. Machine learning models do have the potential to find important but previously unconsidered relationships. Psychologists, who have dominated research on hiring, have been keen to study attributes relevant to their interests, such as personality, rather than asking the broader question “What identifies a potential good hire?” Their results gloss over the fact that they often

have only a trivial ability to predict who will be a good performer, particularly when many factors are involved. Machine learning, in contrast, can come up with highly predictive factors. Research by Evolv, a workforce analytics pioneer (now part of Cornerstone OnDemand), found that expected commuting distance for the candidate predicted turnover very well. But that’s not a question the psychological models thought to ask. (And even that question has problems.) The advice on selection is straightforward: Test for skills. Ask assessments vendors to show evidence that they can actually predict who the good employees will be. Do fewer, moreconsistent interviews.

The Way Forward It’s impossible to get better at hiring if you can’t tell whether the candidates you select become good employees. If you don’t know where you’re going, any road will take you there. You must have a way to measure which employees are the best ones. Why is that not getting through to companies? Surveyed employers say the main reason they don’t examine whether their practices lead to better hires is that measuring employee performance is difficult. Surely this is a prime example of making the perfect the enemy of the good. Some aspects of performance are not difficult to measure: Do employees quit? Are they absent? Virtually all employers conduct performance appraisals. If you don’t trust them, try something simpler. Ask supervisors, “Do you regret hiring this individual? Would you hire him again?” Organizations that don’t check to see how well their practices predict the quality of their hires are lacking in one of the most consequential aspects of modern business. HBR Reprint R1903B

Peter Cappelli is the George W. Taylor Professor of Management at the Wharton School and the director of its Center for Human Resources. His most recent book is Will College Pay Off? A Guide to the Most Important Financial Decision You’ll Ever Make (PublicAffairs, 2015).

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HOW RECRUITING WORKS NOW

Navigating Talent Hot Spots How companies can benefit from innovation centers without necessarily relocating by William Kerr

I

N 2016, General Electric announced that it was moving its longtime corporate headquarters from suburban Fairfield, Connecticut, to downtown Boston. The company felt it needed to plug in to Boston’s high-tech young ventures and talent to become more innovative and digital—and ensure that it would be on the forefront of any emerging disruptive technologies. Jeff Bornstein, then the CFO, summed up the advantage of Boston to the Wall Street Journal this way: “I can walk out my door and visit four start-ups. In Fairfield I couldn’t even walk out my door and get a sandwich.” Leading cities have long had an outsize influence on the global economy, but today the impact that top talent clusters like Boston and San Francisco have on innovation is especially pronounced. In

ILLUSTRATION BY JOANNA ŁAWNICZAK

2017, America’s 10 largest tech hubs accounted for 58% of U.S. patents. Globally, cities such as Tokyo, Paris, Beijing, Shenzhen, and Seoul produced a similarly large proportion. The increased clout of these hubs poses a dilemma for companies that have historically located their leadership and talent in suburban industrial parks. Having a presence in innovation hotbeds is crucial, but it’s also extraordinarily expensive—especially in the narrow innovation districts within cities where most of the high-tech activity takes place. How can companies most effectively harness the benefits of these urban pools of knowledge and skills? In my work on global talent flows, I’ve seen corporations take three core approaches: At one extreme, they relocate their headquarters, just as GE did. A less expensive and more easily reversible way

Originally published in September–October 2018

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to establish a brick-and-mortar foothold is to set up an innovation lab or corporate outpost in a talent cluster. The most conservative option is to organize executive retreats and immersive visits there. The three options are not mutually exclusive— especially since companies often need to keep in touch with several clusters—and each one involves substantial risks. But as the influence of a handful of global cities continues to grow, these approaches offer a playbook to companies that find themselves outside the action in today’s concentrated innovation geography.

OPTION 1

Headquarters Moves While we tend to associate innovation hubs with entrepreneurs and start-ups, increasingly they’re the domain of incumbents, too. Twenty years ago inventors working in the top 10 cities for patenting activity accounted for fewer than half the patents filed by America’s 50 largest companies; their innovations were developed mostly in corporate labs in smaller cities. In 2017, by contrast, inventors working in the top 10 cities accounted for almost 70% of the Fortune 50’s patent filings. Corporations have gone from being underrepresented in tech hubs to exceeding the national average. To some extent, this shift reflects the displacement of legacy companies in the Fortune 50 by innovative firms such as Alphabet and Amazon. But other incumbents besides GE are moving resources to tech hubs. In 2016 packaged foods manufacturer Conagra, for instance, relocated its headquarters from Omaha, Nebraska, to Chicago in order to attract more Millennials and recruit senior talent with experience in consumer brands. While he praised Omaha, CEO Sean Connolly told the Omaha World-Herald, “Chicago is an environment that offers us access to innovation and brand-building talent.” Though cross-state moves grab headlines, companies are also migrating out of less-dense areas surrounding talent clusters and into urban centers. In Boston, organizations relocating to the downtown area include Reebok, Converse, and much of the local venture capital industry. A local recruiting agency, WinterWyman, has reported that downtown Boston and Cambridge accounted for more than 60% of recent tech hires in the metropolitan area, compared with just 5% two decades ago. Conagra closed a suburban Chicago

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facility so that it could move more of its executive team into its downtown HQ. McDonald’s, Motorola Solutions, Kraft Heinz, and some 50 other companies have also relocated to downtown Chicago from nearby suburbs. Greg Brown, the CEO of Motorola, noted that its HQ move would accelerate cultural change in the company and make recruiting software developers and data scientists easier. The increased access to talent can be substantial, since the share of the local college-educated workforce engaged in digital fields in hub cities is typically two to three times as high as the national average. Moreover, many talented young people want to work in hip downtown locations with sleek new offices, not aging suburban complexes with lots of parking. But a headquarters relocation poses several risks. For large incumbents it can be incredibly difficult, time-consuming, and expensive. The need to uproot an existing workforce, change legacy customer locations, and establish new local political connections and responsibilities means that any relocation will be disruptive, offsetting the advantages a talent cluster might offer. What’s more, HQ moves are hard to reverse. Because talent hot spots can rise and fall—in the 1950s, Silicon Valley was barely a dot on the economic map, and Detroit was the epicenter of rapidly growing industry—corporations may end up overinvesting in a temporary competitive advantage.

As the influence of a handful of global cities grows, these three approaches offer a playbook to companies that find themselves outside the action.

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Idea in Brief One way to mitigate that risk is to build smaller headquarters that are focused on innovation and the key needs of top decision makers. GE is moving fewer than 800 people (out of a workforce of more than 300,000) to Boston; only those who are especially focused on innovation and digitization are being relocated. At some incumbents the top leaders already work mostly remotely, especially if they have heavy travel schedules. New corporate HQs are starting to look and operate more like the offices of unicorn start-ups than of industrial giants. Communication technologies and connectivity allow corporate leadership to oversee operations with ever greater scope and scale from a small command post. This points to the second broad risk with headquarters moves: that ideas generated within the talent hub may fail to spread to the rest of the organization. Cutting-edge concepts picked up in Boston or Berlin will benefit a global company only if they improve the productivity of operations around the world. Moving key executives to talent clusters may distance leaders from other employees in the firm, whereas the older corporate HQs in suburban office parks tended to minimize internal distances. As a result, careful thought will have to go into diffusing acquired knowledge throughout the organization’s facilities. Talent rotations can mitigate this risk. A study of an Indian R&D center at a leading multinational showed that short business trips to the firm’s U.S. headquarters boosted the productivity of the site’s scientists and engineers upon their return home, because they had gained technical knowledge and formed tighter personal relationships with leaders at headquarters and were better able to match people’s skills to assignments. And as more companies are learning, communication technology is not a substitute for people flows but a complement. Yes, great videoconferencing technology helps, but there’s no better way than meeting in person to kick off or renew a relationship. A third risk is negative press and the loss of political capital. No city wants a leading firm to leave, but the potential for ill will extends to new locations, too. Many companies seek tax breaks and other incentives for their new headquarters; it’s a delicate balancing act to secure preferential treatment but also be perceived as a partner in the new home city. Amazon has been criticized for the multiround bidding contest it held and the incentives it sought when scouting sites for its second

North American headquarters. As Apple began its search for the site of a fourth U.S. campus, CEO Tim Cook remarked that his company would not hold a beauty pageant like Amazon’s. “That’s not Apple,” he told Recode. Headquarters moves must also deliver on high expectations. They must weather any changes in corporate leadership and the ups and downs of company performance. Shortly after John Flannery took over as CEO of GE, in 2017, the company announced that it would delay construction on its new $200 million building in Boston. And after GE announced job cuts, some of which would affect Boston workers, last fall, a local newspaper columnist wondered, “Was Boston sold a lemon?” GE remains committed to its new HQ but is also rethinking the role of the HQ as it works to realign itself. A fourth risk that companies must guard against is a “leaky bucket.” Although they can recruit more easily in hubs, they can see ideas and talent flow out, too. In top clusters being an attractive local employer often means stacking up well against an Apple or a Spotify with competitive salaries and benefits. Finally, there’s a risk of unintended and unforeseen consequences. Research shows that companies are more likely to close plants that are distant from HQs than plants close by, for instance. Headquarters moves permanently shift the internal workings of a firm in material ways. The company will also adopt more of the culture of the new home base—which was often the point of the move, after all—and executives will have a new peer group going forward. But for executives and directors looking to deeply transform their organizations, all those risks may be warranted.

THE SHIFT Leading cities have long had an outsize influence on the global economy, but today the impact that top talent clusters such as Boston and San Francisco have on innovation is especially pronounced.

THE CHALLENGE Urban innovation hubs are extraordinarily expensive. How can companies harness the benefits of their dense pools of knowledge and skills in the most effective manner?

THE SOLUTION Companies have three options: Relocate their headquarters to hubs; set up innovation labs or corporate outposts there; or run executive retreats and immersions there.

OPTION 2

Creating Outposts and Innovation Labs At many companies, moving the headquarters is not up for discussion. In September 2017, the same month that Amazon began its search for a second North American headquarters, Walmart announced the construction of a new head office in its longtime home of Bentonville, Arkansas. But even if Walmart remains forever rooted in Arkansas, it has no intention of ceding the battle for the insights of talent clusters to the likes of Amazon (Seattle) and Alibaba (Hangzhou). Walmart Labs,

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Companies benefit most from innovation when they acquire the best ideas, not when their average ideas are better.

opened in 2011 in Silicon Valley, focuses on making advances, ranging from voice-enabled shopping to crowdsourced delivery, on the frontiers of e-commerce. Many companies a small fraction of Walmart’s size have opened similar corporate outposts in order to access important talent clusters in their industries. Such offices can serve a range of functions. Some simply house a small team that listens to what’s going on locally and scouts out business development opportunities. Some establish an innovation lab like Walmart’s that works on new technology development. At others, companies focus on corporate venturing—partly to make a financial return on investments, but more to have a better vantage point on new advances. Companies benefit most from innovation when they acquire the best ideas, not when their average ideas are better. A physical presence in leading clusters helps companies connect with the most powerful concepts emerging in their sector. Corporate outposts are relatively inexpensive to launch, at least compared with HQ moves, and some companies effectively buy one by acquiring a young tech start-up. An important step in the launch of Walmart Labs, for instance, was the retail giant’s purchase of Kosmix in 2011. Companies often want a presence in two or more clusters. One never knows where the next top idea will emerge, and firms can compete for talent better when they touch multiple clusters at once. Microsoft Research, for example, has built a network of labs outside Redmond, Washington, in locations that include Cambridge, Massachusetts; Cambridge, England; New York; Montreal; Beijing; and Bangalore. The Chinese white-goods giant Haier has five R&D centers—within and outside top clusters in the United States, Europe, Japan,

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Australia, and China—which are helping it stake out a role in the internet of things. One of the major risks with outposts is being “penny-wise and pound-foolish” when selecting real estate. Location matters even within cities. The costs of locating close to Sand Hill Road or Market Street are substantially higher than elsewhere in the San Francisco area—but so are the benefits. A study of advertising agencies in Manhattan is illustrative. Manhattan’s agencies create about a quarter of all advertising in the United States. They rely on personal networking to share project work, splitting larger jobs into parts that can be independently attacked by each firm. However, the study found that sharing declines rapidly with geographical distance, disappearing entirely when two firms are more than half a mile apart. To successfully tap into the market, an ad agency requires not only a New York address but an address within a few city blocks of Madison Avenue. The good news is that real estate vendors that make it less costly for companies to launch outposts are emerging. The coworking company CIC, for example, located in the heart of Kendall Square in Cambridge, Massachusetts, offers high-end, flexible office space on a month-to-month basis. CIC has created packages suitable for the innovation outposts of large companies, and its clients have included Amazon, Bayer, PwC, and Royal Dutch Shell. CIC even houses a “Captains of Innovation” program that links corporations to local innovators. An advantage of outposts is that companies can experiment and start with a small team—keeping the option open for investment down the road. Five years before announcing its move to Boston, GE launched an outpost in Silicon Valley to accelerate its digital innovation efforts. The one-person

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office initially housed just Bill Ruh, an executive recruited from Cisco to lead a new lab. Over the next three years, he grew the office to 150 people, hiring Silicon Valley talent almost exclusively. The launch strategy kept initial needs small and allowed Ruh to shape the effort to Silicon Valley’s practices rather than being restricted by GE’s typical playbook. His group would grow to 1,800 employees and ultimately become its own business unit, now branded GE Digital. If outposts aren’t working out, they can be closed, but this reversibility carries its own risk. Companies often pull the plug too quickly, believing an operation is failing because they have unrealistic expectations about how quickly they’ll see results. Leaders must understand that it takes time to build relationships; three to six months is rarely sufficient. What makes talent clusters special is an enormous volume and diversity of activity. The investment in start-ups housed within CIC’s coworking space alone exceeds the venture investment made in most U.S. states, for instance. There is much to learn before a new outpost can be effective, and discovery processes take time. This is especially true when organizations invest in a cluster far from home. Another risk is that small teams away from the corporate center will be viewed as impotent, rendering outpost executives less interesting to local entrepreneurs and innovators. Empowering the local staff to make modest deals on behalf of the company goes a long way toward boosting the stature of an outpost’s leaders at the watercooler. Perhaps most critical is the choice of initial outpost directors. These executives lend their personal credibility both internally to the corporation and externally to the cluster. One approach is to seek a “best of both worlds” launch team by combining a relocating executive from the parent’s HQ with a star already working in the cluster. When a foreign company enters the United States, this local talent is often an ex-pat of the same nationality as the parent organization. A final risk with innovation outposts is that the best ideas and innovations will not flow back to the parent company effectively. Studies of patent data show that poor internal transfer is especially pronounced in cross-border settings. This may explain why many firms are disappointed with the returns from overseas innovation work—if the right conditions aren’t set, the output tends to be isolated.

One effective countermeasure is to promote international knowledge transfer by distributing collaborative teams across locations. That way, a company’s innovations are more likely to build on the patents filed in several locations. This approach is used extensively when companies first open new international facilities, either as a deliberate hedge to protect intellectual property or simply as a needed prop for the fledgling operations. Cross-border collaborative teams now account for 13% of the patents of large U.S. companies, up from just 1% in 1975. Though these global teams need to be carefully managed (see Tsedal Neeley’s HBR article “Global Teams That Work,” October 2015), they’re likely to grow in importance as companies seek more access to talent clusters.

Follow the Money Where are the global talent hot spots? Data on venture capital investment and unicorn start-ups (those with billion-dollar evaluations) point to these locations:

Metro areas with the greatest VC investment (since 2009)

Metro areas with the most unicorns (since 2009)

1. SAN FRANCISCO 2. BEIJING 3. SHANGHAI 4. NEW YORK 5. BOSTON 6. LOS ANGELES 7. LONDON 8. SHENZHEN 9. SAN DIEGO 10. SEATTLE

1. SAN FRANCISCO 2. BEIJING 3. NEW YORK 4. LOS ANGELES 5. SHANGHAI 6. BOSTON 7. LONDON 8. SEATTLE 9. HANGZHOU 10. CHICAGO

Source: Calculations from Thomson One data on venture capital funding

Source: Calculations from CB Insights data

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HBR Special Issue 63

HOW RECRUITING WORKS NOW NAVIGATING TALENT HOT SPOTS

Starwood Hotels has moved its entire corporate headquarters from America to China, India, and the United Arab Emirates for monthlong immersions.

OPTION 3

Executive Retreats and Immersions Executive visits to top talent clusters can be a cost-effective way to increase awareness and excitement about efforts to accelerate innovation and reshape business models and management approaches. Though a weeklong trip rarely provides the missing piece to a company’s innovation puzzle, it can help executives build a grounded understanding of what’s happening at the frontier and how their companies may need to react. In 2014 executives at the large European bank ING Netherlands felt that their organization, while profitable and seemingly stable, was not realizing its full potential in a financial services sector that was rapidly being revolutionized. So they embarked on visits to Spotify, Google, Netflix, Zappos, and other innovative companies to explore new possibilities. Those trips led the executives to reimagine ING Netherlands as a smaller, nimbler organization with a stronger customer focus. To fulfill that new vision, the company would adopt agile team methodology throughout the organization, reduce head count at its Dutch headquarters by 25%, and redesign its facilities to have open floor plans without offices (even for the CEO) in order to foster new team interactions. Every person at headquarters had to reapply for a job, and all positions would be quite different under the new system. The transformation went live in 2015. CEO Vincent van den Boogert has been very pleased with the gains ING Netherlands has made since then in product innovation, customer satisfaction, and digital talent acquisition.

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The global telecom giant Vodafone has also made executive immersions part of its innovation strategy. The company is based in London, a premier talent cluster, but outgoing CEO Vittorio Colao strongly feels that Vodafone must tap into other clusters to stay on the cutting edge in communication technologies and other advanced technologies that affect firm operations. Every year the top 50 Vodafone executives take a weeklong trip to Silicon Valley together to broaden their perspectives. Many other companies organize similar visits to New York, London, Boston, Shanghai, and other clusters for their executives or board members. (I myself have organized corporate immersions in Boston, and this article draws on those experiences. None of the companies mentioned in this article have been my clients, however.) But many firms underinvest in immersions, for two reasons: Executives view the trip as a semi-vacation or, at the other extreme, can’t extract themselves from e-mails about daily operations to the team back home. The CEO must emphasize immersions’ high price—especially the opportunity costs related to executive time—to all participants. Mandates from the CEO regarding prework for the trip will set the tone, and nothing keeps executives off their smartphones the way the CEO’s mindful eye and visible passion do. An all-in mentality for leaders makes the immersion a success, and trips should be planned at times when that kind of dedication is realistic for the executive team. A second risk is that participants in immersions won’t dig deep enough. Visits to local companies

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can be informative and inspiring, but not if they don’t get past preset professional tours. ING’s visit to Spotify became much more effective, for instance, when people at the Swedish music company began to relate the costs and challenges of adopting agile methodology, not just the benefits. One (rare) route to deep immersion is to park the leadership team abroad for an extended time. To obtain insights on innovative technology and services in emerging regions, Starwood Hotels has moved its entire corporate headquarters from America to China, India, and the United Arab Emirates for monthlong immersions. With shorter trips, visiting companies need to organize tailored sessions with local experts (such as business leaders and university faculty members) to achieve greater learning. Companies also must ensure that the insights gathered are acted on back home. A one-off immersion may deliver short-term change while it’s top of mind for executives, but its lessons may soon get crowded out by other priorities. Tying immersions to a regular strategy or leadership-building process is a good way to capture their benefits. Immersions that have clear links to important corporate work before and after the retreat will have the strongest power, and executives should spend time on the trip itself debating and applying insights. Vodafone offers a good example of how to leverage an immersion’s insights back home. The company invites its top 250 employees to London for three-day training sessions on the advanced technologies its top 50 leaders have studied. This program—which includes exercises like building a rudimentary chatbot for ordering coffee—pushes familiarity with the technologies into the organization’s second tier of leadership. To spread the insights throughout its vast organization, the company incorporates the emerging technology trends it has identified into personalized learning programs on its digital Vodafone University platform. (Vodafone also pairs leaders with young “digital ninjas” to provide ongoing upward mentoring on emerging technology trends and applications.) A final risk is that executives will bring the wrong insights home with them. Clusters excel when the local community buys into the same priorities and perspectives, such as the deep respect given in Silicon Valley to people who launch gamechanging companies. But any tightly knit place can also suffer from groupthink. Silicon Valley’s “move fast and break things” ethos has arguably left

many tech giants blind to a backlash on issues like privacy, data security, and surveillance. Executives participating in immersions may be dazzled by the wrong things, when they should be listening carefully and asking questions.

