The Digital Mindset “Today, when every company has to be a tech company, developing a strong digital mindset may be the single most important step toward achieving your future success The Digital Mindset is an invaluable resource for anyone looking to become a better leader, future proof their career, or simply gain a better understanding of the present and future of business ” —MICKEY (HIROSHI) MIKITANI, founder, Chairman, and CEO, Rakuten Group “If you’re worried that algorithms will replace o.
“Today, when every company has to be a tech company, developing a strong digital mindset may be the single most important step toward achieving your future success The Digital Mindset is an invaluable resource for anyone looking to become a better leader, future-proof their career, or simply gain a better understanding of the present and future of business.” —MICKEY (HIROSHI) MIKITANI, founder, Chairman, and CEO, Rakuten Group “If you’re worried that algorithms will replace our judgment, big data will make our little knowledge obsolete, or robots will steal our jobs, this book is for you Paul Leonardi and Tsedal Neeley are leading experts on how technology is transforming work, and they offer the practical insights you need to understand the next wave of digital change—and ride it smoothly.” —ADAM GRANT, New York Times bestselling author, Think Again; host, TED podcast WorkLife “We’ve all heard it a million times: You need to be more digital Finally, here’s a book that explains what that really means, a book that ascribes real meaning to the buzzword With clarity and a surprising level of detail, Paul Leonardi and Tsedal Neeley prepare you for the digital future by developing your digital mindset.” —SHELLYE ARCHAMBEAU, former CEO, MetricStream; author, Unapologetically Ambitious “Digital transformation doesn’t stop with good strategy It starts there The Digital Mindset provides critical and actionable insights that make it possible for everyone—from the executive team to individual contributors—to help their company succeed in the digital era Today’s CEOs must make sure their entire workforce has a digital mindset This book is the place to start.” —JEFF HENLEY, Executive Vice Chairman, Oracle “If we continue to consider the digital age as a purely technological revolution, we will miss the most significant economic, political, and behavioral disruption of our societies since the Industrial Revolution This is exactly what The Digital Mindset offers: the 360-degree understanding necessary to seize this moment.” —ELIE GIRARD, former CEO, Atos “This breakthrough book is the ideal guide to enable you to operate or lead with a digital mindset Down-to-earth and practical, it makes digital transformation achievable for anyone committed to learning new ways of thinking about the three c’s of collaboration, computation, and change in order to solve complex systems problems Most importantly, you don’t need to be a computer guru to transform your organization using these principles.” —BILL GEORGE, Senior Fellow, Harvard Business School; former Chairman and CEO, Medtronic; and bestselling author, Discover Your True North “Leonardi and Neeley have produced the indispensable, foundational playbook for leaders looking to thrive in the digital age In The Digital Mindset they have managed to effectively combine a crisp review of key concepts and practical advice on how to put them to work.” —HUBERT JOLY, former Chairman and CEO, Best Buy; Senior Lecturer, Harvard Business School; and author, The Heart of Business HBR Press Quantity Sales Discounts Harvard Business Review Press titles are available at significant quantity discounts when purchased in bulk for client gifts, sales promotions, and premiums Special editions, including books with corporate logos, customized covers, and letters from the company or CEO printed in the front matter, as well as excerpts of existing books, can also be created in large quantities for special needs For details and discount information for