A Manager's Guide to the New World of Work: The Most Effective Strategies for Managing People, Teams, and Organizations

A Manager's Guide to the New World of Work: The Most Effective Strategies for Managing People, Teams, and Organizations

by MIT Sloan Management Review

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Overview

Insights from organizations that are navigating the novel challenges of the digital workplace.

How can technology and analytics help companies manage people? Why do teams working remotely still need leaders? When should organizations use digital assessment tools for gauging talent and potential? This book from MIT Sloan Management Review answers questions managers are only beginning to ask, presenting insights and stories from organizations navigating the novel challenges of the digital workplace.

Experts from business and academia describe what's worked, what's failed, and what they've learned in the new world of work. They look at strategies that organizations use to help managers and employees adapt to the fast-changing digital environment, from the benefits of wool-gathering to the use of anonymous chats; examine digital tools for collaboration, including interactive spreadsheets and analytics that increase transparency; and discuss such “big-picture” trends as expanded notions of value and new frontiers in upskilling. A detailed case study, produced by MIT Sloan Management Review in collaboration with McKinsey & Company, explores how IBM reimagined talent and performance management with the goal of increasing employee engagement.

Contributors

Steve Berez, Ethan Bernstein, Josh Bersin, Matthew Bidwell, Ryan Bonnici, Tomas Chamorro-Premuzic, Rob Cross, Chris DeBrusk, Federica De Stefano, Thomas H. Davenport, Angela Duckworth, Ken Favaro, Lynda Gratton, Peter Gray, Lindred Greer, John Hagel III, Manish Jhunjhunwala, David Kiron, Frieda Klotz,, David Lazer, Massimo Magni, Likoebe Maruping, Kelly Monahan, Will Poindexter, Reb Rebele, Adam Roseman, Michael Schrage, Jeff Schwartz, Jesse Shore, Brian SolisBarbara Spindel, Anna A. Tavis, Adam Waytz,, David Waller, Maggie Wooll

Product Details

ISBN-13: 9780262539449
Publisher: MIT Press
Publication date: 07/21/2020
Series: The Digital Future of Management
Pages: 224
Sales rank: 791,874
Product dimensions: 5.38(w) x 8.06(h) x 0.54(d)