A STRIKING FEATURE of today’s business landscape is the growing concentration of innovation activity—and the exceptional talent associated with it—into a small number of geographic clusters. As new technologies continue to disrupt industries, the fate of corporations will increasingly be determined in these hot spots. By taking one or more of the approaches I’ve outlined here, companies can access the intelligence in these key locations and keep up with the fast pace of change. HBR Reprint R1805E

William Kerr is the Dimitri V. D’Arbeloff–MBA Class of 1955 Professor of Business Administration at Harvard Business School and the author of The Gift of Global Talent: How Migration Shapes Business, Economy & Society (Stanford University Press, 2018).

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HBR Special Issue 65

HOW RECRUITING WORKS NOW

Quick Takes

by Peter Cappelli

RECRUITING MANAGERS desperately need new tools, because the existing ones—unstructured interviews, personality tests, personal referrals—aren’t very effective. The newest development in hiring, which is both promising and worrying, is the rise of data science–driven algorithms to find and assess job candidates. By my count, more than 100 vendors are creating and selling these tools to companies. Unfortunately, data science—which is still in its infancy when it comes to recruiting and hiring—is not yet the panacea employers hope for.

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Vendors of these new tools promise they will help reduce the role that social bias plays in hiring. And the algorithms can indeed help identify good job candidates who would previously have been screened out for lack of a certain education or social pedigree. But these tools may also identify and promote the use of predictive variables that are (or should be) troubling. Because most data scientists seem to know so little about the context of employment, their tools are often worse than nothing. For instance, an astonishing percentage build their models

All analytic approaches to picking candidates are backward looking— they are based on outcomes that have already happened.

observations—many years’ worth of job performance data even for a large employer.) As Amazon learned, the past may be very different from the future you seek. It discovered that the hiring algorithm it had been working on since 2014 gave lower scores to women—even to attributes associated with women, such as participating in women’s studies programs— because historically the best performers in the company had disproportionately been men. So the algorithm looked for people just like them. Unable to fix that problem, the company stopped using the algorithm in 2017. Nonetheless, many other companies are pressing ahead. The underlying challenge for data scientists is that hiring is simply not like trying to predict, say, when a ball bearing will fail—a question for which any predictive measure might do. Hiring is so consequential that it is governed not just by legal frameworks but by fundamental notions of fairness. The fact that some criteria are associated with good job performance is necessary but not sufficient for using it in hiring. Take a variable that data scientists have found to have predictive value: commuting distance to the job. According to the data, people with longer commutes suffer higher rates of attrition. However, commuting

MICHAEL ROBERTO/GETTY IMAGES

Data Science Can’t Fix Hiring (Yet)

by simply looking at attributes of the “best performers” in workplaces and then identifying which job candidates have the same attributes. They use anything that’s easy to measure: facial expressions, word choice, comments on social media, and so forth. But a failure to check for any real difference between high-performing and low-performing employees on these attributes limits their usefulness. Furthermore, scooping up data from social media or the websites people have visited also raises important questions about privacy. True, the information can be accessed legally, but the individuals who created the postings didn’t intend or authorize them to be used for such purposes. Furthermore, is it fair that something you posted as an undergrad can end up driving your hiring algorithm a generation later? Another problem with machine learning approaches is that few employers collect the large volumes of data—number of hires, performance appraisals, and so on—that the algorithms require to make accurate predictions. Although vendors can theoretically overcome that hurdle by aggregating data from many employers, they don’t really know whether individual company contexts are so distinct that predictions based on data from the many are inaccurate for the one. Yet another issue is that all analytic approaches to picking candidates are backward looking—they are based on outcomes that have already happened. (Algorithms are especially reliant on past experiences in part because building them requires lots and lots of

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distance is governed by where you live—which is governed by housing prices and relates to income and race. Picking whom to hire on the basis of where they live most likely has an adverse impact on protected groups such as racial minorities. Unless no other criterion predicts at least as well as the one being used—and that is extremely difficult to determine in machine learning algorithms— companies violate the law if they use hiring criteria that have adverse impacts. Even then, to stay on the right side of the law, they must show why the criterion creates good performance. That might be possible in the case of commuting time, but—at least for the moment—it is not for facial expressions, social media postings, or other measures whose significance companies cannot demonstrate. In the end, the drawback to using algorithms is that we’re trying to use them on the cheap: building them by looking only at best performers rather than all performers, using only measures that are easy to gather, and relying on vendors’ claims that the algorithms work elsewhere rather than observing the results with our own employees. Not only is there no free lunch here, but you might be better off skipping the cheap meal altogether.

PETER DAZELEY/GETTY IMAGES

Originally published in Harvard Business Review May–June 2019

HBR Reprint R1903B Peter Cappelli is the George W. Taylor Professor of Management at the Wharton School and the director of its Center for Human Resources. His most recent book is Will College Pay Off? A Guide to the Most Important Financial Decision You’ll Ever Make (PublicAffairs, 2015).

The Legal and Ethical Implications of Using AI in Hiring by Ben Dattner, Tomas Chamorro-Premuzic, Richard Buchband, and Lucinda Schettler

DIGITAL INNOVATIONS and advances in AI have produced a range of novel talent identification and assessment tools. Many of these technologies promise to help organizations improve their ability to find the right person for the right job, and screen out the wrong people for the wrong jobs, faster and cheaper than ever before. These tools put unprecedented power in the hands of organizations to pursue databased human capital decisions. They also have the potential to democratize feedback, giv-

ing millions of job candidates data-driven insights on their strengths, development needs, and potential career and organizational fit. In particular, we have seen the rapid growth (and corresponding venture capital investment) in game-based assessments, bots for scraping social media postings, linguistic analysis of candidates’ writing samples, and video-based interviews that utilize algorithms to analyze speech content, tone of voice, emotional states, nonverbal behaviors, and temperamental clues.

Although these novel tools are disrupting the recruitment and assessment space, they leave many yet-unanswered questions about their accuracy and the ethical, legal, and privacy implications they introduce. This is especially true when compared with more long-standing psychometric assessments—such as the NEO PI-R, the Wonderlic test, the Raven’s Progressive Matrices test, or the Hogan Personality Inventory—that have been scientifically derived and carefully validated vis-à-vis relevant jobs, identifying reliable associations between applicants’ scores and their subsequent job performance (publishing the evidence in independent, trustworthy, scholarly journals). Recently, there has even been interest and concern in the U.S. Senate about whether new technologies (specifically, facial analysis technologies) might have negative implications for equal opportunity among job candidates. In this article, we focus on the potential repercussions of new technologies on the privacy of job candidates, as well as the implications for candidates’ protections under the Americans with Disabilities Act (ADA) and other federal and state employment laws. Employers recognize that they can’t or shouldn’t ask candidates about their family status or political orientation, or whether they are pregnant, straight, gay, sad, lonely, depressed, or physically or mentally ill; drinking too much; abusing drugs; or sleeping too little. However, new technologies may already be able to discern many of these factors

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HBR Special Issue 67

HOW RECRUITING WORKS NOW QUICK TAKES

indirectly and without proper (or even any) consent. Before delving into the current ambiguities of the brave new world of job candidate assessment and evaluation, it’s helpful to look at the past. Psychometric assessments have been in use for more than 100 years and became more widely used as a result of the U.S. military’s Army Alpha, which placed recruits into categories and determined their likelihood of being successful in various roles. Traditionally, psychometrics fell into three broad categories: cognitive ability or intelligence, personality or temperament, and mental health or clinical diagnosis. Since the adoption of the ADA in 1990, employers are generally forbidden from inquiring about or using physical disability, mental health, or clinical diagnosis as a factor in preemployment candidate assessments, and companies that have done so have been sued and censured. In essence, disabilities—whether physical or mental—have been determined to be private information that employers cannot inquire about at the preemployment stage, just as employers shouldn’t ask applicants intrusive questions about their personal lives and can’t take private demographic information into account in hiring decisions. Cognitive ability and intelligence testing are reliable and valid predictors of job success in many occupations; however, these kinds of assessments can be discriminatory if they adversely impact certain protected groups, such as those defined by gender, race, age, or national origin. If an employer

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is using an assessment that has been found to have such an adverse impact, which is defined by the relative scores of different protected groups, the employer has to prove that the assessment methodology is job-related and predictive of success in the specific jobs in question.

Many talent tools have emerged as technological innovations, rather than from scientifically derived methods or research programs.

Personality assessments are less likely to expose employers to possible liability for discrimination, because there is little to no correlation between personality characteristics and protected demographic variables or disabilities. It should also be noted that the relationship between personality and job performance depends on the context (for example, type of role or job). Unfortunately, there is far less information about the new generation of talent tools that are increasingly used in prehire assessment. Many of these tools have emerged as technological innovations, rather than from scientifically derived methods or research programs. As a result, it is not always clear what they assess, whether their underlying hypotheses are valid, or how they predict job candidates’ performance. For example, physical properties of speech and the human voice—which have long been associated with elements of personality—have been linked

to individual differences in job performance. If a tool shows a preference for speech patterns (such as consistent vocal cadence or pitch or a “friendly” tone of voice) that do not have an adverse impact on job candidates in a legally protected group, then there is no legal issue, but these tools may not have been scientifically validated and therefore are not controlling for potential discriminatory adverse impact—meaning the employer may incur liability for any blind reliance. In addition, there are yet no convincing hypotheses or defensible conclusions about whether it would be ethical to screen out people on the basis of their voices, which are physiologically determined, largely unchangeable personal attributes. Likewise, social media activity—such as Facebook or Twitter usage—has been found to reflect people’s intelligence and personality, including their dark-side traits. But is it ethical to mine this data for hiring purposes when users generally use such apps for different purposes and may not have provided their consent for data analysis to draw private conclusions from their public postings? When used in the hiring context, new technologies raise a number of new ethical and legal questions around privacy, which we think should be publicly discussed and debated, namely:

1. What temptations will companies face in terms of candidate privacy relating to personal attributes? As technology advances, big data and AI will continue to be

able to determine “proxy” variables for private, personal attributes with increased accuracy. Today, for example, Facebook “likes” can be used to infer sexual orientation and race with considerable accuracy. Political affiliation and religious beliefs are just as easily identifiable. Might companies be tempted to use tools like these to screen candidates, believing that because decisions aren’t made directly on the basis of protected characteristics, they aren’t legally actionable? While an employer may not violate any laws in merely discerning an applicant’s personal information, the company may become vulnerable to legal exposure if it makes adverse employment decisions by relying on any protected categories such as one’s place of birth, race, or native language—or on the basis of private information it doesn’t have the right to consider, such as possible physical illness or mental ailment. How the courts will handle situations where employers have relied on tools using these proxy variables is unclear, but the fact remains that it is unlawful to take an adverse action on the basis of certain protected or private characteristics—no matter how these were learned or inferred. This might also apply to facial recognition software, as recent research predicts that face-reading AI may soon be able to discern candidates’ sexual and political orientation, as well as internal states like mood or emotion, with a high degree of accuracy. How might the application of the ADA change? In addition, the Employee Polygraph Protection Act generally prohibits employ-

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ers from using lie detector tests as a preemployment screening tool, and the Genetic Information Nondiscrimination Act prohibits employers from using genetic information in employment decisions. But what if the exact same kind of information about truth, lies, or genetic attributes could be determined by the above-mentioned technological tools?

2. What temptations will companies face in terms of candidate privacy relating to lifestyle and activities? Employers can now access information such as one candidate’s online “check-in” to her church every Sunday morning, another candidate’s review of the dementia care facility into which he has placed his elderly parent, and a third’s divorce filing in civil court. All these things, and many more, are easily discoverable in the digital era. Big data is following us everywhere we go online and collecting and assembling information that can be sliced and diced by tools we can’t even imagine yet—tools that could possibly inform future employers about our fitness (or lack thereof) for certain roles. And big data is only going to get bigger; according to experts, 90% of the data in the world was generated just in the past two years alone. With the expansion of data comes the potential expansion for misuse and resulting discrimination—either deliberate or unintentional. Unlike the EU, which has harmonized its approach to privacy under the General Data Protection Regulation, the U.S. relies on a patchwork approach to privacy driven largely by state

law. With regard to social media specifically, states began introducing legislation back in 2012 to prevent employers from requesting passwords to personal internet accounts as a condition of employment. More than 20 states have enacted these types of laws that apply to employers; however, in terms of general privacy in the use of new technologies in the workplace, there has been less specific guidance or action. In particular, legislation has passed in California that will potentially constrain employers’ use of candidate or employee data. In general, state and federal courts have yet to adopt a unified framework for analyzing employee privacy as related to new technology. The takeaway is that at least for now, employee privacy in the age of big data remains unsettled. This puts employers in a conflicted position that calls out for caution: Cutting-edge technology is available that may be extremely useful, but it’s providing information that has previously been considered private. Is it legal to use in a hiring context? And is it ethical to consider if the candidate didn’t consent?

3. What temptations will companies face in terms of candidate privacy relating to disabilities? The ADA puts mental disabilities squarely in its purview, alongside physical disabilities, and defines an individual as disabled if the impairment substantially limits a major life activity, the person has a record of such an impairment, or the person is perceived to have such an impairment. About a decade ago, the U.S. Equal Employment

Opportunity Commission issued guidance to say that the expanding list of personality disorders described in the psychiatric literature could qualify as mental impairments, and the ADA Amendments Act made it easier for an individual to establish that he or she has a disability within the meaning of the ADA. As a result, the category of people protected under the ADA may now include those who have significant problems communicating in social situations, issues concentrating, or difficulty interacting with others. In addition to raising new questions about disabilities, technology also presents new dilemmas with respect to differences, whether demographic or otherwise. There have already been high-profile real-life situations where these systems have revealed learned biases, especially relating to race and gender. Amazon, for example, developed an automated talent search program to review résumés—which was abandoned after the company realized that the program wasn’t rating candidates in a genderneutral way. To reduce such biases, developers are balancing the data used for training AI models to appropriately represent all groups. The more information the technology has and can account for and learn from, the better it can control for potential bias. In conclusion, new technologies can already cross the lines between public and private attributes, traits, and states of mind in new ways, and there is every reason to believe that in the future they will be increasingly able to do so. Using AI, big data, social media, and machine

learning, employers will have greater access to candidates’ private lives, private attributes, and private challenges and states of mind. There are no easy answers to many of the new questions about privacy we have raised here, but we believe that they are all worthy of public discussion and debate. Originally published on HBR.org April 25, 2019

HBR Reprint H04X5S Ben Dattner is an executive coach and organizational development consultant, and the founder of New York City–based Dattner Consulting. Follow him on Twitter: @bendattner. Tomas Chamorro-Premuzic is the chief talent scientist at ManpowerGroup, a professor of business psychology at University College London and Columbia University, and a cofounder of Deeper Signals and MetaProfiling. He’s also the author of Why Do So Many Incompetent Men Become Leaders? (And How to Fix It) (Harvard Business Review Press, 2019). Follow him on Twitter: @drtcp. Richard Buchband is the senior vice president, general counsel, and secretary at ManpowerGroup and a member of the New York Stock Exchange Listed Company Advisory Board. Lucinda Schettler is a senior attorney for ManpowerGroup, specializing in employment law in the U.S. She focuses on the legal issues implicated in the ever-changing world of work, including AI and the use of technology.

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HBR Special Issue 69

HOW RECRUITING WORKS NOW QUICK TAKES

Expanding the Pool How Goldman Sachs Changed the Way It Recruits

by Dane E. Holmes

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centric business—every day our employees engage with our clients to find solutions to their challenges. As a consequence, hiring extraordinary talent is vital to our success and can never be taken for granted. In the wake of the 2008 financial crisis we faced a challenge that was, frankly, relatively new to our now 150-year-old firm. For decades investment banking had been one of the most soughtafter, exciting, and fast-growing industries in the world. That made sense—we were growing by double digits and had high returns, which meant that opportunity and reward were in great supply. However, the crash took some of the sheen off our industry; both growth and returns moderated. And simultaneously, the battle for talent intensified—within and outside our industry. Many of the candidates we were pursuing were heading off to Silicon Valley, private equity, or startups. Furthermore, we were no longer principally looking for a specialized cadre of accounting, finance, and economics majors: New skills, especially coding, were in huge demand at Goldman Sachs—and pretty much everywhere else. The wind had shifted from our backs to our faces, and we needed to respond. Not long ago the firm relied on a narrower set of factors for identifying “the best” students, such as school, GPA, major, leadership roles, and relevant experience—the classic résumé topics. No longer. We decided to replace our hiring playbook with emerging best practices for assessment and recruitment, so we put together a

task force of senior business leaders, PhDs in industrial and organizational psychology, data scientists, and experts in recruiting. Some people asked, “Why overhaul a recruiting process that has proved so successful?” and “Don’t you already have many more qualified applicants than available jobs?” These were reasonable questions. But often staying successful is about learning and changing rather than sticking to the tried-and-true. Each year we hire up to 3,000 summer interns and nearly as many new analysts directly from campuses. In our eyes, these are the firm’s future leaders, so it made sense to focus our initial reforms there. They involved two major additions to our campus recruiting strategy—video interviews and structured interviewing.

Asynchronous video interviews. Traditionally we had flown recruiters and business professionals to universities for first-round interviews. The schools would give us a set date and number of time slots to meet with students. That is most definitely not a scalable model. It restricted us to a smaller number of campuses and only as many students as we could squeeze into a limited schedule. It also meant that we tended to focus on top-ranked schools. How many qualified candidates were at a school became more important than who were the most talented students regardless of their school. However, we knew that candidates didn’t have to attend Harvard, Princeton, or Oxford to excel at Goldman Sachs—our leadership ranks were already rich with people

JOHN KUCZALA

GOLDMAN SACHS is a people-

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from other schools. What’s more, as we’ve built offices in new cities and geographic locations, we’ve needed to recruit at more schools located in those areas. Video interviews allow us to do that. At a time when companies were just beginning to experiment with digital interviewing, we decided to use “asynchronous” video interviews—in which candidates record their answers to interview questions—for all first-round interactions with candidates. Our recruiters record standardized questions and send them to students, who have three days to return videos of their answers. This can be done on a computer or a mobile device. Our recruiters and business professionals review the videos to narrow the pool and then invite the selected applicants to a Goldman Sachs office for finalround, in-person interviews. (To create the video platform, we partnered with a company and built our own digital solution around its product.) This approach has had a meaningful impact in two ways. First, with limited effort, we can now spend more time getting to know the people who apply for jobs at Goldman Sachs. In 2015, the year before we rolled out this platform, we interviewed fewer than 20% of all our campus applicants; in 2018 almost 40% of the students who applied to the firm participated in a first-round interview. Second, we now encounter talent from places we previously didn’t get to. In 2015 we interviewed students from 798 schools around the world, compared with 1,268 for our most recent incoming class. In

the United States, where the majority of our student hires historically came from “target schools,” the opposite is now true. The top of our recruiting funnel is wider, and the output is more diverse. Being a people-driven business, we have worked hard to ensure that the video interviews don’t feel cold and impersonal. They are only one component of a broader process that makes up the Goldman Sachs recruitment experience. We still regularly send Goldman professionals to campuses to engage directly with students at informational sessions, “coffee chats,” and other recruiting events. But now our goal is much more to share information than to assess candidates, because we want people to understand the firm and what it offers before they tell us why they want an internship or a job. We also want them to be as well prepared as possible for our interview process. Our goal is a level playing field. To help achieve it, we’ve created tip sheets and instructions on preparing for a video interview. Because the platform doesn’t allow videos to be edited once they’ve been recorded, we offer a practice question before the interview begins and a countdown before the questions are asked. We also give students a formal channel for escalating issues should technical problems arise, though that rarely occurs. We’re confident that this approach has created a better experience for recruits. It uses a medium they’ve grown up with (video), and most important, they can do their interviews when they feel fresh and at a time that works with their

schedule. (Our data shows that they prefer Thursday or Sunday night—whereas our previous practice was to interview during working hours.) We suspected that if the process was a turnoff for applicants, we would see a dip in the percentage who accepted our interviews and our offers. That hasn’t happened.