both print and ebook formats, contact booksales@harvardbusiness.org, tel 800-988-0886, or www.hbr.org/bulksales Copyright 2022 Harvard Business School Publishing Corporation All rights reserved No part of this publication may be reproduced, stored in or introduced into a retrieval system, or transmitted, in any form, or by any means (electronic, mechanical, photocopying, recording, or otherwise), without the prior permission of the publisher Requests for permission should be directed to permissions@harvardbusiness.org, or mailed to Permissions, Harvard Business School Publishing, 60 Harvard Way, Boston, Massachusetts 02163 The web addresses referenced in this book were live and correct at the time of the book’s publication but may be subject to change Library of Congress Cataloging-in-Publication Data Names: Leonardi, Paul M., 1979– author | Neeley, Tsedal, author Title: The digital mindset : what it really takes to thrive in the age of data, algorithms, and AI / Paul Leonardi and Tsedal Neeley Description: Boston, Massachusetts : Harvard Business School Publishing Corporation, [2022] | Includes index Identifiers: LCCN 2021047511 (print) | LCCN 2021047512 (ebook) | ISBN 9781647820107 (hardback) | ISBN 9781647820114 (epub) Subjects: LCSH: Technological innovations | Computer literacy | Numeracy | Artificial intelligence | Success in business Classification: LCC HD45 L434 2022 (print) | LCC HD45 (ebook) | DDC 658.5/14— dc23/eng/20211202 LC record available at https://lccn.loc.gov/2021047511 LC ebook record available at https://lccn.loc.gov/2021047512 ISBN: 978-1-64782-010-7 eISBN: 978-1-64782-011-4 For Rodda, Amelia, Norah, and Eliza, who all have brilliant minds and, most impressively, the courage to change them —Paul Leonardi For my mother, the wisest person I know, who embodies curiosity, courage, and lifelong learning —Tsedal Neeley CONTENTS Introduction The 30 Percent Rule PART ONE COLLABORATION Working with Machines When Human Intelligence Meets Artificial Intelligence Cultivating Your Digital Presence Being There When You’re Not PART TWO COMPUTATION Data and Analytics What Is Counted Ends Up Counting Drunks and Lampposts It’s Time to Become Conversant in Statistics PART THREE CHANGE Cybersecurity and Privacy Why You Can’t Just Build a Castle The Experimentation Imperative You Won’t Know Until You Try The Only Constant Leading as Transitioning Conclusion It’s Time! Appendix: Continuous Learning Case Examples Glossary Notes Index Acknowledgments About the Authors Introduction The 30 Percent Rule The world as we have created it is a process of our thinking It cannot be changed without changing our thinking —Albert Einstein Sara Menker sat at her desk in Manhattan staring at her computer screen It was the summer of 2008 and she was watching the financial markets collapse before her eyes As an energy commodities trader at Morgan Stanley, she knew the numbers running across her screen were catastrophic A loud gasp from her colleague at the next desk made her turn He had his face in his hands, as if to hide from the horror “The world’s coming to an end,” he said “This is Armageddon We better start buying up gold.” “What are you going to with all that gold if the world’s economies collapse?” Sara blurted out “Forget gold Buy a sack of potatoes! You need potatoes We’ll all need potatoes.” Her colleague laughed Then Sara laughed too, uneasily Later that evening, Sara was still thinking about potatoes Born and raised in Ethiopia, a country with a history of catastrophic famine, she understood the value of food security in ways that many of her peers on Wall Street did not.1 She found herself researching farmland prices in her home country Thinking like a trader, she saw an investment opportunity The land was cheap It was selling for $1.50 an acre in some areas It also seemed relatively easy to purchase tens of thousands of acres Intrigued, Sara decided to take a trip home to learn more She didn’t know anything about agriculture, but she had confidence that