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- Herausgeber: John Wiley & Sons
- Kategorie: Fachliteratur
- Sprache: Englisch
An in-depth, research-backed exploration of the answers to worker motivation
Based on an extensive global research program conducted in nineteen countries around the world surveying over forty-eight thousand people, The Archetype Effect delivers a new framework to understand and cater to worker motivators across roles, industries, and organizations. This book shows how workers can be classified into six major archetypes based on their motivations, and describes how recent disruptions, such as gig work, remote work and AI-assisted automation, are impacting worker motivators overall.
The archetypes discussed in this book include:
- Givers: Driven by helping others, thrive in collaborative environments
- Operators: Value stability and teamwork, prefer clear instructions and minimal risks
- Explorers: Seek variety, creativity, and new experiences, prefer flexibility and innovation
- Artisans: Motivated by mastery and pride in their work, prefer autonomy and focus on quality
- Strivers: Ambitious and career-oriented, motivated by recognition and advancement
- Pioneers: Visionary and entrepreneurial, driven by creating and often leading new ventures
The Archetype Effect is an enlightening read for anyone wanting a new way to understand what motivates them at work every day, or looking for a language to talk about current role, future choices, and career options with their firm. It is also for all leaders seeking to apply these insights across an organization to increase employee wellbeing, performance, and retention.
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Seitenzahl: 286
Veröffentlichungsjahr: 2025
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Table of Contents
Cover
Table of Contents
Title Page
Copyright
Prologue
Introduction: The Mystery and the Moment
noteSet
Chapter 1: Old Norms, New Norms
The Professional Management System
The Birth of Professional Management
Scientific Management
Pig Iron and Schmidt
The Hawthorne Experiments
What's Different About Knowledge Workers
The New Norms
An Explosion of Experiments
Notes
Chapter 2: The Six Archetypes
What Do You Want in a Job?
The Six Worker Archetypes
Archetypes Around the World
The Most Important Job Attributes
Using Your Archetype
The 10 Most Common Conflicts
Archetype Alliances
Notes
Chapter 3: Putting Archetypes to Work
Starting with the Data About Your Team
Training Team Leaders
Older Worker Archetypes
The New Tools
Who Was Your Talent System Built For?
Happy Work, Happy Life? Lessons from the Nordics
Notes
Chapter 4: Leaders
Alfred Sloan, Striver as Leader
Francesco Datini, Pioneer as Leader
What Do Leaders Want from Work?
Women Leaders
Mind the Gaps
Notes
Chapter 5: Energy, Stress, and Wellness
What Is Stressing People Out at Work?
Helping Workers Manage Their Stress
Should Firms Take a Stand on Political and Social Topics?
Optimism
Notes
Chapter 6: Older and Younger, Women and Men
Older Workers
Younger Workers
Women and Men
Passports and Ladders
Notes
Chapter 7: Good Jobs
Have We Hit Peak Good Jobs?
The Mystery Once More
Confident Archetypes, Fearful Archetypes
Governments Can Help
To Flexibility and Beyond
Solving the Mystery
Notes
Epilogue
Acknowledgments
About the Author
Index
End User License Agreement
List of Illustrations
Chapter 2
Figure 2.1 The intersection of archetypes and countries.
Chapter 4
Figure 4.1 Mix of Pioneers among executives compared to frontline workers in...
Guide
Cover
Table of Contents
Title Page
Copyright
Prologue
Introduction: The Mystery and the Moment
Begin Reading
About the Author
Acknowledgments
Epilogue
Index
End User License Agreement
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• • • THE ARCHETYPE EFFECT • • •
Unlocking the Six Types of Motivation at Work
JAMES ROOT
Copyright © 2025 by John Wiley & Sons, Inc. All rights reserved, including rights for text and data mining and training of artificial intelligence technologies or similar technologies.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
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Library of Congress Cataloging‐in‐Publication Data
Names: Root, James (Writer of Archetype effect), author.
Title: The archetype effect : unlocking the six types of motivation at work / James Root.
Description: Hoboken, New Jersey : Wiley, [2025] | Includes index.
Identifiers: LCCN 2024037111 (print) | LCCN 2024037112 (ebook) | ISBN 9781394295210 (hardback) | ISBN 9781394295234 (adobe pdf) | ISBN 9781394295227 (epub)
Subjects: LCSH: Employee motivation. | Employee morale.