Structured questioning and assessments. How can you create an assessment process that not only helps select top talent but focuses on specific characteristics associated with success? Define it, structure it, and don’t deviate from it. Research shows that structured interviews are effective at assessing candidates and helping predict job performance. So we ask candidates about specific experiences they’ve had that are similar to situations they may face at Goldman Sachs (“Tell me about a time when you were working on a project with someone who was not completing his or her tasks”) and pose hypothetical scenarios they might encounter in the future (“In an elevator, you overhear confidential information about a coworker who is also a friend. The friend approaches you and asks if you’ve heard anything negative about him recently. What do you do?”). Essentially, we are focused less on past achievements and more on understanding whether a candidate has qualities that will positively affect

our firm and our culture. Our structured interview questions are designed to assess candidates on 10 core competencies, including analytical thinking and integrity, which we know correlate with long-term success at the firm. They are evaluated on six competencies in the first round; if they progress, they’re assessed on the remaining four during inperson interviews. We have a rotating library of questions for each competency, along with a rubric for interviewers that explains how to rate responses on a fivepoint scale from “outstanding” to “poor.” We also train our interviewers to conduct structured interviews, provide them with prep materials immediately before they interview a candidate, and run detailed calibration meetings using all the candidate data we’ve gathered throughout the recruiting process to ensure that certain interviewers aren’t introducing grade inflation (or deflation). We’re experimenting with prehire assessment tests to be paired with these interviews; we already offer a technical coding and math exam for applicants to our engineering organization. We decided not to pilot these changes and instead rolled them out en masse, because we realized that buy-in would come from being able to show results quickly—and because we know that no

We are focused less on past achievements and more on understanding whether a candidate has qualities that will positively affect our firm and our culture. Our structured interview questions are designed to assess 10 core competencies.

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HBR Special Issue 71

HOW RECRUITING WORKS NOW QUICK TAKES

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and in our industry. And we’re evaluating various tools and tests to bring even more data into the hiring decision process. Can I imagine a future in which companies rely exclusively on machines and algorithms to rate résumés and interviews? Maybe, for some. But I don’t see us ever eliminating the human element at Goldman Sachs; it’s too deeply embedded in our culture, in the work we do, and in what we believe drives success. I’m excited to see where this journey takes us. Our 2019 campus class is shaping up to be the most diverse ever—and it’s composed entirely of people who were selected through rigorous, objective assessments. There’s no way we aren’t better off as a result. Originally published in Harvard Business Review May–June 2019

HBR Reprint R1903B Dane E. Holmes is the global head of human capital management at Goldman Sachs.

Recruiting Strategies for a Tight Talent Market by Erica Dhawan

“FEELING PINNED DOWN?” read the message targeted at Pinterest employees. “This place driving you mad?” asked the clever riff aimed at Uber workers. If any story demonstrates how far employers will go in today’s fierce war for talent, the tale of Snapchat’s geofilter recruiting campaign is it. Last fall Forbes reported that Snapchat had begun using geofilters (overlays that Snapchat users can put on top of images) to poach employees from other top start-ups. Geofilters become available when a user is in a specific location—think Athens, Greece, or Morristown, New Jersey. Or, as it turns out, even the vicinity of 1455 Market Street, the address of Uber’s San Francisco headquarters. Snapchat’s geofilters combined amusing visuals and messages with the web address of the company’s job page, all in the hope that a Twitter engineer

taking a quick Snapchat break might come across the targeted “Fly higher!” message and think, Hey, maybe it’s time for a change. The fight for new recruits is intense—not just in the tech sector but across all industries. But as the Snapchat story establishes, connecting with today’s workforce no longer simply means going to the usual places and doing the usual things. These days, I advise Fortune 500 executives to treat talent as they would customers: Understand their behavior, and design recruiting strategies that meet them where they are. Here are three such innovative approaches for connecting with top talent.

Don’t keep relying on the same old social media platforms. The Society for Human Resource Management reports that 84% of organizations use social media for recruiting, and

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process is perfect. Indeed, what I love most about our new approach is that we’ve turned our recruiting department into a laboratory for continuous learning and refinement. With more than 50,000 candidate video recordings, we’re now sitting on a treasure trove of data that will help us conduct insightful analyses and answer questions necessary to run our business: Are we measuring the right competencies? Should some be weighted more heavily than others? What about the candidates’ backgrounds? Which interviewers are most effective? Does a top-ranked student at a state school create more value for us than an average student from the Ivy League? We already have indications that students recruited from the new schools in our pool perform just as well as students from our traditional ones—and in some cases are more likely to stay longer at the firm. What’s next for our recruiting efforts? We receive almost 500,000 applications each year. From this pool we hire approximately 3%. We believe that many of the other 97% could be very successful at Goldman Sachs. As a result, picking the right 3% is less about just the individual and increasingly about matching the right person to the right role. That match may be made straight out of college or years later. We’re experimenting with résumé-reading algorithms that will help candidates identify the business departments best suited to their skills and interests. We’re looking at how virtual reality might help us better educate students about working in our offices

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82% of them use it primarily in the hunt for passive candidates. If so many companies are using social media, it must be effective, right? Well, not necessarily. What this high percentage means is that on the most popular social media platforms—LinkedIn, Facebook, and Twitter—you’re already vying with your competition for the same pool of expertise. So venture out. Connect with other online platforms where people gather for the pleasure of sharing knowledge. For developers, that may be Stack Overflow, a questionand-answer site specifically for programmers. For the medical field, it may be Doximity, which 60% of U.S. physicians are members of. For Millennial women, it might be Levo or The Muse. For people in other professions, it may be Quora, a website that hosts questions and answers on subjects ranging from programming languages to fashion to the outbreak of the Zika virus. What’s the trick? It’s pretty straightforward: Go on a platform connected to the industry you’re recruiting for, and then look for people who are using it to have smart, relevant conversations. If you are impressed by someone’s questions, answers, or other posts, you may just have identified a potentially valuable employee. At least one company has worked Quora specifically into its recruitment strategy. Highfive, a Silicon Valley–based video and web conferencing supplier, uses Quora to connect “with like-minded individuals.” The company was already developing content, targeted specifically at recruits, that

Connecting to top talent today is about connecting in the right places and with the right attitude.

demonstrated its “culture and the type of company we want to be in 1, 5, and 10 years.” By distributing this message through the Quora community, Highfive was “able to attract the type of people we want, and do it in an original way.” Such creative solutions have paid off: In 2016 Fortune magazine named Highfive to its list of the 10 Best Small Workplaces in Technology.

Generate and nurture your own talent channels. Genesys, a pioneer of customer experience and call center software, has offices across the globe, and it’s growing quickly, having acquired 10 companies since 2012. Part of its success is that the company supports a collaborative work environment and boasts transparent operations from the top down. But a few years ago, delays in signing new hires were impairing its expansion; in 2013 the average time to hire was 100 days. Merijn te Booij, Genesys’s chief marketing officer, decided to stop waiting for the perfect candidate to appear through established channels. He partnered with HR to start an associate program that put new college and experienced professionals through an intensive three-week training, later pairing them with a mentor for ongoing counsel. Since 2014 Genesys has graduated nearly 70 associates from the United States, Africa, South Korea, Malaysia, and South America.

In addition, Genesys began actively networking to build a talent pool and even organized a two-hour event to introduce high school students to the company’s products. Genesys staff plan to remain connected with these students, who may later return as interns or new hires upon graduation. These efforts have definitely made a difference: In 2014 the average time to hire was 50 days—half the time of the previous year. Just one year later, Glassdoor named Genesys one of the Best Places to Work.

Looking for Millennials? Address their specific concerns—and make it funny. Poor Owen. In GE’s recent recruitment advertising campaign, What’s the Matter with Owen?, the fictional star can’t find anyone to share his excitement about his new job: a developer for GE. Everyone he knows is stuck in the same ideological rut: GE is a manufacturer, they all think, not a place to change the world. At a surprise party, his friends struggle to maintain their masks of encouragement. At a backyard gathering, Owen is upstaged by a friend who will be working for an “app where you put fruit hats on animals.” In his family’s living room, his proud parents give him his “grandpappy’s” giant hammer. GE knew that it had an image problem, one that was especially problematic for Millennials, who value purpose over paycheck. The company needed to spread the message that, in fact, GE is involved in fascinating projects that will affect the world in positive ways. And what GE and its ad agency, BBDO, knew is that humor is

one of the most effective ways to connect with this age group. In a 2012 online survey of 2,000 people born after 1981, 88% of people reported that humor is essential to their sense of self. Tanya Giles, former executive vice president for research at MTV Networks, told the New York Times, “One big takeaway is that unlike previous generations, humor, and not music, is their number one form of self-expression.” The What’s the Matter with Owen? campaign premiered on the first episode of The Late Show with Stephen Colbert, the perfect outlet to reach a demographic that prefers comedians to sports stars. Since then, the campaign has been viewed more than 800,000 times on YouTube. As these examples show, connecting to top talent today is about reimagining the possibilities of leveraging all kinds of networks. It’s about connecting in the right places and with the right attitude. And while picking through the dense online tapestry may be daunting, remember: You already employ a staff of experts. Current employees can tell you which sites they use to connect with like-minded individuals and help you launch networks that are organized to meet your company’s specific needs. Originally published on HBR.org April 7, 2016

HBR Reprint H02SXU Erica Dhawan is one of the world’s leading authorities on 21st-century collaboration, the author of Get Big Things Done: The Power of Connectional Intelligence (St. Martin’s Press, 2015), the host of the Masters of Leadership podcast, and the CEO of Cotential. Follow her on Twitter: @edhawan.

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HBR Special Issue 73

THE ERA OF the specialized Rolo-

How Recruiters Can Stay Relevant in the Age of LinkedIn by Atta Tarki and Ken Kanara

dex as the main way to differentiate recruiters is over. LinkedIn killed it. This is not to say that talent-acquisition professionals can no longer add value. On the contrary, technological change has made it possible for recruiters to make themselves more critical to organizations than ever before. Recruiters, however, must adapt and focus their value proposition on five main areas to remain relevant in the new digital era of talent acquisition. They can do this by following these steps:

Help Hiring Managers Define the Correct Search Strategy Asking insightful questions is essential to defining the correct search strategy. Strong recruit-

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ers will play a crucial role as thought partners in conversations with hiring managers, even if that means breaking the traditional transactional recruiter relationship. At a recent conference, Nellie Peshkov, Netflix’s vice president of talent acquisition and one of the leading thinkers in the field, explained, “Our value in talent acquisition is really about coaching, guiding, providing creative thinking and strategies for that hiring manager.” Michael Orozco Jr., one of Netflix’s recruiters, added that while some recruiters ask their hiring manager, “What do you want?” Netflix recruiters ask questions such as “Why are you looking for them?” and “How will they make an impact?”

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HOW RECRUITING WORKS NOW QUICK TAKES

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Recruiters often receive frantic calls from hiring managers looking to fill roles. Convincing them to take a step back can be difficult but valuable. For example, one of our clients recently asked us to urgently hire him a vice president of new retail to support the large number of new stores their company planned to open. “Find me someone who did this at Starbucks,” he told us. Because the coffee chain had also rapidly opened new stores, our client believed a candidate with experience there would have the right skill set to manage a large number of building contractors while recruiting and training staff for the new stores. Instead of leaping off into a search for executives at Starbucks or similar chains, we asked him to describe the main challenges his company’s new stores typically face. The discussion helped our client realize that contrary to his original belief, attracting sufficient foot traffic due to his company’s weak brand recognition was their primary challenge. He therefore concluded that a background at Starbucks was quite likely to be the absolute wrong profile he needed. A few minutes invested up front in such discussions will allow recruiters to focus their efforts from the beginning of a search, target more-ideal profiles, and land candidates faster.

Get the Best Candidates to Apply A 2016 SilkRoad study of 13 million applicants and 300,000 hires at 1,200 companies revealed that the “post and pray” strategy is still the

most popular way of hiring candidates. That is, 42% of hires came from posting roles on job boards and company websites. Recruiter-sourced candidates represented only 10% of the hires.

Convincing hiring managers to take a step back can be difficult but valuable.

While job postings have some benefits, hoping that star performers will fall into your lap, especially during the lowest period of unemployment in almost 50 years, is not advisable. Successful recruiters help organizations by building a repeatable and scalable formula for finding and engaging star performers. Recruiters can do this by experimenting with and increasing the efficiency of other sourcing channels. At our firm, we have found the following through trial and error of thousands of messages when actively sourcing candidates: • For some roles, emails to candidates that do not include a job description are 27% more efficient than those that do. This could be because candidates have more trust in emails without a link or attachment or because emails with job descriptions are longer. • Personalized emails are about 75% more effective than generic ones. • LinkedIn messages are about six times (!) more effective than emails for parts of the candidate pool.

Select the Best of the Best The next step is to help hiring managers better understand how to predict job performance. Google’s recruiting team is perhaps the best in the world at this: They help hiring managers understand what categories of questions they should ask candidates and even provide hiring managers with sample questions they can ask. In his book Work Rules! Insights from Inside Google That Will Transform How You Live and Lead (Twelve, 2015), Laszlo Bock, former senior vice president of people operations at Google, described how he helped reduce bias in Google’s interview process by having an independent committee make hiring decisions and incorporating structured interview questions and job knowledge tests into their process.

Get Candidates Over the Finish Line Strong recruiters will help hiring managers get candidates over the finish line by helping their companies create a positive candidate experience as well as organizing and managing the interview and offer process. One candidate we spoke with who had recently declined an offer cited how she had originally been excited about the company’s pitch about being entrepreneurial and fast-moving, but started doubting if this was true when their interview process dragged on for three months.

improve their methods. Without establishing this critical step, it is difficult to determine what is working, and what isn’t. For instance, job knowledge tests may be predictive of job performance at Google, but have they been as successful at your organization? Our own testing underscores this point, as we have found that methods that were highly effective two years ago no longer work. One simple example is that by using a candidate’s first name in the email subject line, we used to get up to twice as many candidates to engage in our searches. Now, perhaps because this tactic has been overused, we have abandoned this approach as it no longer increases candidate engagement. CEOs who position their talent acquisition teams to follow these five steps will gain a significant advantage in attracting the right talent in the new era of talent acquisition. Originally published on HBR.org February 8, 2019

HBR Reprint H04SED Atta Tarki is the founder and CEO of specialized executive search and projectbased staffing firm Ex-Consultants Agency. He is also the author of Evidence Based Recruiting: How Google and Netflix Leverage Talent Acquisition to Gain a Competitive Edge (Ex-Consultants Agency, forthcoming). Ken Kanara is the president of Ex-Consultants Agency. He has more than a decade of experience in consulting and executive search, with a focus on private equity and PE portfolio companies.

Evaluate Finally, recruiters should evaluate their hiring practices on an ongoing basis and apply an iterative process to continuously

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HBR Special Issue 75

RETAINING THE BEST

Your Workforce Is More Adaptable Than You Think Employees are eager to embrace retraining—and companies need to seize this as a competitive opportunity. by Joseph B. Fuller, Manjari Raman, Judith K. Wallenstein, and Alice de Chalendar

M

ANY MANAGERS have little

Originally published in May–June 2019

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faith in their employees’ ability to survive the twists and turns of a rapidly evolving economy. “The majority of people in disappearing jobs do not realize what is coming,” the head of strategy at a top German bank recently told us. “My call center workers are neither able nor willing to change.” This kind of thinking is common, but it’s wrong, as we learned after surveying thousands of employees around the world. In 2018, in an attempt to understand the various forces shaping the nature of work, Harvard Business School’s Project on Managing the Future of Work and the Boston Consulting Group’s Henderson Institute came together to conduct a survey spanning 11 countries—Brazil, China, France, Germany, India, Indonesia, Japan, Spain, Sweden, the United Kingdom, and the United States—gathering responses from 1,000 workers in each. In it we focused solely on the people most vulnerable to changing dynamics: lower-income and middle-skills workers. The majority of them were earning less than the average household income in their countries, and all of them had no more than two years of postsecondary education. In each of eight countries— Brazil, China, France, Germany, India, Japan, the

United Kingdom, and the United States—we then surveyed at least 800 business leaders (whose companies differed from those of the workers we surveyed). In total we gathered responses from 11,000 workers and 6,500 business leaders. What we learned was fascinating: The two groups perceived the future in significantly different ways. Given the complexity of the changes that companies are confronting today and the speed with which they need to make decisions, this gap in perceptions has serious and far-reaching consequences for managers and employees alike. Predictably, business leaders feel anxious as they struggle to marshal and mobilize the workforce of tomorrow. In a climate of perpetual disruption, how can they find and hire employees who have the skills their companies need? And what should they do with people whose skills have become obsolete? The CEO of one multinational company told us he was so tormented by that last question that he had to seek counsel from his priest. The workers, however, didn’t share that sense of anxiety. Instead, they focused more on the opportunities and benefits that the future holds for them, and they revealed themselves to be much more eager to embrace change and learn new skills than their employers gave them credit for.

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RETAINING THE BEST YOUR WORKFORCE IS MORE ADAPTABLE THAN YOU THINK

The Nature of the Gap

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When executives today consider the forces that are changing how work is done, they tend to think mostly about disruptive technologies. But that’s too narrow a focus. A remarkably broad set of forces is transforming the nature of work, and companies need to take them all into account. In our research we’ve identified 17 forces of disruption, which we group into six basic categories. (See the sidebar “The Forces Shaping the Future of Work.”) Our surveys explored the attitudes that business leaders and workers had toward each of them. In their responses, we were able to discern three notable differences in the ways that the two groups think about the future of work. The first is that workers seem to recognize more clearly than leaders do that their organizations are contending with multiple forces of disruption, each of which will affect how companies work differently. When asked to rate the impact that each of the 17 forces would have on their work lives, using a 100-point scale, the employees rated the force with the strongest impact 15 points higher than the force with the weakest impact. In comparison, there was only a nine-point spread between the forces rated the strongest and the weakest by managers. In fact, the leaders seemed unable or unwilling to think in differentiated ways about the forces’ potential for disruption. When asked about each force, roughly a third of them described it as having a significant impact on their organization today; close to half projected that it would have a significant impact in the future; and about a fifth claimed it would have no impact at all. That’s a troubling level of uniformity, and it suggests that most leaders haven’t yet figured out which forces of change they should make a priority. Interestingly, workers appeared to be more aware of the opportunities and challenges of several of the forces. Notably, workers focused on the growing importance of the gig economy, and they ranked “freelancing and labor-sharing platforms” as the third most significant of all 17 forces. Business leaders, however, ranked that force as the least significant. The second difference that emerged from our survey was this: Workers seem to be more adaptive and optimistic about the future than their leaders recognize. The conventional wisdom, of course, is that workers fear that technology will make their jobs obsolete. But our survey revealed that to be

a misconception. A majority of the workers felt that advances such as automation and artificial intelligence would have a positive impact on their future. In fact, they felt that way about two-thirds of the forces. What concerned them most were the forces that might allow other workers—temporary, freelance, outsourced—to take their jobs. When asked why they had a positive outlook, workers most commonly cited two reasons: the prospect of better wages and the prospect of more interesting and meaningful jobs. Both automation and technology, they felt, heralded opportunity on those fronts—by contributing to the emergence of more-flexible and self-directed forms of work, by creating alternative ways to earn income, and by making it possible to avoid tasks that were “dirty, dangerous, or dull.” In every country workers described themselves as more willing to prepare for the workplace of the future than managers believed them to be (in Japan, though, the percentages were nearly equal). Yet when asked what was holding workers back, managers chose answers that blamed employees, rather than themselves. Their most common response was that workers feared significant change. The idea that workers might lack the support they needed from employers was only their fifth-most-popular response. That brings us to our third finding: Workers are seeking more support and guidance to prepare themselves for future employment than management is providing. In every country except France and Japan, significant majorities of workers reported that they—and not their government or their employer—were responsible for equipping themselves to meet the needs of a rapidly evolving workplace. That held true across age groups and for both men and women. But workers also felt that they had serious obstacles to overcome: a lack of knowledge about their options; a lack of time to prepare for the future; high training costs; the impact that taking time off for training would have on wages; and, in particular, insufficient support from their employers. All are barriers that management can and should help workers get past.