Einstein, Albert, 1, 83 Eisenberg, Eric, 55 Electronic Arts (EA), 106, 107 email spam filter, AI system in, 30 Embr Labs, 102 employee(s) autonomy, 192, 193, 206, 208 data change impact on employees behavior, 187–188 decision to use new technology, 185–187 learning programs, 182–183 “Englishnization,” 183 ERP systems, 176 error(s), 76, 81, 95 type I, 107–108 type II, 107–109 Escher, M C., 232n5 Ethereum, 138 Ethiopia(n) coffee market, GDP of, 219n1 “ethos of experimentation,” 148 Everledger, 135 experimentation, 10 See also digital experimentation Facebook, 63, 75, 88, 127–128, 129, 234n2 failure, acceptance of, 205 “faster and cheaper” designs, 184–186, 188–189 Felin, Teppo, 140 FleishmanHillard, 52 FLIR, 76 4Cs (color, cut, clarity, and carat weight), 135 “front-end” system, 38, 214 Fuechsel, George, 79 gamification, 206–207 “garbage in, garbage out” approach, 79–81 Gebru, Timnit, 86 Geico, 101–102 Gemological Institute of America, 134 Gender Shades, 86 Germany, coffee import and export in, 3–4 Gillespie, Tarleton, 129 Glikson, Ella, 46 global ecosystem of digital technologies, Global Science Research, 127 Go1 startup, 208 Gonick, Larry, 107 Google, 43, 81, 128, 129, 173, 181, 219n4 Google AdWords, 58 Google Health, 37 Google Search, AI system in, 31 Google Translate, AI system in, 30 GreenHouse, 192 Gro Intelligence, 4–5 group trainings, 66 Hacker News, 149 Hawkins, Eric, 125 Heap, Imogen, 139 HERE Technologies, 133 Hewlett-Packard, 52 Hill, Jonah, 76 horizontal learning, 206 horizontal mobility, 207, 208 Houston, Drew, 149 HubSpot, 106–107, 108 human-agent teaming, 43 AI-powered machines, 46–48 digital mindset development, 44–45 machine learning, 44 “objective” vs “subjective” criteria, 45–46 trust in machines, 45, 46 Human Development Index, 219n1 hypothesis testing, 104, 114, 215 A/B testing, 105–106 alternative hypothesis, 104, 108, 109t, 114, 215 null hypothesis, 104, 105, 107, 108, 109t, 114 Iansiti, Marco, 139 IBM, 37, 52, 86, 138, 139 inferential statistics, 101–102, 215 confidence intervals, 102–104 hypothesis testing, 104–107 sample set, 101 “informal” social relationships, 226n14 information, 14, 43, 68, 78, 128–130, 137, 199 See also data complex, 138 consumer, 229n12 contextual, 60–61 mutual knowledge, 52 real-time, sharing, 61–63, 65, 67 visual, 47 information technology (IT), 175–176 ING, 173, 174, 176 innovation, 6, 61, 62, 66, 166, 194, 205, 22n10 digital, 147, 151, 171 internal, 154 Instagram, 63, 234n2 interaction, 47, 59, 205 face-to-face, 67–68 human-like, 40, 43 non-work, 64, 226n15 rules of, 26–28 social media, 64, 69 internal marketing campaigns, 66, 179, 180 internal record-keeping systems, 138, 141 internal social media, 10, 12, 53, 59 strategies for digital presence, 69–70 tools, 60 Interstellar company, 139 Interstellar (movie), 28 Isaac, William, 89 Java, 20 J P Morgan, 220n9 Kanaan, Michael, 60 key performance indicators (KPIs), 99 Kimberley Process, 134 Kim, Y., 224n27 King, Jennifer, 132 Kogan, Aleksandr, 127 Kopp, Michael, 133 Lakhani, Karim, 139 Lang, Andrew, 98 leaders(hip), 170 learning from, 204 messaging from, 178 selling digital transformation, 184–185 servant, 206, 207 learning cloud-based, 209 horizontal, 206 from leaders, 204 to love chaos, 205 learning agenda creation, 148–149, 165 become comfortable with failure, 151–152 document creation, 150–151 intentional experiment, 149–150 learning experience platforms (LXPs), 193 “Learn with Google AI” training program, 182 Lees’ Guide to Game of Draughts and Checkers (Samuel), 44 Leibowitz, Sarah, 223n21 Lewis, Michael, 73, 74, 83 linear regression model, 109–110 LinkedIn, 128 “localized” applications, 139 Logg, Jennifer, 45 LogMeIn, 52 Lombana, Claudia, 57 L’Oréal, 150, 151 Los Angeles Police Department (LAPD), 86, 88 Los Angeles Strategic Extraction and Restoration See Operation LASER Lum, Kristian, 89 LYNA (LYmph Node Assistant), 37 machine language, 19–20 machine learning, 12, 31, 44, 49, 168, 170, 215 algorithms, 34, 35–37 analysis, 88 classic machine learning