Classification: LCC HF5549.5.M63 R65 2025 (print) | LCC HF5549.5.M63 (ebook) | DDC 658.3/14—dc23/eng/20240917
LC record available at https://lccn.loc.gov/2024037111
LC ebook record available at https://lccn.loc.gov/2024037112
Cover Design: Jon Boylan
Cover Image: © Bain & Company
Author Photo: Courtesy of Rebecca Helene Hoffmann
For TSR and SJR, my greatest motivations
Prologue
Jing is having a bad week. She is 28 years old, a product manager at a young fintech business‐to‐business payments company in Shanghai. It was the role she was convinced she wanted from the time she joined the firm one year ago. Before the promotion and role switch into product management, she worked on policy and regulation. This week was hard because she's come to learn that her new role demands constant refereeing between the engineers and the go‐to‐market team, both of whom are noisy fanatics for their own points of view. Plus, one of the founders had shown up to a meeting unexpectedly (both founders had a habit of doing this), dominated the conversation for 10 minutes, confused everyone with new directions that implied delays to a planned release date, and then left the meeting without looking back. Jing's entire time as a product manager has been tough.
Growing up in a Tier 2 city in Zhejiang province, she was always a high‐performing student. She could handle the 6.5‐day school week and the 7:30 a.m. to 9 p.m. days, with the heavily programmed curriculum of math, Chinese, sciences, written English, geography, oral English, plus club activities like PE and music. Her father, who works for the local government, and her mother, a high school chemistry teacher, had sacrificed to get her into an academic (versus vocational) high school in their city and to hire the tutors required to keep her grades high. They vested many of their private hopes in Jing, an only child. Against almost impossible odds, making sacrifices of her own to study around the clock, she won a place at the nearest C9 college (equivalent to the Ivy League in the United States and the Russell Group in the United Kingdom) – Zhejiang University in Hangzhou.
She was recruited on graduation, along with a select few of her classmates, as an analyst in the e‐commerce business of Alibaba. Alibaba's headquarters are in Hangzhou; the firm has close ties to the school. She found the “996” working norms (9 a.m. to 9 p.m., six days a week) to be demanding and exhausting, but she wanted to succeed. As someone who had always been at or near the top of her class at school and university, it was a shock when her first performance review said she was in the middle 60%, below the top 30%. Her parents worried too. She was less than three hours away from her home town, but hardly ever made it back for a visit.
She fought her way into the top 30% at her next performance review (although slipped back to the middle group in the following cycle), was promoted twice in the first three years, and received a special award for a team project that launched a new solution for the key opinion influencer program.
None of those achievements and recognitions gave her quite the sense of satisfaction and achievement she thought they would. Her whole life, it felt, she'd been driven to hit the next milestone, the next exam, to take the next win. Just over three years into a job at Alibaba that calibrated her performance against her peer group every six months, that demanded everything she could give in terms of hours and energy, she was starting to wonder if the role was right for her.
The most satisfaction she'd had recently was organizing a two‐day customer event for dozens of big consumer brands to come in to Hangzhou, talk about their plans on the Alibaba platforms, and listen to a stream of Alibaba team members tell their stories about future improvements and opportunities. She wasn't in the spotlight, but behind the scenes she was the one making sure the production went smoothly and that all the speakers performed well.
She had also taken on a role as coordinator for onboarding the analysts (people like her, four years ago), which involved planning their training agenda, making sure they had mentors, and ensuring they were assigned to suitable projects in the first year. She thoroughly enjoyed this role and spent more time on it than she was notionally supposed to.
Suddenly, the unimaginable. She lost her job. In the face of a slowdown and competitive missteps, in the middle of COVID‐19, Alibaba started a round of layoffs in 2022 that resulted in 20,000 people leaving the firm (another 20,000 were let go in 2023). Jing was devastated.
No matter how much her friends told her the layoff had nothing to do with her, the sense of failure and rejection was overwhelming. Worse than that, she felt failure and rejection about a job she was not even sure she was enjoying any more.
It took her a week to call home and break the news. Her father said she should focus on joining another prestigious company, with a good income and financial stability. Her mother said, “Look at me, I don't make a lot of money as a teacher, but I work so hard because I love to see my students doing well in my class and after they leave. Some of them come back years later to thank me.”