What Employers Can Do to Help The gap in perspectives is a problem because it leads managers to underestimate employees’

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Idea in Brief ambitions and underinvest in their skills. But it also shows that there’s a vast reserve of talent and energy companies can tap into to ready themselves for the future: their workers. The challenge is figuring out how best to do that. We’ve identified five important ways to get started.

1. Don’t just set up training programs— create a learning culture. If companies today engage in training, they tend to do it at specific times (when onboarding new hires, for example), to prepare workers for particular jobs (like selling and servicing certain products), or when adopting new technologies. That worked well in an era when the pace of technological change was relatively slow. But advances are happening so quickly and with such complexity today that companies need to shift to a continuouslearning model—one that repeatedly enhances employees’ skills and makes formal training broadly available. Firms also need to expand their portfolio of tactics beyond online and off-line courses to include learning on the job through project staffing and team rotations. Such an approach can help companies rethink traditional entry-level barriers (among them, educational credentials) and draw from a wider talent pool. Consider what happens at Expeditors, a Fortune 500 company that provides global logistics and freight-forwarding services in more than 100 countries. In vetting job candidates, Expeditors has long relied on a “hire for attitude, train for skill” approach. Educational degrees are appreciated but not seen as critical for success in most roles. Instead, for all positions, from the lowest level right up to the C-suite, the company focuses on temperament and cultural fit. Once on staff, employees join an intensive program in which every member of the organization, no matter how junior or senior, undertakes 52 hours of incremental learning a year. This practice supports the company’s promotefrom-within culture. Expeditors’ efforts seem to be working: Turnover is low (which means substantial savings in hiring, training, and onboarding costs); retention is high (a third of the company’s 17,000 employees have worked at the company for 10 years or more); most senior leaders in the company have risen through the ranks; and several current vice presidents and senior vice presidents, along with the current and former CEOs, got their jobs despite having no college degree.

2. Engage employees in the transition instead of herding them through it. As companies transform themselves, they often find it a challenge to attract and retain the type of talent they need. To succeed, they have to offer employees pathways to professional and personal improvement—and must engage them in the process of change, rather than merely inform them that change is coming. That’s what ING Netherlands did in 2014, when it decided to reinvent itself. The bank’s goal was ambitious: to turn itself into an agile institution almost overnight. The company’s current CEO, Vincent van den Boogert, recalls that the company’s leaders began by explaining the why and the what of the transformation to all employees. Mobile and digital technologies were dramatically altering the market, they told everybody, and if ING wanted to meet the expectations of customers, improve operations, and deploy new technological capabilities, it would have to become faster, leaner, and more flexible. To do that, they said, the company planned to make investments that would reduce costs and improve service. But it would also eliminate a significant number of jobs—at least a quarter of the total workforce. Then came the how. Rather than letting the ax fall on select employees—a process that creates psychological trauma throughout a company—ING decided that almost everybody at the company, regardless of tenure or seniority, would be required to resign. After that, anybody who felt his or her attitude, capabilities, and skills would be a good fit at the “new” bank could apply to be rehired. That included Van den Boogert himself. Employees who did not get rehired would be supported by a program that would help them find jobs outside ING. None of this made the company’s transformation easy, of course. But according to Van den Boogert, the inclusive approach adopted by management significantly minimized the pain that employees felt during the transition, and it immediately set the new, smaller bank on the path to success. The employees who rejoined ING actively embraced its new mission, felt less survivor’s remorse, and devoted themselves with excitement to the job of transformation. “When you talk about the why, what, and how at the same time,” Van den Boogert told us, “people are going to challenge the why to prevent the how. But in this case, everyone had already been inspired by the why and what.”

THE PROBLEM As they try to build a workforce in a climate of perpetual disruption, business leaders worry that their employees can’t—or just won’t—adapt to the big changes that lie ahead. How can companies find people with the skills they will need?

WHAT THE RESEARCH SHOWS Harvard Business School and the BCG Henderson Institute surveyed thousands of business leaders and workers around the world and discovered an important gap in perceptions: Workers are far more willing and able to embrace change than their employers assume.

THE SOLUTION This gap represents an opportunity. Companies need to start thinking of their employees as a reserve of talent and energy that can be tapped by providing smart on-the-job skills training and career development.

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HBR Special Issue 79

RETAINING THE BEST YOUR WORKFORCE IS MORE ADAPTABLE THAN YOU THINK

THE FORCES SHAPING THE FUTURE OF WORK ACCELERATING TECHNOLOGICAL CHANGE • New technologies that replace human labor, threatening employment (such as driverless trucks) • New technologies that augment or supplement human labor (for example, robots in health care) • Sudden technology-based shifts in customer needs that result in new business models, new ways of working, or faster product innovation • Technology-enabled opportunities to monetize free services (such as Amazon web services) or underutilized assets (such as personal consumption data) GROWING DEMAND FOR SKILLS • General increase in the skills, technical knowledge, and formal education required to perform work • Growing shortage of workers with the skills for rapidly evolving jobs CHANGING EMPLOYEE EXPECTATIONS • Increased popularity of flexible, self-directed forms of work that allow better work-life balance • More widespread desire for work with a purpose and opportunities to influence the way it is delivered (for example, greater team autonomy)

SHIFTING LABOR DEMOGRAPHICS • Need to increase workforce participation of underrepresented populations (such as elderly workers, women, immigrants, and rural workers) TRANSITIONING WORK MODELS • Rise of remote work • Growth of contingent forms of work (such as on-call workers, temp workers, and contractors) • Freelancing and labor-sharing platforms that provide access to talent • Delivery of work through complex partner ecosystems (involving multiple industries, geographies, and organizations of different sizes), rather than within a single organization EVOLVING BUSINESS ENVIRONMENT • New regulation aimed at controlling technology use (for example, “robot taxes”) • Regulatory changes that affect wage levels, either directly (such as minimum wages or Social Security entitlements) or indirectly (such as more public income assistance or universal basic income) • Regulatory shifts affecting crossborder flow of goods, services, and capital • Greater economic and political volatility as members of society feel left behind

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3. Look beyond the “spot market” for talent. Most successful companies have adopted increasingly aggressive strategies for finding critical high-skilled talent. Now they must expand that approach to include a wider range of employees. AT&T recognized that need in 2013, while developing its Workforce 2020 strategy, which focused on how the company would make the transition from a hardware-centric to a software-centric network. The company had undergone a major transformation once before, in 1917, when it launched plans to use mechanical switchboards rather than human operators. But it carried that transformation out over the course of five decades! The Workforce 2020 transformation was much more complex and had to happen on a much faster timeline. To get started, AT&T undertook a systematic audit of its quarter of a million employees to catalog their current skills and compare those with the skills it expected to need during and after its revamp. Ultimately, the company identified 100,000 employees whose jobs were likely to disappear, and several areas in which it would face skills and competency shortages. Armed with those insights, the company launched an ambitious, multiyear $1 billion initiative to develop an internal talent pipeline instead of simply playing the “spot market” for talent. In short, to meet its evolving needs, AT&T decided to make retraining available to its existing workforce. Since then, its employees have taken nearly 3 million online courses designed to help them acquire skills for new jobs in fields such as application development and cloud computing. Already, this effort has yielded some unexpected benefits. The company now hires far fewer contractors to meet its needs for technical skills, for example. “We’re shifting to employees,” one of the company’s top executives told CNBC this past March, “because we’re starting to see the talent inside.”

4. Collaborate to deepen the talent pool. In a fast-evolving environment, competing for talent doesn’t work. It simply leads to a tragedy of the commons. Individual companies try to grab the biggest share of the skilled labor available, and these self-interested attempts just end up creating a shortage for all.

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To avoid that problem, companies will have to fundamentally change their outlook and work together to ensure that the talent pool is constantly refreshed and updated. That will mean teaming up with other companies in the same industry or region to identify relevant skills, invest in developing curricula, and provide on-the-job training. It will also require forging new relationships for developing talent by, for instance, engaging with entrepreneurs and technology developers, partnering with educational institutions, and collaborating with policy makers. U.S. utilities companies have already begun doing this. In 2006 they joined forces to establish the Center for Energy Workforce Development. The mission of the center, which has no physical office and is staffed primarily by former employees from member companies, is to figure out what jobs and skills the industry will need most as its older workers retire—and then how best to create a pipeline to meet those needs. “We’re used to working together in this industry,” Ann Randazzo, the center’s executive director, told us. “When there’s a storm, everybody gets in their trucks. Even if we compete in certain areas, including for workers, we’ve all got to work together to build this pipeline, or there just aren’t going to be enough people.” The center quickly determined that three of the industry’s most critical middle-skills jobs— linemen, field operators, and energy technicians— would be hit hard by the retirement of workers in the near future. Together, those three jobs make up almost 40% of a typical utility’s workforce. To make sure they wouldn’t go unfilled, CEWD implemented a two-pronged strategy. It created detailed tool kits, curricula, and training materials for all three jobs, which it made available free to utility companies; and it launched a grassroots movement to reach out to next-generation workers and promote careers in the industry. CEWD believes in connecting with promising talent early—very early. To that end, it has been working with hundreds of elementary, middle, and high schools to create materials and programs that introduce students to the benefits of working in the industry. These include a sense of larger purpose (delivering critical services to customers); stability (no offshoring of jobs, little technological displacement); the use of automation and technology to make jobs less physically taxing and more intellectually engaging; and, last but not least, surprisingly high wages. Describing the program

to us, Randazzo said, “You’re growing a workforce. We had to start from scratch to get students in the lower grades to understand what they need to do and to really be able to grow that all the way through high school to community colleges and universities. And it’s not a one-and-done. We have to continually nurture it.”

5. Find ways to manage chronic uncertainty.

Firms need to expand their portfolio of tactics beyond online and off-line courses to include learning on the job.

In today’s world, managers know that if they don’t swiftly identify and respond to shifts, their companies will be left behind. So how can firms best prepare? The office-furniture manufacturer Steelcase has come up with some intriguing ideas. One is its Strategic Workforce Architecture and Transformation (SWAT) team, which tracks emerging trends and conducts real-time experiments in how to respond to them. The team has launched an internal platform called Loop, for example, where employees can volunteer to work on projects outside their own functions. This benefits both the company and its employees: As new needs arise, the company can quickly locate workers within its ranks who have the motivation and skills to meet them, and workers can gain experience and develop new capabilities in ways that their current jobs simply don’t allow. Employees at Steelcase have embraced Loop, and its success illustrates an idea that came through very clearly in our survey results. As Jill Dark, the director of the SWAT team, put it to us, “If you give people the opportunity to learn something new or to show their craft, they will give you their best work. The magic is in providing the opportunity.” That’s a lesson that all managers should HBR Reprint R1903H heed.

Joseph B. Fuller is a professor of management practice and a cochair of the Project on Managing the Future of Work at Harvard Business School. Judith K. Wallenstein is a senior partner and managing director at Boston Consulting Group, a BCG Fellow, and the director of the BCG Henderson Institute in Europe. Manjari Raman is a program director and senior researcher for Harvard Business School’s Project on U.S. Competitiveness and the Project on Managing the Future of Work. Alice de Chalendar is a consultant at BCG and a researcher at the BCG Henderson Institute.

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Talent Management and the Dual-Career Couple Rigid tours of duty are the wrong approach to development. by Jennifer Petriglieri

A

S THE HEAD of a large manufacturing plant at a multinational conglomerate, an executive I’ll call David had proved himself a competent, trustworthy manager. So when the presidency of one of the company’s key businesses unexpectedly became vacant, the CEO sat David down to share the good news that he had been chosen for the role. He had earned it. Sudden career announcements like this are actually pretty common. Even so, David was caught off guard and didn’t know what to say. The head of

ILLUSTRATION BY JOANNA ŁAWNICZAK

HR—who was at the meeting—sensed his surprise. Though the offer may have come earlier than expected, she explained, his current boss had been consulted and supported the move. It was a golden opportunity for David, and everyone was rooting for him to succeed. He would have time to make all the necessary arrangements, the CHRO added, and the company would gladly help his family move to the other side of the country, where the business he would run was based. He would start in four weeks. After asking a few questions and learning about the generous raise that would come with the

Originally published in May–June 2018

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promotion, David thanked the CEO and the CHRO warmly and promised to discuss the opportunity with his wife that evening. “Of course,” they replied, smiling. They were shocked when David turned down the offer the next day. He was committed to the company and to his career, he said, but he was also committed to his wife’s career. She had a challenging final year to complete in her surgery residency program, and a move now would hurt her. David suggested various options—taking on the role at a later date, commuting for a period, or working remotely. The CEO rejected them all. “Leadership is about showing up,” he snapped. A joyful occasion had turned sour in less than 24 hours. The CEO was angry. The company had invested heavily in David. Where was his dedication when it counted, and how could he expect to advance if he was not willing to move for a leadership role? The CHRO was equally confused and upset by David’s response. After all, she had introduced work-family policies and generous mobility allowances to support employees like him. David felt cornered. He had been presented with an untimely, rigid option, and now he was being punished for daring to try to negotiate it. The company soon found another candidate for the job. David continued to perform well in his role, but things had changed. He felt that he was no longer on the top team’s talent radar. Nine months later, when his wife, Helen, completed her residency and was again mobile, she and David put out feelers for career opportunities. David was immediately headhunted by a rival company to lead its largest business, in a city where Helen found a position at a prestigious hospital. David’s career was back on track, and his wife’s was launched. And David’s old employer had lost a talented leader—after spotting him, grooming him, and offering him a plum role. I learned about David from the CHRO, who told me that the company still had not figured out how best to manage the growing number of its employees who want to advance but also care deeply about their partners’ careers. I’ve seen this again and again in my work over the past several years. Otilia Obodaru, of Rice University, and I have studied more than 100 dual-career couples across generations and organizational settings (interviewing both members of each couple), and I have conducted in-depth interviews with the heads of people strategy at 32 large companies in

tech, health care, professional services, and other industries. I also work closely with the heads of talent and learning at companies that send executives to the management program I codirect at INSEAD. Most talent VPs, I’ve found, are keenly aware of the rise of dual-career couples. Today, in almost half the two-parent households in the United States (compared with 31% in 1970), both parents work full-time. Still, companies struggle to anticipate and mitigate the effects on their talent pipelines. People in David’s predicament resign after their employers have invested in them, and those stories spread like wildfire in organizations, prompting other dual-career high potentials to look for the nearest exit. The crux of the problem is that companies tend to have fixed paths to leadership roles, with set tours of duty and long-held ideas about what ambition looks like. That creates rigid barriers for employees—and recruitment and retention challenges for their employers, many of whom are failing to consider the whole person when mapping out high potentials’ career trajectories. To reap the benefits of their investments in human capital, organizations must adopt new strategies for managing and developing talent. I’ll describe them, but first let’s take a closer look at why traditional approaches often fail.

The Trouble with the Usual Talent Strategies Although most companies deny having traditional career ladders, executives in midsize and large organizations are widely expected to cycle through a variety of divisions and functions en route to the executive suite. This talent-development model usually involves multiple relocations. It originated in the early 1980s, before technology had opened the door to efficient, productive virtual work. For the most part, talent was “unbounded” (my term). That is, spouses didn’t have competing careers, so they managed home and family life, freeing up executives to meet their companies’ demands. Times have changed, of course, but most talent management programs are still designed as if every couple had a dedicated homemaker and the internet didn’t exist. For executives whose partners have full careers, such programs create two major challenges (and, my research suggests, two top reasons to resign). They are:

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Idea in Brief The mobility challenge. Members of dualcareer couples understand that they’ll need to make multiple moves across functions and geographies if they want to ascend to senior roles—and they’re not averse to that. But having to drop everything and move at a moment’s notice forces them to choose which partner’s career will lead and which will follow. These days, fewer couples are willing to make that trade-off. Take Melissa and Craig, both of whom were managers in their companies’ “future leader” programs. They had long harbored dreams of working abroad, but when Craig was offered a “now-ornever golden opportunity” in London, he turned it down. “Melissa could probably have found a job in London, but not at the same level and on the same track,” he told me. “Equality is important to us, and we know that senior careers are uncertain. So we want to hedge against risk by balancing our careers. We need to move in a more planned way.” Eventually, the two did make an international move. First they agreed on a destination—Dubai— and then they launched parallel job searches. Melissa’s interest in moving to the Middle East landed her an internal transfer and a boost in responsibilities. Craig’s company was less keen on a transfer, but he found an exciting new role with a competitor. Craig’s company lost a talented manager to a rival not because he wasn’t mobile but because it couldn’t match mobility options to his needs. Even if he had accepted the London job, his employer might have paid a price in the long run. Expatriate assignments and geographic relocations are often cut short when an executive’s partner struggles to adapt to a new community, for example, or can’t find a suitable career opportunity. Because Craig secured a good job in Dubai, Melissa’s expat assignment was more likely than many others to succeed. The mobility challenge is exacerbated when organizations expect several moves in a short time frame, which is not unusual. At one global chemical company, for example, a new management acceleration program moves people through three functions—and to three locations around the world—within a year and a half. “You move every six months,” the head of talent explained. This rounds out participants’ experience and knowledge in an efficient way. But, she added, “it certainly doesn’t work if you’re in a dual-career couple or for anyone who doesn’t want to drag

their family around the world….So it stops a lot of great talent from even applying.” Even when managers are not enrolled in formal rotation programs, many companies expect their best people to spend no more than three years in any role before moving to a new challenge. Those who don’t progress at that pace will look stagnant and perhaps be shown the door. “I’m dealing with a very talented woman who is going to lose her job,” the vice president of HR at a global logistics firm lamented. “She’s at the end of a three-year role, and she cannot relocate because of her husband’s career. Rather than being flexible and saying, ‘You can still live in Charlotte and commute to Atlanta three days a week,’ her manager is saying, ‘No, it’s all or nothing. We’ll just have to let her go.’ It’s frustrating. Retaining senior female talent is a key priority for us, but the business is stuck in this rigid way of operating.” I heard stories like this from about 40% of my research sample. It sounds crazy to set an arbitrary three-year limit on someone who is doing excellent work. But most companies assess executives on potential as well as performance—and people who don’t want to move are dinged on potential, because they’re perceived as lacking ambition. Thwarted advancement is the most likely outcome, particularly for junior and midlevel managers. But at senior levels, where fewer lateral moves are available, there’s a great deal of pressure to “move up or out.” The flexibility challenge. Every family has tasks that must get done—buying groceries, making meals, taking the car in for maintenance and repairs, driving children to and from school and activities, and so on. In traditional couples, the noncareer partner assumes the lion’s share of these responsibilities. For dual-career couples (even those who can afford to hire help), managing all this on top of work is a constant juggling act. As I studied these couples, it was clear that they do not want to work less, but they do need to work smarter and more flexibly. Most leadership roles and paths, however, lack flexibility—and people who seek it are penalized. This can lead to what one executive, Emily, called the “‘Whose job is more important today?’ roulette.” She and her partner, Jamal, had a finely tuned system: Emily dropped the kids at school in the morning and worked late in the evening, while Jamal did the opposite. However, when they hit a bump—sick kids, home repairs, elderly parents

THE PROBLEM High potentials are increasingly committed to their partners’ careers as well as their own, but most companies haven’t figured out how to accommodate that commitment. They invest heavily in grooming star performers for leadership roles, only to have them resign when confronted with flexibility and mobility challenges. That’s wreaking havoc on recruitment and retention.