vs deep learning, 32, 33f deep learning, vs., 33–34, 34f DLAD, 36–37 image patterning demonstration, 31–32 NLP, 34–35 machines, working with, 25–26 30 percent rule in, 49–50 artificial intelligence, 28–31 human-agent teaming, 43–48 machine learning, 31–37 rules of interaction, 26–28 technology stack, 38–40 treating machines like machines, 40–43 Madsen, Peter, 151 Major League Baseball, 73 manual input data production method, 78 McCarthy, John, 28 McHugh, Nadine, 150 McKinsey diversity study, 103, 109, 111, 112 MedRec, 138 Menker, Sara, 1–2, 8, 219n2 developing analytic skills, 2–4 digital mindset of, 4–6 and Gro Intelligence company, 4–5 metadata, 152–153 metaknowledge, 61, 63, 215, 225n9 Metropolitan Planning Organization (MPO), 89–90 microcredentials, 193 Microsoft, 76, 86, 129, 147, 180 middleware, 38–39, 215 Mikitani, Hiroshi, 182 millennials, 63 mindset, definition of, 10 See also digital mindset minimally invasive cardiac surgery (MICS), 162–163 Minority Report (movie), 28 Moderna, 14, 174–175 Moneyball (Lewis), 73, 74 Moon, Youngme, 42 Moore’s law, 222n11 Mortensen, Dennis, 41 Mountainside approach, 90, 92f, 93–94 Mulligan, Deirdre, 132 mutual knowledge, 52 problem, 51–52, 53, 68, 216 Mycelia, 139 Napoleon Dynamite (movie), 84, 85 Nasdaq, 139 Nass, Clifford, 42 National Basketball Association (NBA), 81 natural language processing (NLP), 34, 43, 216 Nest Thermostat, 30 Netflix, 13, 84, 85, 173 neural network, 33, 216 Newman, David, 45 Newsfeed (Facebook), 31 New York Times Magazine, 74 Nika, Marily, 31 nonverbal communication, 68 null hypothesis (H0), 104, 105, 107, 108, 109t, 114, 215 NYX Professional Makeup, 151 Oakland Athletics, 73, 75, 82 “objective” criteria, 45–46 objectivity of data, 87 Oceanside approach, 90, 91f, 93 one-on-one sessions, 66 online dating, 63 online social activity, 61 opacity, 224n34 Operation LASER, 86–87, 88 organizational politics, 159–161 Palantir, 87 paper ledgers, data from, 78 Philips, 192, 209–210 physical robots, 27 Pitt, Brad, 76 Pixar, 84 possibility of being wrong, 107–108 type I error, 108 type II error, 108–109 prediction of data, 82 predictive statistics, 109, 115, 216 PredPol, 88–89 prescription of data, 82 privacy, 128, 129 best practices for, 130–134 data, 128 design for, 128, 130, 142 safeguard, 156–157 Privacy by Design (PbD), 131, 216 for consent management, 133 foundational principles, 131–132 Project Aristotle, 163, 164 psychological safety, 209 for digital experimentation, 161–164 public-key cryptography, 137 p-value in regression, 107, 111–112, 114, 216 Python, 18, 19, 20 quantum computing systems, 37 radio frequency identification tags (RFID tags), 78–79, 226n5 Rakuten, 182, 183 rapid change era, 6, 10, 172, 192, 201 Reddit, 63 regressions, 109, 110, 115, 228n15 correlation vs causation, 112, 115 linear regression model, 109–110 model, 216 P-value in, 111–112, 114 predictive statistics, 109, 115 reinforcement learning, 36, 216 Research Lab OpenAI, 222n11 Ripple, 138 Robins, Mark, 32 robotic teammates, 10 robots, 29 AI-powered, 46–48 physical, 27 Ruby, 20 safeguard privacy, 156–157 Samuel, Arthur, 44 Saudi Aramco, 126 cyberattack on, 119–120 scripts, 18–19, 20, 217 security, 10 See also cybersecurity 30 percent rule, 142–143 reducing security problems, 141 vulnerabilities, 122 self-determination theory, 204 self-ownership, 205 sense of curiosity creation, 55–57 servant leadership, 206, 207 “server side” system See “back-end” system “Shamoon” (computer virus), 120, 126 Shaw, George Bernard, 197 significance level, 107, 114, 217 Silicon Valley, Silo Effect, The (Tett), 233n10 SimCity games, 106, 107, 108 Simon, Herbert, 199 singular value decomposition, 84–85, 95 Siri (Apple), 28 Skype, 43 Slack, 152, 153, 198, 234n2 smart contracts, 138–139, 217 smart phones, AI system in, 30 Smith, Woolcott, 107 Snapchat, 63 socialization, 210 social lubrication for digital tools, 59–60, 68 articulating purpose, 60–61, 69 learning from digital collaboration tools, 61–63, 69 personal or social chats, 63–66, 69–70 