Priority one for Jing was finding a new job. Alibaba had paid well, and with the help of her parents she had recently put down a deposit on an apartment. With her background and experience, the job search proved easier than she expected. The payments firm was not prestigious in the way her father wanted; it was in Shanghai, farther from her home city; it did not pay as much as Alibaba; but they valued her skills in analytics, data management, and customer engagement, plus some experience working with engineering teams. They saw a path for her in product management, which for Jing and many like her, was considered a dream job. She thought that being a bigger fish in a small pond might be good for her career.
In her first few months at the new firm, she was back to the old Jing: motivated to deliver, working around the clock, proving to new colleagues that she could be trusted with the product manager promotion on the timeline they had agreed to.
Right on schedule, she was promoted. During her time in policy and regulation she had met a lot of people at the young firm but had not worked directly with the engineering teams. It was now clear to Jing that the tensions between the various groups, compounded by unpredictable founder interventions, were going to make her new role very challenging. She was not afraid of the hard work, and she still believed the product they were building was a good one, but she was starting to wonder why exactly she wanted the product manager job in the first place.
Introduction: The Mystery and the Moment
The Mystery
Why do you go to work? Who are you when you get there?
No, really. These are serious questions. How about the Gen Z marketer in the cubicle next to yours (if you still have a cubicle) – why does she go to work? Or the man in human resources who led your onboarding a couple of years ago? The engineer who drove your subway train this morning? The barista who made your coffee? The construction worker who built the office you are sitting in? The chief executive officer (CEO) of your firm, whom you have never met but seen on a few all‐hands Zoom calls? What about the board director who voted to appoint that CEO?
Is it likely that each of these workers will have the same answers to these questions?
Not very likely. While there are important similarities in work motivation that cut across countries, job types, age groups, and genders, it turns out to be the differences that are most striking.
My colleagues at Bain and I have been talking to workers in 19 countries from all corners of the world, more than 48,000 of them so far – young, old; male, female; highly educated, much less educated; high, middle, and low income; care workers, service workers, manual workers, administrative workers, knowledge workers; workers in developed countries with aging workforces like Japan and Italy, workers in developing markets with young workforces like India and Nigeria. It is the largest and most global body of research on this topic that we know of.
Of course there are executives in the sample. They always attract attention. Far outnumbering the executives, we have listened to agricultural workers, construction and maintenance workers, customer service reps, food service workers, manufacturing workers, office administrative workers, resource extraction workers, retail salespeople, transportation workers, warehouse workers, architects, accountants, data analysts, engineers, finance professionals, information technology (IT) professionals, business consultants, marketing professionals, scientists, private security workers, legal professionals, graphic designers, academics, artists and entertainers, nurses and carers, doctors, journalists, law enforcement workers, librarians, workers serving in the military, psychologists, public officials, religious workers, social workers, teachers, travel guides … you get the idea. We made it a priority to hear from the full range of workers in all of the markets.
The main thing we observed is the rich diversity of motivations that bring people to work every day. Everyone has a personal algebra of motivation. Its roots may run deep, back to childhood, listening to your parents' dinner‐time conversations about money and jobs; to school, the values it instilled and the skills it developed; to your early working experience, with a great boss or a horrible boss; to your current role. Or perhaps your motivation at work reflects some aspect of your intrinsic nature, however you choose to define that.
Six Worker Archetypes Emerge
Motivations might seem random at the individual level, but at scale, clear patterns emerge. The global research delivered something distinctly new. Six worker archetypes describe virtually all 48,000 individuals we surveyed. Two of them care mainly about relationships at work (Givers work to help others thrive; Operators like to have colleagues as friends but prefer to keep their heads down at work and take no risks).
Two of them care mainly about learning and growth (Explorers are highly motivated to try new things; Artisans want to achieve mastery of their domain).
The third pair care mainly about achievement at work (Strivers plan ahead and value the recognition of promotions; Pioneers want to change the world in some way and are comfortable taking risks to do so).
This insight about motivations arrives at a time of considerable complexity at work. There are talent shortages and talent mismatches in many firms. The workforce is shrinking in most developed economies and is on a similar path even in middle‐income countries. And there are three trends, possible thanks only to technology, combining to change the relationship between individuals and firms.