THE SOURCE Because “future leaders” are usually expected to advance in a certain way—often through set tours of duty around the globe— it can be difficult for members of dual-career couples to move ahead at work.

THE SOLUTION Organizations can remove barriers to advancement by allowing people to develop in morecreative ways—through brief “job swaps,” for example, or “commuter” roles. But often a culture change is needed. Instead of stigmatizing flexibility, companies must learn to embrace it.

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who needed help—the system broke down and frantic negotiations began. Even when the system worked well, they found themselves being punished. Jamal, a management consultant, described being passed over for a promotion: “I brought more business to my firm than any other senior manager last year, but I left work at 5:30 PM every day. That was noticed. It’s not that I wasn’t working. I always put in an extra two or three hours after the kids went to bed. But I was told that my lack of presence signaled a lack of commitment to the firm.” The expectation that rising stars should always be in the office made more sense when most business was local or regional and much of it had to be done in person. But now business is global, runs 24/7, and in many cases must be conducted virtually—and yet physical absence is still stigmatized. The head of learning and development at an engineering firm told me, “We’re one of those companies that has had a flexible working policy for a long time, but due to stigma we have not allowed or encouraged people to take full advantage of that, and those who do have been sidelined in their careers.” The irony is that research has shown the benefits of flexible working—for instance, improvements in efficiency and knowledge sharing. And in my interviews I’ve found that an organization’s commitment to cultivating and valuing flexible work is a key draw for members of dual-career couples. HR teams are well aware of these advantages. That’s why they put flexible policies in place. If companies know what works in theory, why do they keep reverting to their old ways of managing and grooming talent? A big reason is inertia: It’s how they’ve done it for a long time, and they’re more likely to make incremental changes than overhauls. There’s also a dues-paying element, I’ve learned. People at the top tend to think, “Well, if I did it, so should the next generation.” It can be hard for them to identify with dual-career constraints if they came of age in a different time and never faced those constraints themselves. Because the current crop of high potentials aren’t willing to sacrifice their partners’ needs, a bit of a stalemate results—and mobility and flexibility challenges go largely unaddressed. The head of learning and development at a large recruitment company put it this way: “Our Millennials are as ambitious and committed to their careers as other generations, but they also hold a

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place for other people in their lives....This affects how they want to work and progress. If we cannot change to cater to them, we will lose more and more talent.” That generational shift is the result of changing marriage patterns that have profound implications for organizations. Over the past three decades, assortative mating—the tendency of people with similar outlooks and levels of education and ambition to marry each other—has risen by almost 25%. Nowadays, when an organization hires a manager in his or her thirties, that person’s partner is also likely to be an ambitious professional with a fastpaced career. Paradoxically, a trend that should expand the talent pool for companies shrinks it instead, because of their outdated ways of developing people.

A New Talent Strategy Designing effective leadership-development paths for members of dual-career couples requires two changes: a revised notion of what is needed to achieve growth and advancement, and a shift in the organizational culture to embrace flexibility in the talent development process.

Recognize that what matters more than where. Organizations must stop worrying so much about where aspiring leaders serve their time and instead focus on the skills and networks to be acquired. The talent management director of a global engineering firm described her company’s approach like this: “We have a list of experiences that future leaders need to have, but they are location-agnostic. For example, managing a business in crisis or doing a turnaround—sometimes you don’t have to move at all to get these experiences.” That’s a departure from the days when the company’s CEOs believed that one had to work in set locations to move up. Shifting the focus from “where” to “what” opens a range of creative solutions, such as brief job swaps, short-term assignments in various organizations or units (sometimes called secondments), and commuter roles. Take Indira, an executive at a large pharmaceuticals company who needed to build experience and knowledge of the Chinese market. To accommodate her dual-career situation, her company facilitated a six-week job swap with a peer in China, followed by a six-month strategic project for the pair to work on. “Because it was a job swap, we felt a mutual responsibility to help each other,”

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Indira told me. “We acted as each other’s coaches, extensively briefed each other before the swap, spoke almost every day during it, and worked closely together on the subsequent project.” This model of having a peer-coach coupled with a burst of intensive experience acted as a “development accelerator,” she said. “I absorbed so much in that process.” For instance, Indira was able to quickly build (and then maintain) a strong network in China. Her Chinese peer made great introductions, vouched for her, and asked people to “look after her” on the ground. (She did the same for him in the United States.) Acutely aware that she would be there for only six weeks, she didn’t want to waste a second, so she made an enormous effort, working evenings and weekends. In that time Indira acquired important knowledge of the local market, the cultural aspects of doing business in China, and the variations in company culture between the two countries. And she gained valuable perspective, having never before worked outside the United States. As she put it, she saw that there was “more than one way to skin a cat.” She said she became better at problem solving and dealing with uncertainty. Indira’s experience is common. Job swaps and shorter-term assignments facilitate rapid development of the networks, skills, and perspective required to progress—which means they can circumvent, or at least minimize, the mobility challenge. When more time—six months to two years— is needed for development, some companies are

When executives see that people with flexible schedules are still working hard, they adjust their own ways of working—and change the culture.

experimenting with partially remote leadership roles to accommodate members of dual-career couples. Managers work three or four days a week at the assignment location and the remainder of the week at home. Historically, this sort of arrangement has been stigmatized, as the head of HR at a global mining company explained: “Business leaders believed it signaled a lack of commitment and that people used it to simply work less.” But companies, including his own, are changing their position. “More and more people in the talent pool are asking for it, and we have the technology to make it work, so we’re a lot more open—especially when it’s likely that someone will return to their home location at the end of their assignment.” This view is supported by a growing body of research showing that people who telecommute don’t work less than their colleagues at the office. In fact, they often put in more hours and are more productive in the hours they work. Though networks, skills, and experiences can be acquired through job swaps, short-term assignments, and remote-leadership arrangements, full-time relocation is sometimes necessary to move one’s career forward. Members of dualcareer couples know that, yet they often feel let down by organizations that offer what one executive described as “a wealth of resources but little real support.” She explained that the resources made available to mobile talent are usually tailored to “trailing” homemakers or secondarycareer partners, not to full-career partners. They typically include cultural adaptation courses, introductions to homemaker networks, and information about various social activities. When career help is offered, it is geared toward parttime secretarial or teaching posts, for example, or volunteering. Thus, even when resources are abundant, they are often not appropriate for dual-career couples. Some companies are tackling this shortcoming by using resources such as the International Dual Career Network as two-way headhunters. The mobile employee’s partner can register to receive access to workshops, placement support, and other job seekers’ services. And without paying a headhunter’s fee, the mobile employee’s organization can fill other vacant positions with qualified people in the network, who are quite clear about their location requirements. As one IDCN member told me, “We’ve filled some of our key senior positions through the network. This

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isn’t a pool of trailing spouses. We’re tapping into a pool of highly skilled people, in some cases more skilled than the talent who is leading the geographic move.”

Remove cultural obstacles to flexibility.

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Even when companies redesign their talent strategies so that their people can expand networks, skills, and experiences in new ways, those policies often get blocked culturally. That risk is particularly high when leaders from the unbounded generation subscribe to the view that the mobility and flexibility challenges of dual-career couples are, as one executive put it, “personal things that talent should work out for themselves.” For HR’s benefit, such leaders may pay lip service to supporting members of dual-career couples—or they may genuinely believe they’re being supportive—while still, consciously or not, discouraging or punishing the use of flexible work policies. To give their new talent strategies a fighting chance, companies need to change their culture. First, they must educate senior leaders about contemporary talent and the best ways to attract and nurture it. One organization I spoke with was using reverse mentoring—partnering a senior executive with a talented Millennial—to foster this awareness. “It’s very effective,” the head of HR said. “Once leaders understand the challenges, they are much better at accommodating them—and of course those executives who really ‘get it’ are able to hoard the best talent.” The strongest examples I’ve seen set up the reverse mentoring in a bilateral way: The senior executive mentors a Millennial on career and organizational matters, and the Millennial mentors the executive on a range of current issues—sometimes technology and social media, but more often what motivates Millennials and what their lives are like. That this exposure changes mindsets mirrors a discovery in another area of study: the finding that men whose wives have careers are less likely to discriminate against women at work and more likely to facilitate their career development. The psychological mechanism at play here is personalization. Someone who experiences “the other’s” situation firsthand is much more likely to understand it and respond in a supportive way. When companies broaden senior leaders’ minds through reverse mentoring and updates on the proven benefits of working flexibly, attitudes about flexible work quickly shift, and that’s what transforms the culture. Here’s how it happens:

When executives see that Millennials (and others) with flexible schedules are still working hard and producing results, they revise their assumptions and begin to adjust their own ways of working. That has ripple effects. Even if the boss makes only small changes, the “signaling” impact is large—it gives others tacit permission to work more flexibly. One HR professional in a manufacturing company pointed out, “Now we have leaders saying, ‘Hey, listen, I’ve got to take off and run to a ball game,’ or ‘We’re going out for dinner.’ Or whatever it may be. That helps set the tone.” It’s especially powerful when senior men behave this way. That challenges the gender stereotype and also creates a more desirable place for members of dual-career couples to work. Joshua, a manager in the high-potential program of a global consumer goods company and part of a dual-career couple, explained: “Word gets around the HiPo group which senior managers encourage flexible working, and we compete like crazy to get assignments with them.”

COMPANIES MUST EMBRACE a new model of talent management to attract and retain tomorrow’s leaders. When high potentials see that it’s possible to grow and advance in their organizations without sacrificing their partners’ success, they’ll feel safer opening up about their mobility and flexibility challenges. As a result, their organizations will be able to plan better for the future and make the right kinds of investments in the right people. Everyone will come out ahead. HBR Reprint R1803H

Jennifer Petriglieri is an associate professor of organizational behavior at INSEAD, where she directs the Management Acceleration Programme, the Women Leaders Programme, and the INSEAD Gender Diversity Programme. She is the author of Couples That Work: How Dual-Career Couples Can Thrive in Love and in Work (forthcoming from HBR Press).

RETAINING THE BEST

The Most Desirable Employee Benefits by Kerry Jones

IN TODAY’S hiring market, a generous benefits package is essential for attracting and retaining top talent. According to Glassdoor’s 2015 Employment Confidence Survey, about 60% of people report that benefits and perks are a major factor in considering whether to accept a job offer, and 80% of employees would choose additional benefits over a pay raise. Google is famous for its over-the-top perks, which

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include lunches made by a professional chef, biweekly chair massages, yoga classes, and haircuts. Twitter employees enjoy three catered meals per day, on-site acupuncture, and improv classes. SAS has a college scholarship program for the children of employees. And plenty of smaller companies have received attention for their unusual benefits, such as vacation expense reimbursement and free books.

But what should a business do if it can’t afford Google-sized benefits? You don’t need to break the bank to offer attractive extras. A new survey conducted by my team at Fractl found that, after health insurance, employees place the highest value on benefits that are relatively low cost to employers, such as flexible hours, more paid vacation time, and work-from-home options. Furthermore, we found that certain

benefits can win over some job seekers faced with higherpaying offers that come with fewer additional advantages. As part of our study, we gave 2,000 U.S. workers ages 18 to 81 a list of 17 benefits and asked them how heavily they would weigh the options when deciding between a high-paying job and a lower-paying job with more perks. Better health, dental, and vision insurance topped the list, with 88% of respondents saying that they would give this benefit “some consideration” (34%) or “heavy consideration” (54%) when choosing a job. Health insurance is the most expensive benefit to provide, with an average cost of $6,435 per employee for individual coverage or $18,142 for family coverage. The next most-valued benefits were ones that offer flexibility and improve work-life balance. A majority of respondents reported that flexible

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Quick Takes

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Health insurance and flexible hours might tip job seekers toward a lower-paying job.

hours, more vacation time, more work-from-home options, and unlimited vacation time could help give a lower-paying job an edge over a high-paying job with fewer benefits. Furthermore, flexibility and work-life balance are of utmost importance to a large segment of the workforce: parents. They value flexible hours and work-life balance above salary and health insurance in a potential job, according to a recent survey by FlexJobs. Eighty-eight percent of respondents said they’d give some or heavy consideration to a job offering flexible hours, while 80% would consider a job that lets them work from home. Both flexible hours and workfrom-home arrangements are affordable perks for companies that want to offer appealing benefits but can’t afford an expensive benefits package. Both of these benefits typically cost the employer nothing—and often save money by lowering overhead costs. More vacation time was an appealing perk for 80% of respondents. Paid vacation time is a complicated expense, because it’s not simply the cost of an employee’s salary for the days they are out; liability also plays into the cost. American workers are notoriously bad at

using up their vacation time. Every year Americans leave $224 billion in unused vacation time on the table, which creates a huge liability for employers because they often have to pay out this unused vacation time when employees leave the company. Offering an unlimited time-off policy can be a win-win for employer and employee. (More than two-thirds of our respondents said they would consider a lower-paying job with unlimited vacation.) For

companies $1,898 per employee, according to research from Project: Time Off. And with only 1% to 2% of companies currently using an unlimited time-off policy, according to the Society for Human Resource Management (SHRM), this benefit clearly can make companies more attractive. Contrary to what employers might expect, unlimited time off doesn’t necessarily equal less productive employees and more time out of the office.

example, HR consulting firm Mammoth considers its unlimited time-off policy a success not just for what it does but also for the message it sends about company culture: Employees are treated as individuals who can be trusted to responsibly manage their workload regardless of how many days they take off. Switching to an unlimited time-off policy can solve the liability issue; wiping away the average vacation liability saves

Which Benefits Are Most Valued by Job Seekers? When choosing between a high-paying job and a lower-paying one with better benefits, respondents said health insurance and flexible hours might tip them toward the latter. PERCENTAGE OF RESPONDENTS WHO SAID THE BENEFIT WOULD BE TAKEN INTO CONSIDERATION Heavy consideration Some consideration Better health, dental, and vision insurance More-flexible hours More vacation time Work-from-home options Unlimited vacation Student loan assistance Tuition assistance Paid maternity/paternity leave Free gym membership Free day care services Free fitness/yoga classes Free snacks Free coffee Companywide retreats Weekly free employee outings On-site gym Team-bonding events

88% 88 80 80 68 4 48 44 42 39 38 33 32 30 26 24 2 22 0 20

SOURCE  FRACTL SURVEY OF 2,000 U.S. WORKERS

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A survey from The Creative Group found that only 9% of executives think productivity would decrease significantly if employees used more vacation time. In some cases, under an unlimited time-off policy, employees take the same amount of vacation time. We adopted an unlimited time-off policy at Fractl about a year ago and haven’t seen a negative impact on productivity. Our vice president of client services, Ryan McGonagill, says there hasn’t been a large spike in the amount

of time employees spend out of the office, but the quality of work continues to improve. Student loan and tuition assistance also ranked highly on the list of coveted benefits, with just less than half of respondents reporting that these bonuses could nudge them toward a lower-paying job. A benefits survey from SHRM found that only 3% of companies currently offer student loan assistance, and 52% provide graduate educational assistance. Although educational assistance sounds

costly, companies can take advantage of a tax break; employers can provide up to $5,250 per employee per year for tuition tax-free. Job benefits that don’t directly impact an individual’s lifestyle and finances were the least coveted by survey respondents, such as in-office freebies like food and coffee. Company-sponsored gatherings like team-bonding activities and retreats were low on the list as well. This isn’t to say employees don’t value these benefits, but

Which Benefits Do Men and Women Prefer? When choosing between a high-paying job and a lower-paying one with better benefits, men and women differ in how much various perks might sway them. PERCENTAGE OF RESPONDENTS WHO SAID THE BENEFIT WOULD BE TAKEN INTO HEAVY CONSIDERATION Men Women Better health, dental, and vision insurance More-flexible hours More vacation time Work-from-home options Unlimited vacation Student loan assistance Tuition assistance Paid maternity/paternity leave Free gym membership Free day care services Free fitness/yoga classes Free snacks Free coffee Companywide retreats Weekly free employee outings On-site gym Team-bonding events SOURCE  FRACTL SURVEY OF 2,000 U.S. WORKERS

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these perks probably aren’t important enough on their own to convince a job candidate to choose a company. We noticed gender differences regarding certain benefits. Most notably, women were more likely to prefer family benefits like paid parental leave and free day care services. Parental leave is of high value to female employees: 25% of women said they’d give parental leave heavy consideration when choosing a job (only 14% of men said the same). Men were more likely than women to value team-bonding events, retreats, and free food. Both genders value fitness-related perks, albeit different types. Women are more likely to prefer free fitness and yoga classes, whereas men are more likely to prefer an on-site gym and free gym memberships. Our survey findings suggest that providing the right mix of benefits that are both inexpensive and highly sought after among job seekers can give a competitive edge to businesses that can’t afford high salaries and pricier job perks. Originally published on HBR.org February 15, 2017

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Kerry Jones is the inbound marketing manager at Fractl, where she specializes in content marketing featuring the company’s proprietary research.

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HBR: In what sense is IBM

putting employee experience at the center of people management?

Co-Creating the Employee Experience A conversation with Diane Gherson, IBM’s head of HR

SALLY MONTANA

by Lisa Burrell

GHERSON: Like a lot of other companies, we started with the belief that if people felt great about working with us, our clients would too. That wasn’t a new thought, but it’s certainly one we took very seriously, going back about four or five years. We’ve since seen it borne out. We’ve found that employee engagement explains twothirds of our client experience scores. And if we’re able to increase client satisfaction by five points on an account, we see an extra 20% in revenue, on average. So clearly there’s an impact. That’s the business case for the change. But it has required a shift in mindset. Before, we tended to rely on experts to build our HR programs. Now we bring employees into the design process, co-create with them, and iterate over time so that we meet people’s needs.

get my credit card in time to get to my first meeting,” or “I had problems accessing the internal network.” All those things affect how someone feels about having joined the company. Once you realize that, the remit for the onboarding team becomes how people experience the whole process, end to end. To get it right, you have to work with a broader set of players. You bring in Security to make sure the ID badges are there. You bring in Real Estate to make sure people have a physical space and know where to go. You bring in Networking to make sure their remote access is up and running. All that is part of onboarding. It’s not just having a great meeting with a bunch of other new hires on your first day. It took a while for us to understand that. You have to broaden your scope and stop thinking in silos in order to create a great employee experience.

What does that look like in practice?

How has IBM’s approach to learning and development changed?

A good example is employee onboarding—the first process we took a very hard look at. We knew we wanted people to walk out thinking, “I’m superexcited I’m here, and I understand what I need to know to get going.” But we started too small. We approached it in a traditional way that made it all about the orientation class, all about the experience you have on your first day. Once we began asking new hires how their onboarding had gone, we heard things like “I didn’t get my laptop on time,” or “I couldn’t

People consume content on their phones and tablets now—they use YouTube and TED talks to get up to speed on things they don’t know. So we had to put aside our traditional learning-management system and think differently about education and development. Again, we brought in our Millennials, brought in our users, and codesigned a learning platform that is individually personalized for every one of our 380,000 IBMers. It’s tailored by role, with intelligent recommendations that

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are continually updated. And it’s organized sort of like Netflix, with different channels. You can see how others have rated the various offerings. There’s also a live-chat adviser, who helps learners in the moment. We measure HR offerings such as learning with a Net Promoter Score—the ultimate metric for an irresistible experience. Before, we used a classic five-point satisfaction scale. Even if someone rated you a 3.1, you ended up saying they were satisfied, whereas with Net Promoter, you have to be at the far end of the scale for it to mean anything, because you have to subtract all the detractors. It’s much harder to get that, and it gives you much better feedback on what people are experiencing. For learning, at last count, our NPS was 60. That’s in the “excellent” range, but of course there’s still room to improve.

What kinds of tools do you use to customize learning? With Watson Analytics, we’re able to infer people’s expertise from their digital footprint inside the company, and we compare that with where they should be in their particular job family. The system is cognitive, so it knows you—it has ingested the data about your skills and is able to give you personalized learning recommendations. It tells you, “OK, you need to increase your depth in these areas—and here are the offerings that will help you do that.” You can then pin those or queue them up in your calendar for future learning. The system also looks at how close you may be to earning a digital badge, which we’ve started using in just the past couple of

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years to demonstrate which employees have applied skills. The tool then helps you achieve the badge by recommending specific webinars and internal and external courses. It’s all based on artificial intelligence. Skills inference is at about 96% accuracy at this point.