social media function, 210 social tools, 61–62 Software as a Service (SaaS), 155, 163, 164, 176, 217 Sorting Things Out (Bowker and Star), 82 Spotify, 99, 173, 192, 204 ARPU, 228n3 using central tendency, 100 using dispersion, 101 “stack-and-pack housing,” 91 standard deviation, 100, 114, 217 Star, Susan Leigh, 82–83 Star Wars (movie), 28 statistical models for AI, 29–30 statistics, 10, 97–98 30 percent rule, 114–115 descriptive, 98–101 inferential, 101–107 possibility of being wrong, 107–109 predicting outcomes with regressions, 109–111 statistical integration into digital mindset, 112–113 Stellar, 139 strategic ambiguity, 56–57 StreetBump, 86 stretch roles, 207 Structural Enablers of 5-Star Performance, 160 subjective criteria, 46 subjective data analysis, 88 subject matter experts (SMEs), 162 Sundar, S Shyam, 224n27 Swanson, Burt, 25 tacit knowledge, 221n13 tailored curricula, 193 Tampa Bay Rays, 73, 76 Tech College, 203 technical debt, 124–125, 217 budget for, 124, 125, 127, 142 consequences of, 126–127 techno-solutionism, 60 technology stack, 38, 39f, 49, 217 interdependent layers, 39–40 middleware, 38–39 subsystems, 38 Terminator, The (movie), 28 Tett, Gillian, 233n10 30 percent rule, 11–12, 211 for digital shift/transformation, 195–196 for digital experimentation, 165–166 establishing digital presence, 69–70 principles of data analysis, 95–96 for security, 142–143 statistics, 114–115 in working with machines, 49–50 “This is Your Digital Life” app, 127 Thomke, Stefan, 148 Thompson, Clive, 63 3-D visualizations, 90, 92 for 30 percent rule, 195–196 transitional states, 169, 218 transparency, 130, 224n34, 224n35 trust, 65, 224n28 in machines, 45, 46 Twitter, 63, 234n2, 123–124 Tyco, 52 type I error, 107, 108, 218 type II error, 107, 108–109, 218 Tyson, 138 Unilever, 173–174 unsupervised learning, 36, 218 upskilling, 179–182, 196 upward mobility, 207 UrbanSim animation model, 90, 200 for Oceanside approach, 90, 91f, 93 or Mountainside approach, 90, 92f, 93 Urban, Tim, 222n8 user experience (UX) design, 194 US Department of Agriculture (USDA), US Federal Trade Commission, 128 Vadon, Mark, 57 variance, 100, 103, 218 vectors, 174, 218 Verizon Wireless, 52 vertical mobility, 209 Visa, 139 vocabulary development, 155–156 voice recognition apps, AI system in, 30 Waddell, Paul, 90 Wakslak, Cheryl, 93 Wall Street, Walmart, 138 Wang, Wuyi, 134 Welde, Rahul, 174 Wells Fargo, 52 Westpac, 193, 208 Wiesenfeld, Batia, 94 Wilson, H James, 157 Woolley, Anita, 46 work digitization process (WDP), 169 Workpl@ce, 234n2 World Economic Outlook Database, 219n1 x.ai company, 26, 41 Yammer, 234n2 Yelp, 14, 35, 36, 194, 205–207 Yelp Beans, 206 Yelp Extended Faculty, 206 Zappos, 173 Zuboff, Shoshana, 157 Zulily, 57 ACKNOWLEDGMENTS Our own journeys toward a digital mindset began in the early 2000s when we enrolled in Stanford University’s Management Science and Engineering PhD program Neither one of us had an engineering background, though both of us had worked in or with high-tech companies and were convinced that technology would be core to the future of work The experience of working alongside engineers while learning new methodologies and ways of thinking charted the course for the next decades of our work that helped us build and refine our conceptualization of a digital mindset We will be forever grateful to Steve Barley, Bob Sutton, Diane Bailey, and Pam Hinds at Stanford’s Center for Work, Technology, and Organization for helping us start down this path and for always providing encouragement and insights along the way We are lucky to have been surrounded by so many inspiring colleagues who have also shaped our thinking about the concepts in this book Tsedal has learned tremendously about digital work from many conversations with intellectual partners including James Barnett, Iav Bojinov, Vittorio Colao, Marco Iansiti, Marily Nika, Michael Norris, Jin Paik, Hanspeter Pfister, Jeff Polzer, and Sebastian Reiche A special thanks to Amy Bernstein, Tsedal’s nephew Emmanuel