Gig Work
First, gig work surged in prominence over the last 15 years, as platforms like Uber, DoorDash, Upwork, and their numerous global equivalents scaled up. We've seen this model before. Piecework has its origins in the guild system of medieval Western Europe and accelerated with the industrial revolution. In the late nineteenth century, the majority of factory workers earned piece rates: they were paid a fixed amount for each item made and were not employees of the firms they manufactured for. This model fell out of fashion as firms brought more and more activity in‐house and worker rights improved during the twentieth century. By 2003, pre‐smartphones, less than 5% of American workers were paid this way. Now, the idea is back, with a new name: the gig economy.
Today, there may be as many as 60M workers in the United States who are current or recent gig workers, being paid piece rates.1 If that seems like a big number, consider China, where there are close to 200M gig workers, more than the entire working population of the United States and the United Kingdom combined.2 This is not simply due to the rise of platform companies for ride‐hailing and deliveries. It is also because the manufacturing base in China that used to offer full‐time employment contracts to their assembly‐line workers has shifted substantially to short‐term contracts and more contingent work. There is a wide gap in job satisfaction between lower‐income contract workers and their full‐time counterparts doing exactly the same job. Ask the gig workers why, unsurprisingly, they cite income insecurity as one driver of lower satisfaction; the other is having little chance to make friends at work.
Flexible Work
Second, flexible work arrangements had been moving into the mainstream for several decades prior to the COVID‐19 pandemic, when many of us found ourselves in a forced experiment about where and when work could get done.3 It's hard now to find consensus among individuals or firms on the future model of working in the office/at home/somewhere else. The global workers we have studied are perfectly divided: one quarter would like to work from home all the time, one quarter never want to work from home again, and the remaining half are divided across one, two, three, and four days in the office.
Automation Anxiety
Third, automation anxiety is experiencing another spike, with the arrival of a new generation of artificial intelligence (AI) tools and applications. Firms are perpetually learning to do more with fewer people. The last 40 years of productivity gains have come from multiple sources: self‐managing teams, the hollowing out of middle management, outsourcing, but above all, technology investment.
The anxiety is a long‐running story. In Modern Times (1936), Charlie Chaplin's character is (unsuccessfully) fed his lunch by a machine as he tightens screws on an ever‐accelerating assembly line. The message is clear: artisanal manufacturing jobs are being destroyed by rampaging automation. In the 1980s, with another wave of interest in AI and the increasing presence of personal computers, the zeitgeist's anxiety about job‐killing machines appears in Blade Runner (1982) and The Terminator (1984). Soon after the launch of Apple's Siri, Spike Jonze's her (2013) presaged the twisting ambiguities in human relations with AI‐powered virtual assistants.
These three tech‐enabled disruptions have emerged at a moment in social history when many workers feel more able to be themselves at work. There are of course differences from country to country, and from work culture to work culture, but the days of toeing the line, of meekly accepting the bad assignment, of sucking it up, if not gone, are certainly in retreat. It's not perfect. Experts remind us that there is still plenty of “covering” at work, when employees are concerned about being judged, or discriminated against, for their unique identities, so they start to conceal or obscure their thoughts and opinions in an effort to fit in. But by comparison to a generation ago, let alone two, we have far more permission to be who we truly are at work.
The Myth of the Average Worker
The talent chessboard includes full‐time employees, robots and AI of many kinds, contractors (often long term), gig workers, and employees of other firms in your ecosystem. The edges of the firm are becoming more porous. The ideas of a workplace and a worker are more fluid than they have been in 100 years. It's complicated.
Today, with these work disruptions and changes in social norms, one conclusion we can draw with confidence is that there is no longer such a thing as an average worker.
This begs the main question of this book – why should firms expect that having one way to do recruiting, one compensation model, one career path system, and one performance management system will allow all their people to bring their best selves to work?
The concept of de‐averaging is nothing new. Customer segmentation has been mainstream business thinking for decades (there are even examples from the nineteenth and early twentieth centuries). The notion that buyers have distinct preferences that can be satisfied with distinct offerings and that they react to distinct messages is conventional. For just one example, the profitable growth and share gain of American Express from the early 1990s, after a period of stagnation, was built on a multiyear sequence of expansions from the original Green charge card to different spend tiers of charge card (Gold, Platinum) to credit cards to prepaid cards to co‐branded credit cards with hotel chains and sports teams to cards for seniors and for students to cards with gift rewards and with cash rewards to corporate cards for purchasing departments and for small businesses – each new offering carefully designed for its distinct customer.