“People are much less likely to resist the change when they’ve had a hand in shaping it.”

How do you know that? We used to have this laborious manual process of getting people to fill out skills questionnaires and having their managers sign off on them. But that gets outdated really fast. So we stopped doing that. Instead, leaders in particular job families or industries do spot checks on how well we are inferring. They interview employees and identify where they are, comparing that with what the inference was in our system.

IBM has given its performance management system an overhaul as well. How have employees been involved in that process? As you know, performance management is kind of a lightning rod in most companies. Rather than do the typical thing—which would be to do some benchmarking, pull together a bunch of experts, come up with a new design, and pilot it—we decided to go all out and co-create it with our employees in a sort of

extended hackathon. We used design thinking and came up with what you might describe as a “concept car”—something for people to test drive and kick the tires on, instead of just dealing with concepts. We did that in the summer of 2015 and implemented it across the company five months later. That’s the power of engaging the whole workforce—people are much less likely to resist the change when they’ve had a hand in shaping it. To start the co-creation process, I blogged about it one day and said, “We’d love your input. If you hate it, we’ll start over, no problem. But we really want your thoughts.” We made a few videos about what we thought it might look like. I got 18,000 responses overnight. Fortunately, we had the technology to analyze it all and see what people liked and didn’t like. At first some people said, “This is such a sham—you already know what you want to do.” But we explained that we really wanted to hear from them, and we got them into various discussion forums. It took a while, but I think we did turn them around. We kept communicating, saying, “OK, you liked this; you didn’t like that. And here are areas where you can’t seem to agree.” Meanwhile, we were putting together prototypes to show people. I was clear up front that there were some ground rules. For example, we were not going to get rid of performance discussions, and we wanted pay-for-performance. But in general, it was wide open. The whole process took less time

than most companies take to redesign their performance management programs, and we involved about 100,000 employees. Finally, we asked, “What do you want to call it?” Tens of thousands of people voted. We had three names in the end, and Checkpoint was selected. Performance management can never be perfect. But your baby is never ugly. Our employees created their own program, and there is pride in that. You can see it in their ongoing blogs, where we ask them to talk about what’s working and what’s not and to tell us how we can improve the system. We’ve been doing that ever since we put it out there. Their overall message has been “This is what we wanted.” It was cited as the top reason engagement improved. People are getting much more feedback out of this system, in much richer ways. And more important, they are not feeling like spectators in our transformation; they are active participants.

How are you using “sentiment analysis” to further address employees’ needs? Sentiment analysis is very helpful in a world where people are always commenting online. Our cognitive technology looks at the words people choose and picks up the tone. It identifies whether it’s positive or negative and then goes deeper, saying whether it’s strongly positive or strongly negative. In that way it’s almost like looking at music—seeing where there are very high notes or very low notes that are loud. It’s always

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behind our firewall, never external. It’s not looking at any of the information people pass around or at their email content or browsing behavior. It’s just looking at tone in their blogs and comments inside the firewall. With this approach you can pick up pretty quickly if there’s an area you need to dive into. We’ve been able to swiftly detect problems that are starting to brew and, more important, make a commitment to do something about them. This is the most exciting part of having a social platform to work with. We’ve had several examples of things we did wrong. Some of my folks decided we wouldn’t reimburse for ridesharing. Employees became agitated, and I could quickly respond to a concern that had turned into a petition. “I read all your comments,” I told them, “and you made some great points we hadn’t thought of. We were trying to look out for your security, but on balance, this wasn’t the right choice. Let’s return to our original policy.” All this happened within 24 hours. People felt listened to and were very appreciative. We had a similar situation about a year ago. We had to impute income when you were traveling to a client site for a full week and, instead of returning home right away, you had your spouse or a friend join you for the weekend. Because we would reimburse the guest’s travel, it created a tax issue. We altered the program because that was getting messy, and again employees were incensed. I can certainly understand why. If you’re on the road all the time, of course you might want your spouse to join you for a

weekend. People didn’t want us making the decision for them. That was another case where we quickly got together and said, “Hey, if they want to be responsible for their own taxes, they can do it.” It was a good wake-up call for us to not be so paternalistic. In organizations where people aren’t physically all together, you can use sentiment analysis to get a sense of where you’ve got trouble spots, where your management isn’t strong enough, where groups of people are expressing negative opinions. It allows you to check in on those sites or groups and find out what’s going on.

“We’ve been able to swiftly detect problems and commit to doing something about them.”

Do employees have more power now than in the past? Yes. So much more weight is now given to what is said inside an organization, because it can be heard outside as well, through social media. Glassdoor is a perfect example. In the past you might have had companies that weren’t great to work for, but only a small circle of people knew about it. Now the whole world knows about it, because it’s on Glassdoor—and that’s turned companies into glass houses. People can look in and see what’s going on and make judgments about whether they want to work there in a way that they weren’t able to before.

Let’s go back to the business reasons behind IBM’s shift to agile talent practices—can you say more about those? I mentioned client satisfaction. Clients today are looking for speed and responsiveness like never before. In an earlier era what they really wanted was the best product at the best price— efficiency was important, but speed was less so. In the early 2000s we would have staffed a project with experts from all over the world, and they would have spent a fraction of their time on that project, because they were also working on other projects. They would have joined conference calls, which is always hard because people are in different time zones. And I’m sure they were multitasking while they were on those calls. That project might have taken six months to a year. Now we would take a smaller group of dedicated people and put them together for three months, and they would get it all done using agile methodology. It’s a different way of thinking about how to create value for clients. It responds to their need for speed.

of your legacy businesses, and you’re renovating those while you’re launching new businesses, you may see some unevenness in performance. You’re basically changing the tires while you’re driving the car. And yes, that takes agility. Originally published in Harvard Business Review March–April 2018

HBR Reprint R1802B Lisa Burrell is a senior editor at HBR.

Is there some hope that an agile approach to talent will help IBM make up ground in revenue and growth that it lost in its transition to cloud computing and other businesses? We’re a company that’s transforming itself: 45% of our revenue comes from businesses we were not in five years ago, and we are an $80 billion company. When you’re going through that kind of shift and seeing a downturn in some

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HBR Special Issue 95

RETAINING THE BEST QUICK TAKES

by Daisy Wademan Dowling

YOU’RE A LEADER with ambitious goals for yourself and your team in 2019. The plan is set; the performance, growth, and efficiency targets committed to. But, to be fully prepared for the year, one issue should be at the top of your priority list: the Working Parent Problem. This is a new, simple label we can use to describe the sometimes overwhelming challenge of trying to earn a living and build a career while also parenting well. For organizations and leaders, it refers to the challenge of effectively employing and fully unleashing the potential of the folks who are navigating the demands of work and family. If you’ve thought about the Problem before as a manager, it’s probably been under a different, hazier label (“work-life balance” or “integration”), and potential solutions may have seemed like a nebulous, elective effort; there was no clear path or upside to getting involved. Even if you’ve directly confronted the Problem in the past—for example, a star performer suddenly decided to stay home at the end of a parental leave—the

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issue probably still felt adjacent to your core business goals, a relatively small and inevitable cost of doing business. But it isn’t anymore. In the current economic and cultural landscape, the Working Parent Problem has moved up to the forefront of leadership concerns, and it’s going to stay there. Ignored, it can become a powerful and insidious threat to your team’s and organization’s success. Here’s why focusing on working parents is so important:

The demographic is huge. Let’s look at the cold hard data: In the United States, the civilian workforce ages 25 to 54 is 102 million people, and there are 52 million working parents, according to the Department of Labor. It’s therefore possible—probable, even—that 50% or more of your new-product sales team, or line managers, or clinical care providers, or the candidates for that specialty role you’ve been recruiting for and that’s proving impossible to fill, are trying to be committed professionals while also raising their kids in a present and loving way. At the same time, unem-

The struggle is arguably more difficult today than in past decades. Not only is the sheer number of working parents large and growing, but those men and women also carry much heavier loads than previous generations have. Today’s working parents are three times more likely, on average, to be part of dual-career couples or to be single than they are to have spouses at home full-time. That means the majority of committed working-parent employees have no slack in their system: no one to whom they can hand off the school pickup or pediatrician visit or 10 PM feeding. And as wonderful as many technological changes are, some have also made working parenthood harder: iPhone in hand, there’s no reason, or excuse, to ever be “off” work, even during the parent-teacher conference or family dinner. Translation: Being a working parent isn’t a marginal or occasional concern for mothers and fathers on your team; it’s one of the central challenges of their lives, and they grapple with it daily.

More working parents care more—and may vote with their feet. Several recent studies indicate that for working parents, flexibility and work-life balance trump every other career decision-making criteria— including pay. And research shows that men, historically less engaged in childcare and other child-related activities, are becoming increasingly committed to it: Today’s dads overwhelmingly report wanting to be present and on the job at home. They’re becoming increasingly willing to make serious career choices around it, too. So working parenthood isn’t a “women’s thing” anymore—it’s a universal concern driving whether people join or stay with your organization. It’s a bellwether. How you treat working parents is an indicator of how you treat talent in general, especially in the eyes of prospective or more-junior employees. Does the Career sections of your corporate website include information about family-related policies? If not, candidates—whether they have kids or not—may quickly move on to other sites and job opportunities that appear more parent-friendly. And if upand-coming stars with young children are leaving your team or organization to stay home, or accepting jobs where it seems more feasible to combine work and family, their younger colleagues (folks who aren’t part of that 52 million yet but want to be someday) will notice and start wondering if they’ve found the right place to build their long-term careers. Bottom line: Without a good approach to working parenthood that you’re willing to

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Your Company Needs a Better Retention Plan for Working Parents

ployment rates are at nearrecord lows. So, if you’re having serious trouble finding the talent you need, it’s probably time to focus on how you can attract this huge pool of working mothers and fathers, retain them, and ensure they deliver at work. Although I’ve used the United States as an example here, data on the growing ranks of professionals with children in other countries is also eye-opening. (In England alone, there are one million more working mothers now than 20 years ago.) In today’s war for talent, working parenthood isn’t a skirmish—it’s a major, central battle.

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showcase publicly and some visible examples of moms and dads succeeding in your organization, you’ll have a hard time developing a reputation as a great boss or convincing people that your company is “a great place to work.”

The issue pervades our public dialogue. Scan the headlines or type the term “working parent” into your browser, and you’ll find a deluge of articles, commentary, and opinion generated in the past two to three years—all underscoring the immediacy and scope of the Working Parent Problem. It’s certainly top of mind for anyone directly affected by it, and increasingly for people who aren’t, and will quite likely stay in that spotlight for the foreseeable future. If you’re a senior leader who hasn’t yet gotten a question about the issue from a reporter, investor, or board member in front of a crowd, or from a star performer during a mentoring conversation, you probably will soon. You don’t want to get caught without a thoughtful stance on a hot-button topic that affects so many people.

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External help probably isn’t on the way—at least, not anytime soon. Yes, there has been a lot of discussion recently in the United States and other countries about working-parentfriendly legislation, including paid and extended parental leaves. While those types of laws could eventually be helpful for parents and for organizations, they may not pass or pass as proposed, and they could be delayed for years. To be effective, your talent strategy has to be based on the here and now, not on the “maybes” of the future.

So what exactly does a strong, feasible strategy look like? And how, in the face of this large, complex challenge, can individual leaders take charge and make an impact? In my consulting work, I’ve advised executives and organizations of all sizes and types in various industries to focus on six key things: 1. Demonstrate personal support for working-parent employees in a highly visible way. 2. Define your organization’s working-parent challenge from the frontline employee perspective, through both a quantitative and a qualitative lens. 3. Engage allies within and outside the HR team to identify and execute on solutions. 4. Take a comprehensive approach rather than relying on silver bullet solutions. 5. Support—and help shape—grassroots, employeeled solutions, such as peer-topeer working-parent mentoring programs or employee resource groups (ERGs). 6. Outcommunicate the competition when it comes to working-parent matters. Ultimately, every leader and organization will find different ways to solve the Working Parent Problem. But, as with any challenge, acknowledging its reality, size, and nature is always the right place to start. Originally published on HBR.org February 1, 2019

HBR Reprint H04RHK Daisy Wademan Dowling is the founder and CEO of Workparent, a consulting firm that provides practical, commercial advice, solutions, and training to working parents and to the organizations that employ them. She also works as a coach, consultant, and adviser to organizations seeking to drive performance through their people.

Why I Encourage My Best Employees to Consider Outside Job Offers by Ryan Bonnici

EVERY DAY we get new reminders of just how tough the war for talent can be. It isn’t enough to attract the greatest employees—you have to retain them. That’s become a bigger challenge with job-hopping on the rise. One survey found that 64% of workers, and 75% of those younger than age 34, believe frequently switching jobs will benefit their careers. Why, then, would I actively encourage even my best employees to pursue outside job offers? The answer is simple,

if counterintuitive: It helps the business succeed. In my last job as senior director at HubSpot, and now as CMO of G2, I’ve not only encouraged my employees to look elsewhere but also told them that I keep an eye out for potential new jobs for myself as well. Ironically, all this helps me win—and quite often keep—terrific employees. Here’s why.

Employees want development, not lip service. Today’s employees, especially Millennials, “want jobs to be develop-

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ment opportunities,” Gallup explains. Eighty-seven percent of Millennials and 69% of nonMillennials rate “professional or career growth and development opportunities” as important. But many businesses are failing on this front. Less than half the Millennials surveyed by Gallup strongly agreed that they’d had opportunities to learn and grow in the previous year. And only one-third said their most recent learning opportunity was “well worth” their time. So while almost every company promises to develop its employees, all too often that’s just lip service. And it’s up to managers to ensure their companies live up to the promises of professional development. As executive coach Monique Valcour wrote in “If You’re Not Helping People Develop, You’re Not Management Material” (HBR, 2014), the “manageremployee dyad is the new building block of learning and development in firms.” When I make clear to my employees that I want them to consider all options for their careers, they see that I’m genuinely committed to helping them learn and grow. If I think they’ve gotten to the top of their learning curve on my team, and I can’t figure out a way to help them grow, I will support their efforts to get a job somewhere else. As research has found, employees often quit not because of their company but because of their manager. They stay for a manager they believe in— one who wants to help them achieve their goals. I’ve had employees tell me they chose to work for me, and chose to stay, because of that commitment.

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Openness allows conversations to thrive. By encouraging my employees to consider outside possibilities and sharing my stories with them, I foster a culture of openness in our communication. When they get outside offers, that communication makes a big difference. As LinkedIn founder Reid Hoffman wrote in “Encourage Your Employees to Talk About Offers” (HBR, 2014), employees often feel they can’t speak honestly with their managers about their career goals “because of the reasonable belief that doing so is risky and career-limiting if the employee’s aspirations do not perfectly match up with the manager’s existing views and time horizons.” So they don’t share information about outside offers until they’ve gone “far down the road” with the potential new employer.

When great employees decide to leave on good terms, there can be upsides for the company.

By showing my team that I want to support them either way, I am creating a culture in which my employees feel comfortable sharing every career step with me. This open dialogue gives me the time and opportunity to find a way to keep them. Often, there’s something I can do—such as get them a new experience or project, add to their responsibilities, or negotiate a raise. I’ve found that most employees don’t realize how much flexibility

a company has when it comes to finding a way to retain highperforming talent. This process also makes them feel respected. As Christine Porath and Tony Schwartz found in an HBR survey they conducted in 2013, half of employees don’t feel respected by their bosses. Those who do are more likely to stay.

There are benefits to their leaving. This may be the most counterintuitive point of all. But when great employees decide to leave on good terms, there can be an upside for the company. Out in the world, they’ll be in a powerful position to speak honestly about their experiences. If they leave our company feeling good about us, they’ll speak positively about the brand. If they feel good about me, they’ll encourage great people to come work for me. This is why, once it’s become clear that there’s no way I can keep them, I offer advice to help my staff negotiate the best deal they can get at their new employer. Every employee is unique. So it’s true that not everyone is entirely replaceable. But when someone leaves, it is an opportunity for me to bring in someone else with different strengths and new things to offer the team.

They’re more likely to return. Not every new venture works out. Some employees leave to try their hand at startups, which have a high failure rate. Others work at new companies only to find that the job isn’t what they expected or the culture isn’t the right fit. So these great employees may be looking for work again

someday—and you want your company to be at the top of their list. These so-called boomerang employees are on the rise and “will be an increasingly valuable source of talent,” Tammy Erickson has noted (see “Never Say Goodbye to a Great Employee” below). So a goodbye party for an employee may turn out to have been a “farewell for now.” If you can help that employee feel that the place he or she is leaving is something of a work “home,” he or she just might return. Of course, there’s no “one size fits all” way to handle employee relationships. People have different styles and different comfort zones for communication. And businesses have different hiring and recruiting strategies depending on their company cultures. No matter what I do, some employees will choose to be more secretive and to keep their outside opportunities closer to the vest. That’s OK. As long as I make clear that my door is open, and that while they’re wanted at our company, we won’t try to trap them here, we build a culture of employee empowerment. And no matter where they end up next, if they become hiring managers, I want them to have learned valuable lessons about giving their own employees this same freedom and encouragement. This is how we build stronger work cultures. Originally published on HBR.org September 11, 2018

HBR Reprint H04J1B Ryan Bonnici is the chief marketing officer of G2.

HBR.ORG

Never Say Goodbye to a Great Employee by Tammy Erickson

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SO-CALLED BOOMERANG employees—those who leave and then return—will become an increasingly valuable source of talent over the years ahead. Perhaps the most frequently discussed example is women who chose to off-ramp for several years sometime in their career and are now eager to return to work. Older workers may present boomerang possibilities as well. Sixty percent of workers ages 60 and older say they will look for a new job after they retire, possibly back in your organization. But it would be a mistake to focus only on these two groups; there are also those who left initially due to personal issues, other job opportunities, or even a round of layoffs. Former employees, of course, offer many advantages: They are familiar with your operations and culture, know many of your current employees and clients, and may require little or no training to start making contributions. Often they are

cheaper to hire, particularly if a former manager has maintained contact while the employee is away. So how do you make it so that these boomerang employees actually want to return to your company? The biggest challenge to leveraging boomerang talent for most organizations is the nature of the “out” process itself. For most of us, departures, whether initiated by the employee or the company, are negative events weighed down with feelings of guilt and failure, often on both sides. This negativity occurs because conventional “outs” are shaped by the expectations we convey about the relationship from the beginning—that we want unconditional loyalty and that it will be rewarded (perhaps “wink, wink”) with a steady career and comfortable retirement. When these expectations are not borne out, due to either party’s initiative, bad feelings are the inevitable result.

Setting the stage for positive exits and creating the possibility of happy returns requires redefining the relationship from the beginning—setting different expectations during the hiring process. Today more than 25% of the working population goes through career transitions every year, and half of all hourly workers leave new jobs within the first 120 days, according to research conducted by Talya N. Bauer of SHRM Foundation; clearly the “employee for life” model has run its course. Rather than implying that you expect indefinite tenure and unconditional loyalty, ask for the employee’s full discretionary effort for the time he or she will be here. And instead of signaling that you will provide opportunities for life (something few hires actually trust anyway), make it clear that you are offering interesting and challenging work, coupled with fair arrangements, while it is available. Reducing the implied promise of long-term protection and care sets the expectation that departures will naturally occur when that interesting and challenging work comes to an end. It conveys the expectation that departures can be mutually positive and facilitates multiple employment stints (off-ramps, on-ramps, boomerangs, and retiree returns) as the company’s workload warrants. This philosophy focuses on matching relevant skills and capabilities in the moment and recognizes, where appropriate, the legitimacy of concurrent employment arrangements. Creating an environment that leverages the power of positive “outs” is greatly enhanced by

forward-thinking work arrangements that let people connect and reconnect with your organization in a variety of ways. For example: Flexible time: flexible shifts, compressed workweeks, and individualized work schedules Reduced time: part-time options, job sharing, selfscheduling, leave-of-absence programs, and cyclic or projectbased work Flexible place: mobile work and telecommuting Tasks, not time: requirements to put in only as much time as it actually takes to get the work done, removing restrictions around a prescribed time or place Decelerating roles: career path options that go “down” (to lower levels of responsibility) In addition to setting the right tone at the beginning, structure the exit process to facilitate reentry, and build a flexible network of talent possibilities. Invite them to join your network, build your own flexible talent pool, and create a residual knowledge bank. Regardless of whether a person’s departure is voluntary or involuntary, it’s never wise to say goodbye to a good employee. Originally published on HBR.org December 19, 2013

HBR Reprint H00L7A Tamara J. Erickson is the author of Retire Retirement: Career Strategies for the Boomer Generation (Harvard Business Press, 2008), Plugged In: The Generation Y Guide to Thriving at Work (Harvard Business Press, 2008), and What’s Next, Gen X? Keeping Up, Moving Ahead, and Getting the Career You Want (Harvard Business Press, 2009). Erickson was named one of the top 50 global business thinkers for 2011.