Read an Excerpt

Digital tools and technologies are now relentlessly and remorselessly transforming how performance management works. Customized and continuous data-driven feedback is becoming the new normal for enterprises worldwide. This feedback appears both qualitatively and quantitatively superior to its performance review precursors and should lead to better outcomes. But does AI-flavored feedback require a human touch to measurably improve its impact?
Organizations committed to state-of-the-art talent management are revisiting the role managers should play in delivering, facilitating, and/or curating employee feedback. Are managers mainly conduits for criticism? Or do they add meaningful value and insight? “We know that putting the manager back in performance management is one of the keys to making it work,” said McKinsey & Company partner Bryan Hancock during a recent webinar on performance management.1 “You can create the best system in the world with the best amount of employee involvement,” he said, “but if at key junctures, the managers aren’t taking responsibility, it’s a problem”—especially since Netflix, Google, Amazon, and other digital innovators have successfully personalized sophisticated analytic assessments for their users.
Whether or not average managers represent an organization’s best option for constructively critiquing employees is now an open and important question. Preliminary findings from our recent research suggest that ongoing investment and innovation in AI capabilities will provoke conflicting answers. The implications for legacy HR and people management are enormous.
This research highlights how direct managerial involvement both complements and competes with data-determined performance reviews. Increasingly, organizations are discovering they must explicitly choose whether humans or machines should get the last word on people’s performance. This process is as much about cultural transformation as organizational transition. However, productively balancing analytic insight with managerial interaction is challenging. Who owns the feedback?
IBM’s digital journey offers a superb case study in confronting these performance management challenges. The company’s HR leadership, for example, explicitly tracks managerial impact on employee engagement and outcomes.
“The role of the manager is incredibly important still, even in an agile culture,” acknowledges Diane Gherson, IBM’s chief human resources officer and senior vice president of human resources. “If there’s a manager who’s not ‘bought in’ or not engaged, the chances of their people not being engaged is something like three times higher. Making sure that managers fully understand the strategy and are fully engaged really can’t be forgotten.”
But Gherson emphasizes that her group’s intensifying commitment to AI has dramatically changed IBM’s human capital management. “We’ve got a lot of AI in our HR,” she notes. That investment profoundly alters how managers and employees engage with one another. Smarter software has fundamentally restructured IBM’s performance management economics and expectations. Increased digitalization often disintermediates direct managerial engagement.
AI’s most significant influence is on productivity, says Gherson. HR has replaced many human resources with chatbots, for example, that learn to advise employees while generating analytics for monitoring how helpful the advice proves to be. In other words, IBM gets feedback on feedback.
Comparable AI systems offer decision support with actionable insights into possible attrition and suggestions about appropriate pay levels for employees with highly competitive skill sets. “Enabling better employee experiences” is another AI focus, Gherson says. These systems embrace career development advice, personalized learning programs, and Blue Matching (IBM’s proprietary system that intelligently matches candidates to desirable job openings within the company).
As important as managers may be, IBM HR’s clarion message is that digitalization must deliver smarter, better, faster, and more engaging talent management services for less. Personalized and productive feedback can’t come at a premium price. At the same time, most organizations authentically want their highercost human managers engaged and involved.
This conflicted sensibility and expectation is not unique. ADP vice president and chief behavioral economist Jordan Birnbaum observes that empowering managers and employees has become an important part of performance management systems design. “When performance management is designed well,” he says, “managers have a toolbox that helps them improve by several orders of magnitude, leaving employees feeling empowered to succeed moving forward.”
The catch, he acknowledges, is that being objectively datadriven often forces people to incorporate uncomfortable algorithmic advice. “If you’re going to use evaluative data properly,” says Birnbaum, “then the job is to frame that data properly, particularly if it is being used to drive future performance. That also includes incorporating feedback not easily measurable or captured by data, like teamwork or supportiveness. But as long as relevant data is not easily captured, there’s a place for the human manager in the process. Whether the human manager feels that to be the case, though, is another story.”
The tension becomes obvious: Is being asked—or told—to follow a prescription that makes one measurably better a source of managerial empowerment or disempowerment? For managers and employees alike, does it bring about more confusion? For example, would managers have the discretion to ignore or significantly alter their data-driven advisories? How do conflicts between intuition and evidence get resolved? Most managers are grateful for contextually relevant analytic advice. But advice that must be followed is no longer advice—it’s compulsion.
As AI and machine learning technologies improve, says Birnbaum, managerial prescriptions become even more specific and explicit. This leads to a natural question: At what point does it make sense—and save money—to simply bypass the manager as a feedback delivery system and directly advise the employee?

Table of Contents

Series Foreword ix

Introduction: Managing Today for the Future xi

I Managing People 1

1 Train Your People to Think in Code David Waller 3

2 Leisure Is Our Killer App Adam Waytz 9

3 Self-Reports Spur Self-Reflection Angela Duckworth 15

4 Career Management Isn't Just the Employee's Job Matthew Bidwell Federica De Stefano 23

5 Can We Really Test People for Potential? Reb Rebele 29

6 Does Al-Flavored Feedback Require a Human Touch? Michael Schrage 39

7 What Managers Can Gain from Anonymous Chats Ryan Bonnici 43

8 Are Your Employees Driven to Digital Distraction? Brian Solis 47

II Managing Teams 53

9 Get Things Done with Smaller Teams Chris DeBrusk 55

10 Why Teams Still Need Leaders Lindred Greer Frieda Klotz 63

11 Why Teams Should Record Individual Expectations Ken Favaro Manish Jhunjhunwala 71

12 Collaborate Smarter, Not Harder Rob Cross Thomas H. Davenport Peter Gray 77

13 Improving the Rhythm of Your Collaboration Ethan Bernstein Jesse Shore David Lazer 93

III Managing Organizations 111

14 Reframing the Future of Work Jeff Schwartz John Hagel III Maggie Wooll Kelly Monahan 113

15 It's Time to Rethink the IT Talent Model Will Poindexter Steve Berez 121

16 New Ways to Gauge Talent and Potential Josh Bersin Tomas Chamorro-Premuzic 127

17 Pioneering Approaches to Re-skilling and Upskilling Lynda Gratton 137

18 How Managers Can Best Support a Gig Workforce Adam Roseman 143

19 Unleashing Innovation with Collaboration Platforms Massimo Magni Likoebe Maruping 147

IV Case Study 155

20 Rebooting Work for a Digital Era: How IBM Reimagined Talent and Performance Management David Kiron Barbara Spindel 157

Commentary: HR Transformation as the Engine for Business Renewal Anna A. Tavis 172

Contributors 179

Notes 183

Index 195

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