Mengistab, and Karim Lakhani who have provided precious support and insights from the very start Paul’s work has benefited from colleagues at Northwestern University, including Noshir Contractor, Barbara O’Keefe, Pablo Boczkowski, Eszter Hargittai, Darren Gergle, Brian Uzzi, Willie Ocasio, Klaus Weber, Jim Spillane, Jeannette Colyvas, and Elizabeth Gerber At UC Santa Barbara, Kyle Lewis, Matt Beane, Jessica Santana, Dave Seibold, Gary Hansen, Cynthia Stohl, Michael Stohl, Ron Rice, Linda Putnam, and Jennifer Gibbs have provided valuable insights that have found their way into many of the ideas and examples in this book Finally, Paul extends an enormous thank you to his PhD students, past and present, including Jeff Treem, Will Barley, Casey Pierce, Samantha Keppler, Lindsay Young, DJ Woo, Camille Endacott, and Virginia Leavell, whose research on their quests to build their own digital mindsets constantly inspires him On a more personal note, we are both grateful to our loving families for their unwavering support Tsedal has been blessed to have parents who always encouraged her to pursue purposeful work A very special thank you to Lawrence, Gabe, and Daniel for encouraging and inspiring her to remain curious Paul’s parents have always encouraged him to explore new areas and try new things Rodda, Amelia, Norah, and Eliza are constant sources of inspiration and hope Their laughter, love, and good deeds fill his life with joy We are also very grateful to Karen Propp for her outstanding editorial support We also extend special thanks to JT Keller, Patrick Sanguineti, and Fed Chavez, who have contributed tremendously to the research and development of this book We are thankful to our editor, Scott Berinato, at Harvard Business Review Press who was a steady hand throughout our many revisions His guidance on how to best communicate our content in an accessible way was invaluable Finally, we thank the thousands of people who work in the organizations we’ve done research in, consulted for, advised, and taught—some of whom were on the cutting edge of technological innovation and others who were struggling to move fully into the digital era There are too many of you to thank individually for your wisdom and kindness But if you see yourself or your company in this book by real name, pseudonym, or allusion, please know that we are grateful for everything you taught us We hope that this book will help you and others to continue on your journey into the digital future confident that you have the ability to see, think, and act in new ways ABOUT THE AUTHORS PAUL LEONARDI is an award-winning researcher, professor, and consultant who focuses on helping organizations become more innovative and creating change that improves the work lives of leaders, managers, and team members As a leading expert in digital transformation, remote work, and social networks, his goal is to prepare organizations and their employees to succeed in the rapid transition into the new era of data-intensive and technology-supported work Paul has published more than 100 articles on these topics in top research-oriented journals, as well as numerous managerialoriented articles based on his original research in magazines such as Harvard Business Review and MIT Sloan Management Review This work has been covered by media outlets such as the New York Times, the Wall Street Journal, Financial Times, Fortune, and Fast Company Paul has published four research-focused books on digital transformation Over the past two decades, he has consulted with for-profit and nonprofit organizations about how to improve communication between departments, how to use social technologies to enhance internal knowledge sharing, how to structure global product development operations, and how to manage the human aspects of new technology implementation He is also a regular keynote speaker for corporate trainings and user conferences on these and other topics related to innovation and change Paul has won more than thirty awards