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HBR Special Issue 99

UNDERSTANDING THE GIG ECONOMY

Thriving in the Gig Economy How successful freelancers manage the uncertainty by Gianpiero Petriglieri, Susan Ashford, and Amy Wrzesniewski

H Originally published in March–April 2018

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AVE YOU EVER been on a

trapeze?” That’s how Martha, an independent consultant, responded when we asked her to describe her work in the five years since she’d left a global consulting firm to set out on her own. She had recently tried the art, which she saw as a good metaphor for her life: the void she felt when between assignments; the exhilaration of landing the next engagement; the discipline, concentration, and grace that mastering her profession required. Trapeze artists seem to take huge risks, she explained, but a safety system—including nets, equipment, and fellow performers—supports them: “They appear to be on their own, but they’re not.”

ILLUSTRATION BY JOANNA ŁAWNICZAK

UNDERSTANDING THE GIG ECONOMY THRIVING IN THE GIG ECONOMY

Martha (whose name, like others in this article, has been changed) is part of a burgeoning segment of the workforce loosely known as the gig economy. Approximately 150 million workers in North America and Western Europe have left the relatively stable confines of organizational life— sometimes by choice, sometimes not—to work as independent contractors. Some of this growth reflects the emergence of ride-hailing and taskoriented service platforms, but a recent report by McKinsey found that knowledge-intensive industries and creative occupations are the largest and fastest-growing segments of the freelance economy. To learn what it takes to be successful in independent work, we recently completed an in-depth study of 65 gig workers. We found remarkably similar sentiments across generations and occupations: All those we studied acknowledged that they felt a host of personal, social, and economic anxieties without the cover and support of a traditional employer—but they also claimed that their independence was a choice and that they would not give up the benefits that came with it. Although they worried about unpredictable schedules and finances, they also felt they had mustered more courage and were leading richer lives than their corporate counterparts. We discovered that the most effective independent workers navigate this tension with common strategies. They cultivate four types of connections—to place, routines, purpose, and people—that help them endure the emotional ups and downs of their work and gain energy and inspiration from their freedom. As the gig economy grows worldwide, these strategies are increasingly relevant. Indeed, we believe they may also be helpful to any corporate employees who are working more autonomously, from

home or a remote office, or who feel they might one day want—or need—to jump into a freelance career.

Produce or Perish The first thing we realized when we began interviewing independent consultants and artists was that the stakes of independent work are enormously high—not just financially but also existentially. Unshackled from managers and corporate norms, people can choose assignments that make the most of their talents and reflect their true interests. They feel ownership over what they produce and over their entire professional lives. One study participant told us, “I can be the most I’ve ever been myself in any job.” However, the price of such freedom is a precariousness that seems not to subside over time. Even the most successful, well-established people we interviewed still worry about money and reputation and sometimes feel that their identity is at stake. You can’t keep calling yourself a consultant, for example, if clients stop asking for your services. A well-published writer told us, “You become your work. If you write a good book…it’s really great, and when you don’t achieve it, you have to accept…that failure might define who you are to yourself.” An artist agreed: “There’s no arriving. That’s a myth.” For this reason, productivity is an intense preoccupation for everyone we interviewed. It provides self-expression and an antidote to precariousness. Interestingly, however, the people we talked with aren’t just focusing on getting things done and sold. They care about both being at work—having the discipline to regularly generate products or services that find a market—and being into their work: having the

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Idea in Brief courage to stay fully invested in the process and output of that labor. Sustaining productivity is a constant struggle. Distress and distractions can erode it, and both impediments abound in people’s working lives. One executive coach gave a poignant description of an unproductive day: “It’s when there is so much to do that I’m disorganized and can’t get my act together. [In the evening,] the same e-mails I opened in the morning are still open. The documents I wanted to get done are not done. I got distracted and feel like I wasted time.” A day like that, he said, leaves him full of self-doubt. When we asked interviewees the secret to getting through such days and ultimately sustaining productivity as they defined it, we discovered a paradox at the heart of their answers. They all want to preserve their independence and, in many cases, even their unsettledness (which one consultant described as the key to continued learning and “keeping my edge”), but they also spend a great deal of time developing a “holding environment”—a physical, social, and psychological space for their work. This concept—first used by the British psychoanalyst Donald Winnicott to describe how attentive caregivers facilitate children’s development by buffering them against distress and creating room for experimentation—has since been employed in the field of adult development to refer to conditions in which people can be their best and grow. Corporate employees, of course, can find them with a good boss in a solid organization. But for independent workers, a holding environment is less a gift than an accomplishment; it must be cultivated, and it can be lost. So they create these environments for themselves by establishing and maintaining what we call “liberating connections”—because they both free people up to be individually creative and bind them to work so that their output doesn’t wane.

The Four Connections Place. Disconnected from a corporate office, the people we interviewed find places to work that protect them from outside distractions and pressures and help them avoid feeling rootless. Though many claimed their work was portable, they all still seemed to have somewhere to

retreat. One writer told us, “People fail because they don’t create a space and time to do whatever it is they need to do.” We visited many of these spaces in person and noticed several similarities among them. They feel confined—almost uncomfortably so in the case of some artists. They are used consistently for all substantive work. They allow easy access to the tools of the owner’s trade and to little else. And they’re dedicated to work; people usually leave them once their daily tasks are done. One software engineer, whose home office has all these features, described it as a “fighter pilot cockpit,” where everything he needs is within arm’s reach. “Sometimes it’s claustrophobic,” he explained, but “when I’m there, the open space is in my mind.” Despite these commonalities, each workspace is also unique, with a location, furniture, supplies, and decorations that reflect the idiosyncrasy of its owner’s work. These places are not just protective cocoons for the working self—they evoke it, too. Karla, an independent consultant who initially told us she could do work “wherever I show up and am doing something that has positive impact in the world,” eventually admitted that her home office is where she goes to avoid distraction and find inspiration, literally surrounded by her current and potential projects, arranged in visible and accessible piles. “When I walk through that door, I step into a space that embraces all the different aspects of myself,” she told us. “I feel at home in there.” Without that place and the space it gives her, Karla explained, she would probably be too sensitive to external demands and thus less focused and free. Routines. In organizations, routines are often associated with safety or boring bureaucracy. However, a growing body of research has shown that elite athletes, scientific geniuses, popular artists, and even everyday workers use routines to enhance focus and performance. The professionals we spoke with tend to rely on them in the same way. Some routines improve people’s workflow: keeping a schedule; following a to-do list; beginning the day with the most challenging work or with a client call; leaving a sentence incomplete in an unfinished manuscript to make an easy start the next day; sweeping the studio floor while reflecting on a new piece. Other routines, usually involving sleep, meditation, nutrition, or

THE SHIFT A growing segment of the workforce, known as the gig economy, is forgoing the relatively stable confines of organizational life for the freedom and ownership of independent work. But the price of such liberty is a precariousness that doesn’t wane.

MAKING A SPACE To combat instability and sustain productivity, successful independent contractors develop a “holding environment” for themselves, establishing connections to place, routines, purpose, and people that help them endure the emotional turbulence of their work and gain energy from their autonomy.

FINDING BALANCE These strategies both liberate people to be creative and bind them to work so that they continue to produce. Freelancers find their success in the balance between predictability and possibility, between the promise of continued work—and feeling present, authentic, and alive in it.

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People in the gig economy must pursue a different kind of success—one that comes from finding a balance between predictability and possibility, between viability and vitality.

exercise, incorporate personal care into people’s working lives. Both kinds often have a ritual element that enhances people’s sense of order and control in uncertain circumstances. One consultant we interviewed takes a bath every morning and visualizes what she wants to accomplish while she soaks. Another consultant, Matthew, who specializes in helping boards focus on innovation, keeps a strict daily schedule: “I’m up at 6:00 and there’s exercise. I pack my wife’s lunch. We pray. She’s out the door around 8:00. I’m in my office by 8:30, and I do work where there’s deeper thought required—design or writing—in the morning. That’s when I’m at my best. Then in the afternoon I schedule phone calls, more of the business or financial things that need to be done.” This discipline even extends to his wardrobe: “I always get dressed for the office. Most days in summer I wear shorts when I’m not on the road, but still I shower and shave as if I were going to a workplace separate from home.” That may sound rigid, but it helps Matthew pour himself into his work. He and other successful independent workers seem to follow the advice of the French novelist Gustave Flaubert: “Be regular and orderly in your life…so that you may be violent and original in your work.” Purpose. For most people in our study, striking out on their own initially involved doing whatever work would allow them to find a footing in the market. But they were adamant that succeeding means taking only work that clearly connects to a broader purpose. All could articulate why their work, or at least their best work—be it to empower women through film, expose harmful marketing practices, sustain the American folk music tradition, or help corporate

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leaders succeed with integrity—is more than a means of earning a living. Purpose creates a bridge between their personal interests and motivations and a need in the world. Matthew, for example, said that although at first he felt “a certain desperation around having clients and making an income,” over time his view of success shifted “to one that is a lot about living a life of service to others and making the planet a better place.” An executive coach we interviewed told us that purpose keeps her steady, inspired, and inspiring. “A big distinction between successful independents and the ones who aren’t or go back [to corporate jobs] is getting to that place of knowing what you’re meant to do. That gives me resilience for the ups and downs. It gives me the strength to decline work that isn’t in alignment. It gives me a quality of authenticity and confidence that clients are drawn to. It’s helpful to building or maintaining the business and serving the people I am here to serve.” We found that purpose, like the other connections, both binds and frees people by orienting and elevating their work. People. Humans are social creatures. Studies in corporate settings have long demonstrated how important other people are to our careers— as role models who show us who we might become, and as peers who help us progress by sharing our path. Researchers have also warned about a “loneliness epidemic” hitting the workplace, for which independent workers can certainly be at even greater risk. But those we interviewed are keenly aware of the dangers of social isolation and strive to avoid it. Though many are ambivalent about formal peer groups, which they often see as insipid

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substitutes for collegiality, all reported having people they turn to for reassurance and encouragement. Sometimes these are direct role models or supportive collaborators; in other cases they’re family members, friends, or contacts in similar fields, who can’t always offer specific work advice but nevertheless help our study participants push through challenging times and embolden them to take the risks their work entails. Matthew, for example, noted that reaching out to people in his inner circle helps calm his anxiety: “If I were just left on my own, I could sit here in the office and go down a rat hole. You’re left to your own inner voice, and it spirals down into ruminating.” Karla told us that she, too, regularly turns to a handful of peers with whom she’s close. “All the work I do in the independent economy comes through these connections,” she said. But their help goes well beyond referrals. “My ability to process, develop, and grow as a human being and understand who I am in the work I’m doing comes from the conversations that I have with these folks,” she explained. “These people are how I know what I’m supposed to be doing.”

Redefining Success In popular management tales, career success usually comes with security and equanimity. For independent workers, however, both are ultimately elusive. And yet most of those we studied told us they feel successful. Our conclusion is that people in the gig economy must pursue a different kind of success— one that comes from finding a balance between predictability and possibility, between viability (the promise of continued work) and vitality (feeling present, authentic, and alive in one’s work). Those we interviewed do so by building holding environments around place, routines, purpose, and people, which help them sustain productivity, endure their anxieties, and even turn those feelings into sources of creativity and growth. “There’s a sense of confidence that comes from a career as a self-employed person,” one consultant told us. “You can feel that no matter how bad it gets, I can overcome this. I can change it. I can operate more from a place of choice as opposed to a place of need.” Many we spoke to believe they wouldn’t be able to find the same mental space or strength in

a traditional workplace. Martha, the consultant who compared herself to a trapeze artist, recalled that she became “much more successful professionally” and “much more comfortable in my identity personally” when a trusted counselor helped her reframe—and own—her struggle, rather than seek ways to evade it. “She helped me understand that I could think of myself, which I now do, as a pioneer. I don’t fit in any categories that exist in organizations, and it’s more effective for me to be independent.” Seen this way, discomfort and uncertainty were not just tolerable but affirming—signs that she was just where she needed to be. When we spoke, she portrayed employment as no longer an anchor she missed but a shackle she’d been fortunate enough to break. “I don’t know that I would frame [my new life] as precariousness anymore,” she concluded. “I would frame it as really living.” HBR Reprint R1802M

Gianpiero Petriglieri is an associate professor of organizational behavior at INSEAD. Susan Ashford is the Michael & Susan Jandernoa Professor of Management and Organizations at the University of Michigan. Amy Wrzesniewski is the Michael H. Jordan Professor of Management at Yale University.

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Quick Takes Gig work is growing, but not as much as you might think.

growing economy that’s offering more full-time employment, but it also shows a generation that may want the same thing as their parents: a steady job with a clear advancement track and benefits such as health insurance and paid time off.

Myths of the Gig Economy, Corrected by David Jolley

EVERY DAY there are news stories about the so-called gig economy where workers contribute part- or full-time labor— not as employees with benefits but as independent contractors. Dara Khosrowshahi, CEO of the ride-sharing giant Uber, proudly declared last year that “very few brands become verbs.” The same week Upwork, a platform for hiring freelancers, filed for an IPO, as did Fiverr, which

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boasts that it offers a “freelance services marketplace for the lean entrepreneur.” In fact, the gig economy has not only turned millions of Americans into contractors but given the more successful entrepreneurs the tools to grow even faster. A fast-moving start-up can secure talent as it needs it, outsource more-quotidian tasks like payroll, and stay lean and mean; indeed, I see entrepreneurs

employ this approach through my work at EY supporting creative, successful start-ups. But there are a lot of myths about gig work, whether fulltime or part-time. Gig work is growing, but not as much as you might think, and in ways that may be very different from what you imagine. It might even be better for older executives than recent grads. Here are a few myths worth dispelling. Millennials love to gig. There is a common perception that somehow the Millennial generation (those born between 1981 and 1996) just loves part-time gig employment. But a recent study by EY found a more complicated picture: 60% of Millennials were not involved in the gig economy at all, and only 24% report earning money from it. In fact, the percentage of Millennials with full-time careers is rising at a brisk clip from 45% in 2016 to 66% in 2018, according to the data we collected. That reflects a

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We’re all going to be giggers. The size of the gig economy and how fast it’s growing also seem to be overimagined at times. The measurements can vary a lot, and so can the predictions for how much it may expand. Back in 2013 a much-touted survey suggested that by 2020— just over a year from now—a whopping 40% of the workforce would be so-called contingent workers, including contractors, temps, and the self-employed. But here are the facts: The best estimates, according to the Gig Economy Data Hub, a joint project of Cornell University’s Institute of Labor Relations and the Aspen Institute, put the percentage at around 30%. That’s a lot, and it’s growing. But don’t think the world as you know it is completely disappearing. Only about 10% of workers rely on gig arrangements for their full-time jobs. And ondemand services, where you get constant gigs from an app like Lyft or Task Rabbit, represent an even smaller percentage of gig workers. In fact, less than 1% of workers have used online platforms to arrange work in the past month. Most workers are still grabbing extra hours the old-fashioned way—tending bar or doing temp work on

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the side—not by being digitally summoned. Gig work is better. In our 2018 EY Growth Barometer, an annual global survey of middle market company leaders, we found some movement away from part-time and gig hiring. Most companies are still committed to full-time hires for all the advantages that bestows— loyalty, retained knowledge, institutional memory, stealing top talent from the competition. In many cases, you have jobs in which the worker is integral to a team or needs to be supervised. That’s why so many entrepreneurs use the gig economy where they can but also have a deep and abiding interest in hiring great full-time talent. Gig-based businesses can’t transmit “a culture” in a traditional sense. “You have individuals doing things you have no supervision of, other than the work itself,” says D. Quinn Mills, the Albert J. Weatherhead, Jr. Professor of Business Administration Emeritus at Harvard Business School. Mills notes that while the gig economy can benefit companies and will most likely expand, it’s not for every business. Gig work is unfulfilling. The perception is that gig jobs are dead-end jobs. Not true. Consider Jody Greenstone Miller, who has had a stunning career in places ranging from the White House to The Walt Disney Company. The Los Angeles lawyer–turned–entrepreneur is the cofounder and CEO of Business Talent Group, which pairs high-end talent with high-end expertise in areas such as finance, operations, and mergers and acquisitions at companies including Pfizer,

Kraft, and Mastercard. Miller says that her stable of top talent wants “to be able to choose who we work with and what we work on.” This lines up with EY’s recent findings. On a global basis, according to our 2018 Growth Barometer, a lack of skilled talent is a bigger headache for U.S. companies than for those in other countries, with 25% of U.S. survey respondents citing this as a challenge to growth compared with 10% of their counterparts elsewhere. With U.S. unemployment at a historic 40-year low, there just aren’t the numbers of suitably qualified people in the talent pool to hire. Lisa Hufford, a consultant and the author of Navigating the Talent Shift: How to Build On-Demand Teams That Drive Innovation, Control Costs, and Get Results (Palgrave Macmillan, 2016), has worked with gig talent for years. She’s seeing firsthand that while the gig economy isn’t the answer to all problems, it can help start-ups meet their talent needs at lower costs and help mature companies grow. It can also be a surprising boon to Baby Boomers and Generation Xers. “We were raised at a time when there weren’t a lot of options, and now there are so many choices,” says Hufford, a member of Generation X. “For people who didn’t grow up that way, it can feel overwhelming. I like to help people navigate that shift. They realize they have a lot of skills that companies want and a lot of options. It’s kind of cool.” Originally published on HBR.org October 30, 2018

HBR Reprint H04MNG David Jolley is the EY Americas Growth Markets leader.

What Motivates Gig Economy Workers by Alex Rosenblat

THE GIG ECONOMY workforce is growing. A Pew Research Center survey on the sharing economy showed that in 2015, 8% of American adults earned money from an online employment platform across industries such as ride hailing, online tasks, and cleaning/laundry. These gig economy workers are driven by a range of motivations, from lacking other jobs to wanting control over their schedule to seeking social connection. But there are big differences separating those who are more financially reliant on gig work (56% of workers surveyed) and “casual” gig workers (42%), who report that they could live

comfortably without the additional income. While gig work is a necessity for some, it is a luxury for others. This bifurcation has been apparent in my own research. For more than two years, I’ve been doing qualitative research on Uber and Lyft drivers. I first examined, with my coauthor Luke Stark, how Uber uses automated mechanisms to manage drivers. More recently, I interviewed 85 Uber and Lyft drivers across the U.S. and Canada to see how their work varies across regions. I’ve also found that the ride-hail workforce spans many different types of drivers—from full-time earners to part-time

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workers and “hobbyists”— who drive for many different reasons. And I’ve seen that not everyone benefits from this work equally. In the U.S., Uber has 600,000 active drivers and Lyft has 315,000 (though both companies may define “active” differently, many drivers work for both, and turnover is very high). But research has found that most of these drivers work part-time. For example, an analysis by Jonathan Hall at Uber and Princeton economist Alan Krueger found that 51% of Uber drivers work one to 15 hours per week, and 30% work 16 to 34 hours per week—while 12% work 35 to 49 hours per week, and 7% work more than 50 hours per week. Similarly, a survey of subscribers to Harry Campbell’s popular blog for ride-share drivers found that Uber drivers who work 20 hours or less per week (nearly half of them) accounted for about 24% of Uber’s services and hours worked. And according to Lyft, 78% of their drivers work one to 15 hours per week, and 86% of them are either employed full-time elsewhere or seeking full-time employment. Other reports have found that most independent workers (in the U.S. and Europe) don’t rely on platforms like Uber for their primary source of income. As UCLA law professor Noah Zatz has observed, “A small proportion of drivers are doing most of Uber’s work.” This creates a tension between a minority of full-time drivers and a majority of drivers who work part-time, earn supplemental income, or drive for social reasons. Because the supply of gig labor is liquid and composed

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largely of part-time workers, employers like Uber have more flexibility to adjust wages and working conditions—but it’s their most dedicated workers who are affected most. The availability of part-time earners reduces pressure on employers to create more-sustainable earning opportunities. The workers who hope to make a living in ride-hail work take on the most risk.