for his research and teaching, including multiple outstanding article awards from professional associations such as the Academy of Management, Strategic Management Society, and the National Communication Association In 2021 he was elected a fellow of the International Communication Association, where he also received the Fredric Jablin Award for lifetime contributions to the study of organizational communication He has also won major awards for his teaching to undergraduate and graduate students for his courses on digital transformation, managing innovation, and the future of work At the University of California Santa Barbara, he holds the Duca Family Endowed Chair in Technology Management and serves as director of the PhD program in Organization Studies in the College of Engineering Previously, he served as the founding director of the Master of Technology Management (MTM) program, a professional management program for technical leaders, which he launched in 2014 and ran until 2019 Before joining UCSB, Paul worked at Northwestern University, where he was jointly appointed across the School of Communication, the McCormick School of Engineering, and the Kellogg School of Management He received his PhD in management science and engineering from Stanford University TSEDAL NEELEY is an award-winning scholar and teacher as the Naylor Fitzhugh Professor of Business Administration and Senior Associate Dean of Faculty Development and Research Strategy at Harvard Business School Recognized as one of the 100 People Transforming Business by Business Insider, Tsedal focuses on helping leaders scale their organizations by developing and implementing global and digital strategies She regularly advises top leaders worldwide who are embarking on virtual work and large-scale change that involves global expansion, digital transformation, and becoming more agile Her bestselling book, Remote Work Revolution: Succeeding from Anywhere, provides remote workers and leaders with the best practices necessary to perform at the highest levels in their organizations Her award-winning book, The Language of Global Success, chronicles the behind-the-scenes globalization process of a company over the course of five years Her “Managing a Global Team” is one of the most extensively used cases worldwide on the subject of virtual work She holds a patent for her widely adopted software simulation, Global Collaboration: Tip of the Iceberg Prior to her academic career, Tsedal spent ten years working for companies like Lucent Technologies and the Forum Corporation in various roles, including strategies for global customer experience, performance software management systems, sales force/sales management development, and business flow analysis for telecommunication infrastructures She currently serves on the board of directors of Brightcove, Brown Capital Management, Harvard Business Publishing, and The Partnership, Inc She also serves on Rakuten’s People & Culture Lab advisory board Tsedal received her PhD from Stanford University in management science and engineering, specializing in work, technology, and organizations Tsedal was named to the Thinkers50 list for making lasting contributions to management, was honored as a Stanford Distinguished Alumnus Scholar, and was a Stanford University School of Engineering Lieberman award recipient for excellence in teaching and research ... Cataloging -in- Publication Data Names: Leonardi, Paul M., 1979– author | Neeley, Tsedal, author Title: The digital mindset : what it really takes to thrive in the age of data, algorithms, and AI / Paul Leonardi and. .. Computers things Algorithms are implemented in software to tell the computer what to and how to it Data are what software programs use to decide what to tell the computer to Algorithms live at the intersection... a digital mindset We developed the idea of the digital mindset through our discussions with thousands of professionals, managers, and executives who provided us with insights into the ways of