While gig work is a necessity for some, it is a luxury for others.

This comes at a cost, however. Turnover is high—one in six online platform workers is new in any given month, and more than half of participants quit within a year. To continue attracting new workers, companies like Uber and Lyft have to do a better job of engaging existing ones by recognizing and meeting their different motivations and needs.

What Motivates Part-Time Ride-Hail Drivers One of the promises of the gig economy is that workers have more flexibility to work when and as much as they want. That’s why many people start driving to earn extra income outside their day jobs or in their free time. Hobbyists represent an illustrative segment of parttime drivers in the ride-hail workforce. These supplemental earners are retirees, working professionals, and empty nesters. Their primary motivation to work is often social.

My research suggests that they benefit most clearly from Uber’s employment model of independent contract labor, as they gain more opportunities for marginal employment and are less vulnerable to the same business practices (for example, rate cuts) that prompt strikes and protests from drivers who rely on Uber as a primary source of their household income. For example, one driver I interviewed, Nathan*, is in his late 60s and works as a licensed psychotherapist in Los Angeles. On weekends when he’s not working, he drives six to 12 hours for Lyft. Although the money is a plus, he mainly drives for social reasons and to escape from the emotionally taxing demands of dealing with patients. Nathan earns about $130 an hour as a psychotherapist, and he initially made $34 an hour driving for Lyft, with incentive pay, though this has dropped over the four months he’s been driving to $15 to $20 an hour. Yet he told me, “If I didn’t like going out to do it, I’d probably stop.” In January 2016, Uber cut rates for drivers in more than 100 cities in the U.S. and Canada, and Lyft followed suit in 33 cities. For drivers who need the money, these cuts can be hard to absorb. Rate cuts have sparked protests, strikes, and efforts to organize from Uber drivers in New York, Dallas, Seattle, and elsewhere. Driver discontent around rate cuts is widespread in forums. But while labor activism has gained momentum on the backs of frustrated ride-hail drivers, the experiences of hobbyists and other part-time earners in the workforce create an issue:

Although no one likes a pay cut, they aren’t as invested in their work conditions as those who make their living driving. Hobbyists like Nathan, who continue to drive despite declining earnings, represent an influx of workers who are motivated in part by nonfinancial values and are usually better positioned to absorb pay cuts. This may contribute to income destabilization for occupational drivers.

What Motivates Full-Time Ride-Hail Drivers A minority of ride-hail drivers work full-time, and for drivers who have made significant investments in this job, the precarity of their employment can cause a lot of strain. Another driver I talked to, Fernando, who drives for uberX and uberXL in the Boston area to support his family, reflected on a pattern that is common to drivers: They’re initially optimistic and satisfied with their work, particularly in the early stages of the company’s growth in their city, but they become distrustful of it over time. In addition to the flood of new drivers in his market and lower compensation (he noted that his take-home pay from airport trips had fallen, for example), he was also upset about Uber shifting its eligibility requirements for cars—in 2014 he spent $42,000 on an Uber-eligible car (which meant a 2005 or newer model), but in February 2015, Uber began allowing models dating to 2001. “You know how many people went to the dealer and bought new cars?” he asks. Another driver I talked to, Raj, has been driving professionally in Toronto for nine

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years, first as a taxi driver, then as the owner of a for-hire vehicle business, and now for UberSelect. He admires Uber’s technology, but he sees the influx of nonoccupational drivers as a threat to his livelihood: “Competition is always good for everyone, but again, it should be reasonable, not that you just flood the market.” With the advent of Uber, he’s become anxious about the stability of his income as a professional driver and is looking to change careers. He keeps textbooks under the front passenger seat so that he can study to become a mortgage broker in between rides. For others, driving offers a solution to a lack of other job opportunities, especially for those with a criminal record or limited education. Cody, who is in his mid-20s, is a Lyft driver in the Ann Arbor and Detroit, Michigan, area. He told me that he’s not eligible for good jobs with only a high school education: “There’s not a lot of jobs unless you’re looking at working in a factory for 80 hours a week.” The Pew survey found that one in five respondents said they used these digital platforms because job opportunities in their area were limited. In sum, the effects of the gig economy on the workforce are mixed. These platforms seem to most benefit people earning supplementary income or those lacking other job opportunities, while they impose the most risk on full-time earners. And Uber and Lyft are still facing legal challenges in the U.S. for classifying drivers as independent contractors rather than employees who can receive benefits. (In the United King-

dom, an employment tribunal recently ruled that two Uber drivers must receive employee benefits, including the national living wage. Uber plans to appeal that ruling.) For companies seeking to replicate Uber’s success, it’s important to understand that high attrition rates may not be a feasible long-term strategy— the flood of part-time workers could always dry up. Many drivers, both full- and part-timers, already strategize to maximize their incomes by switching between multiple platforms that offer different incentives or premiums. Uber, Lyft, and other app-based employers stand to gain from retaining dedicated users, or “power drivers,” who may be willing to work under more-strenuous conditions than social or supplementary earners. Platforms should seek to understand their diverse workforces and offer distinct employment promises that speak to their varied motivations and needs.

Performance Management in the Gig Economy

*Names have been changed to preserve driver anonymity. Originally published on HBR.org November 17, 2016

HBR Reprint H03A10 Alex Rosenblat is the author of Uberland: How Algorithms Are Rewriting the Rules of Work (University of California Press, 2018). She is also a technology ethnographer and works as a research lead at the Data and Society Research Institute.

by Jon Younger and Norm Smallwood

WE SEE BIG changes ahead in performance management. Organizations like GE and Accenture are experimenting with new approaches to that old shibboleth: the annual performance review. And far-thinking companies are replacing the annual rating and ranking process with more-timely capture of critical incidents and authentic spot feedback.

But one important and growing population in organizations isn’t benefiting from this feedback renaissance. They’re the external professionals your organization increasingly counts on: freelancers, gigsters, advisers, and consultants, the people we call agile talent in our new book. In our research, performance management is the weakest link in managing

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and engaging agile talent and in gaining the greatest productivity from your external talent investment. According to Deloitte, external workers may represent 30% or more of your organization’s true workforce. Freelancers Union reports that as much as 40% of the U.S. workforce views themselves as freelancers. And our research found that more than 50% of leaders fully expect agile talent to increase as a percentage of total employees. Why? Certainly, one goal is cost efficiency. But the more important drivers are speed, flexibility, and innovation.

Rapport blooms when agile talent is expected to honestly discuss potential problems.

Most organizations, however, are not set up to benefit from their increased investment in agile talent. Research by PMI describes most problems in project performance as being the result of alignment issues. Our findings concur. And the alignment gap is greatest when it comes to performance management. What can we do to close the performance alignment gap? Our research suggests six important steps: Share context. Too often agile talent reports that they are excluded from critical meetings and discussions that would provide helpful—and sometimes essential—context for their work. Our data shows

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that both agile talent and their client organizations miss critical opportunities to provide a thorough orientation to the work and its importance.

Measure more than cost, schedule, and quality. Defining the usual measures isn’t enough. Agile talent wants to know the nuances, and they’re particularly concerned that issues like cultural fit or other “soft” factors are often left unsaid or undefined until problems arise, creating additional cost or difficulty and enabling preventable conflict with internal colleagues.

Encourage agile talent to communicate concerns before problems bloom. To resolve problems before they affect a project, organizational leaders must sincerely encourage agile talent to communicate concerns. Our interviews reinforce the importance of regular review and a well-defined agenda for review. Rapport, the secret sauce of open discussion, blooms when agile talent is regularly invited and expected to honestly discuss potential problems.

Demonstrate two-way feedback. But encouragement isn’t enough. When we ask agile talent whether their client organizations really want feedback, we often see more teeth gnashing than affirmation. We learned that boundaries are important in two-way feedback—for example, “We talk about issues, not individuals,” or what some people call the “no gossip” rule.

Make sure the right managers are supervising your agile talent. Is your organization assigning the right professionals and managers to supervise

agile talent and their work? We heard time and again from external experts about the importance of both a performance and a developmental mindset. Managers who are performance oriented but not development oriented may assess well but not provide effective feedback and coaching. Managers who focus on development more than performance may miss when it comes to frank, tough assessments. Good managers of agile talent—just like good managers of full-timers—do both.

Acknowledge excellence and share the news. Agile talent is just as motivated by appreciation and recognition as your full-time employees are— more so, in fact, given that client satisfaction is the basis for their career success. Whether through something as simple as public praise or as personal as sending a dozen flowers and a handwritten letter, reinforce with acknowledgment and thanks. And let colleagues know. Agile talent is growing and here to stay, and organizational leaders are increasingly turning to external experts to provide the speed, flexibility, and innovation they need and to more cost-effectively plan initiatives. But organizations will gain the full benefits they seek only if they recognize that their agile talent needs strong performance management support, too. Originally published on HBR.org January 11, 2016

HBR Reprint H02LPB Jon Younger is the founder of the Agile Talent Collaborative, a nonprofit research organization, and an investor and adviser

in the HR/talent tech space. He was previously a partner of the RBL Group and senior vice president of human resources of a top-five U.S. bank. Younger is the coauthor of several books in talent management and HR, including Agile Talent: How to Source and Manage Outside Experts (Harvard Business Review Press, 2016). Norm Smallwood is a cofounder of the RBL Group, a strategic HR and leadership systems advisory firm, and a coauthor of several books, including Agile Talent: How to Source and Manage Outside Experts: How to Source and Manage Outside Experts (Harvard Business Review Press, 2016).

TODAY’S TALENT MANAGEMENT

Executive Summaries Build the SpeciaI Workforce You Need Issue How to Hire the Right People and KeepThem Engaged

The Best of HBR Insights on: Better People Analytics, Desirable Benefits, Adapting Your Workforce, and More!

“Hiring talent remains the number one concern of CEOs in the most recent Conference Board Annual Survey; it’s also the top concern of the entire executive suite.”

10 | HR Goes Agile Peter Cappelli and Anna Tavis Companies’ core businesses and functions have largely replaced long-range planning models with methods that let them adapt and innovate more quickly, and to support that, HR departments are starting to go “agile lite”—adopting the general principles but not all the protocols from the tech world. In this article Wharton’s Peter Cappelli and NYU’s Anna Tavis discuss the profound changes companies are making in six critical areas. Annual performance appraisals are often the first traditional practice to go. As employees work on shorter-term projects, run by different leaders and organized around teams, companies are recognizing that workers need more-immediate, ongoing feedback so that they can “course-correct” mistakes, improve performance, and learn through iteration. Coaching is another key item: getting managers to move from judging employees to helping them develop. Teams, rather than individuals, are the focus now that work is increasingly organized project by project. Compensation is changing too, with a switch to spot bonuses or no bonus but more-frequent salary adjustments. Recruiting has become faster and nimbler, and new learning and development practices help employees identify and access the skills and training they need to advance. HR has not had to change in recent decades nearly as much as have the line operations it supports. But now the pressure is on, and organizations from IBM to Regeneron Pharmaceuticals to the Bank of Montreal are paving the way.

18 | One Bank’s Agile Team Experiment Dominic Barton, Dennis Carey, and Ram Charan

YOUR APPROACH TO HIRING IS ALL WRONG PAGE 50

As mobile banking took hold and customers became increasingly aware of what they could do for themselves, the global banking group ING launched a pilot transformation in its Dutch retail unit, replacing most of its traditional structure with a fluid and more responsive organization composed of tribes, squads, and chapters. Dominic Barton, Dennis Carey, and Ram Charan report on this new way of working, which is being rolled out more widely across the bank. HBR Reprint R1802B

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22 | Reinventing Performance Management

30 | Better People Analytics

Marcus Buckingham and Ashley Goodall

Lately, people analytics—using statistical insights from employee data to manage talent—has gotten a lot of hype and even won mainstream acceptance. Yet most firms lack an understanding of which talent dimensions drive performance in their organizations. Why? Their analytics examine only the attributes of employees, when people’s interactions are equally, if not more, telling. Research shows that a lot of employees’ success can be explained by their relationships— something that’s the focus of a new discipline, relational analytics. The key is finding “structural signatures”: patterns in social networks that predict who will have good ideas, which employees have the most influence (it’s not senior leaders), which teams will be efficient, which will innovate best, where silos exist, and which employees firms can’t afford to lose. This article describes what indicators to watch for and how most firms already have the raw material they need to build relational analytics models: the “digital exhaust” from their internal communications.

Like many other companies, Deloitte realized that its system for evaluating the work of employees— and then training them, promoting them, and paying them accordingly—was increasingly out of step with its objectives. It searched for something nimbler, real-time, and more individualized—something squarely focused on fueling performance in the future rather than assessing it in the past. The new system will have no cascading objectives, no once-a-year reviews, and no 360-degree-feedback tools. Its hallmarks are speed, agility, one-sizefits-one, and constant learning, all underpinned by a new way of collecting reliable performance data. To arrive at this design, Deloitte drew on three pieces of evidence: a simple counting of hours, a review of research in the science of ratings, and a carefully controlled study of its own organization. It discovered that the organization was spending close to 2 million hours a year on performance management, and that “idiosyncratic rater effects” led to ratings that revealed more about team leaders than about the people they were rating. From an empirical study of its own high-performing teams, the company learned that three items correlated best with high performance for a team: “My coworkers are committed to doing quality work,” “The mission of our company inspires me,” and “I have the chance to use my strengths every day.” Of these, the third was the most powerful across the organization. With all this evidence in hand, the company set about designing a radical new performance management system, which the authors describe in this article. HBR Reprint R1504B

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Paul Leonardi and Noshir Contractor

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40 | “Numbers Take Us Only So Far” Maxine Williams Though executives tend to think—and want to believe—they’re hiring and promoting fairly, bias still creeps into their decisions. They often use ambiguous criteria to filter out people who aren’t like them or deem people from minority groups to be “not the right cultural fit,” leaving those employees with the uneasy feeling that their identity might be the real issue. Companies need to acknowledge that it’s fair for employees from underrepresented groups to be suspicious about bias, says Williams, Facebook’s global director of diversity. They also must find ways to give those workers more support. To that end, many organizations are turning to people analytics, which aspires to replace gut decisions with data-driven ones. Unfortunately, firms often say that they don’t have enough people from marginalized groups in their data sets to produce reliable insights. But there are things employers can do to supplement small n’s: draw on industry or sector data; learn from what’s happening in other companies; and deeply examine the experiences of individuals who work for them, talking with them to gather critical qualitative information. If firms are systematic and comprehensive in these efforts, they’ll have a better chance of improving diversity and inclusion. HBR Reprint R1706L

HOW RECRUITING WORKS NOW

50 | Your Approach to Hiring Is All Wrong

58 | Navigating Talent Hot Spots

Peter Cappelli

William Kerr

Businesses have never done as much hiring as they do today and have never done a worse job of it, says Peter Cappelli of Wharton. Much of the process is outsourced to companies such as Randstad, Manpower, and Adecco, which in turn use subcontractors to scour LinkedIn and social media for potential candidates. When applications come—always electronically—software sifts through them for key words that hiring managers want to see. Vendors offer an array of smartsounding tools that claim to predict who will be a good hire—but whether they produce satisfactory results is unknown. Cappelli explores what’s wrong with today’s recruiting and hiring and how to fix it.

Innovation clusters like San Francisco and Boston have long had an outsize impact on the global economy, and their influence keeps growing. In 2017, for instance, America’s 10 largest tech hubs accounted for 58% of U.S. patents. Globally, cities such as Tokyo, Paris, Beijing, Shenzhen, and Seoul produced a similar proportion. The increased geographic concentration of innovation activity poses a challenge for firms based in suburban industrial parks. To stay relevant, they need to tap into urban hotbeds, but setting up operations there can be extremely expensive. In his work on global talent flows, Harvard Business School’s Kerr has seen organizations try three solutions: At one extreme, they can relocate their headquarters to a hub, as GE recently did (but make them much smaller). A less expensive strategy is to create an innovation lab or corporate outpost in a talent cluster, as Walmart did with Walmart Labs. The most conservative strategy is to run executive retreats and immersions in talent clusters—a tactic Vodafone uses effectively. These three options aren’t mutually exclusive. Given the need to stay in touch with multiple clusters, companies may want to try them all. Each one involves substantial risks that executives must manage. But together they offer a good playbook to firms that are finding themselves outside the action as the clout of a handful of cities grows.

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RETAINING THE BEST

UNDERSTANDING THE GIG ECONOMY

76 | Your Workforce Is More Adaptable Than You Think

82 | Talent Management and the Dual-Career Couple

100 | Thriving in the Gig Economy

Jennifer Petriglieri

Joseph B. Fuller, Judith K. Wallenstein, Manjari Raman, and Alice de Chalendar

Companies invest heavily in grooming star talent for leadership—but most of them haven’t figured out how to manage the growing population of employees who care deeply about their partners’ or spouses’ careers at the same time that they want to advance their own. As a result, many high potentials are heading for the nearest exit. The author has seen this happen again and again in her research on dual-career couples in tech, health care, professional services, and other industries. She says the crux of the problem is that companies tend to have fixed paths to leadership roles, with set tours of duty and rigid ideas about what ambition looks like. That creates flexibility and mobility challenges for employees—and recruitment and retention headaches for employers. Organizations must adopt new strategies for managing and developing talent. They can remove barriers to advancement by allowing people to develop skills and networks in more-creative ways—through brief “job swaps,” for example, or commuter-leader roles. But often a culture change is needed. Instead of stigmatizing flexibility, companies must learn to embrace it.

Gianpiero Petriglieri, Susan Ashford, and Amy Wrzesniewski

In 2018 the Project on Managing the Future of Work at HBS teamed up with the BCG Henderson Institute to survey 6,500 business leaders and 11,000 workers about the various forces reshaping the nature of work. The responses revealed a surprising gap: While the executives were pessimistic about their employees’ ability to acquire the capabilities needed to thrive in an era of rapid change, the employees were not. The employees were actually focused on the benefits that change would bring and far more eager to learn new skills than their leaders gave them credit for. This gap highlights a vast reserve of talent and energy firms can tap into: their own workers. How can a company do that? By creating a learning culture; engaging employees in the transition instead of shepherding them through it; developing an internal talent pipeline for the entire workforce; and collaborating with outside partners to build the right skills in the labor pools it hires from. HBR Reprint R1903H

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Approximately 150 million people in North America and Western Europe now work as independent contractors, most of them in knowledge-intensive industries and creative occupations. The authors studied 65 of them in depth and learned that although they feel a host of personal, social, and economic anxieties without the cover and support of a traditional employer, they also say they chose independence and wouldn’t give up the benefits that come with it. Many of these workers have created a “holding environment” for themselves by establishing four connections: (1) place, in the form of idiosyncratic, dedicated workspaces that allow easy access to the tools of their owners’ trades; (2) routines that streamline workflow and incorporate personal care; (3) purpose, to create a bridge between personal interests and motivations and a need in the world; and (4) people to whom they turn for reassurance and encouragement. These connections help independent workers sustain productivity, endure their anxieties, and even turn those feelings into sources of creativity and growth. HBR Reprint R1802M