De‐averaging has gone into overdrive in the last 20 years, with social media, search, location tracking, and online payments providing the fuel for acceleration. We take for granted how much Google or Amazon or Instagram or Tencent or Alibaba or Little Red or ByteDance or Flipkart or Grab or Careem or Naver or Kakao or Line know about us as consumers and shoppers. For the most part, while there are those who opt out, many of us seem happy to offer our personal information in return for more personalized communications and products.
The mystery is, why have we not applied this same thinking to our workers? Why do the firms who want to sell us their products, or sell our profiles to advertisers, know so much more about what motivates us than the firms we actually work for?
The prevailing ideas about the relationship between worker and firm were forged in a different world than today's, one where workers were viewed mostly as factors of production in the machine of enterprise. Today's firm requires a new mental model, one that humanizes the way we think about work and workers.
If we want all our workers to bring their best selves every day, we have to de‐average them, not only on the basis of their skills but on their motivations. And from that understanding, build good jobs and career paths around what they want, not only what suits our systems best.
The Moment
This mystery, like all mysteries, must be seen in its context.
In sector after sector, insurgent firms are creating new ways to meet customer needs and trying to tilt the economic structure of an industry away from historic leaders.
Incumbent firms, with customer assets nurtured over decades, with systems and processes built for scale, can find it hard to be as fast and as responsive to customers as the younger firms with just a fraction of their history; but they are trying, many are succeeding, and more will.
The winning playbook is changing, which should come as no surprise. Looking back through the last several hundred years of business history, since global commerce began in earnest, the idea of the firm has evolved through a series of what we can now discern as definable eras: periods when particular strategies, corporate forms, financing sources, and styles of management are the dominant norm.
The primary trigger of a move from one era to another is the declining cost and increasing speed to move products, money, and information (for example, from horses to ships to railroads to airplanes; from mail to telegraphy to the Internet; from coins to checks to digital payments). Another trigger comes from the ratcheting expectations of consumers for more value and convenience. And there is always the genius of entrepreneur‐leaders who find new solutions to the old problems and are willing to go to war with the status quo to serve customers better.
The New Era
Here in the mid‐2020s, we are already in transition from one era of business to the next. Inevitably, winning strategies have to embrace new truths.
The Trade‐Off Between Scale and Customer Intimacy Is Over
The first of these new truths is that the traditional trade‐off between scale and customer intimacy is no longer a trade‐off. Insurgents defy the sacred strategy text of the 1980s,4 which laid down that your firm can either be low cost or be differentiated, but not both. How do they defy it? By being both. They see no problem with pursuing the benefits of massive scale (achieving low cost) at the same time as delivering previously unimaginable degrees of customer intimacy (being differentiated). Even the newly termed hyperscalers should really be called the hyperscaler‐hyperintimates, because all of them are both.
Algorithms like Amazon Recommendations or Netflix Suggestions typify the booming capability to offer the benefits of scale (the low cost of Amazon's procurement, warehousing, and distribution network; Netflix's investment in content) combined with extremely high degrees of personalization or customer intimacy. Starbucks offers an intimate relationship with your barista, who knows your name and your daily order, plus the scale‐driven benefits of the loyalty program and the mobile ordering app. We are a long way from Henry Ford pursuing the scale benefits of continuous assembly for the Model T by eliminating customer choice completely (“any color, so long as it's black”).
New Ways to Manage Workers
The second new truth is about us, the workers.
More work is being automated. More work is being outsourced to ecosystem partners. More firms are testing new methods of working, often with self‐managing teams setting their own objectives. More firms want to push decision‐making and accountabilities down to the front line, where the organization meets the customer. There is more use of gig workers and contractors to manage capacity and for specialized expertise, more cross‐functional teaming, more peer‐to‐peer information flow, more continuous feedback rather than once‐a‐year top‐down performance evaluations, more team‐based incentives.
With more automation, more outsourcing, and more self‐managing teams, head count at the typical firm will fall, all other things equal. Just as measures of plant asset efficiency became less meaningful in a world of outsourced manufacturing, traditional measures of overhead efficiency are losing relevance in the era of scale insurgency. Long‐held ideas about appropriate spans and layers are being challenged. In the parts of the business using self‐managing teams, for instance, the proper span might not be the usual 6 to 8, but 20, or why not 30?
The role of the generalist professional manager, enshrined at the center of almost all large organizations for the last 100 years, is diminishing, not to nothing, but at least relegated in comparison to the mission‐critical roles – those roles that truly deliver the firm's promise to its customers.
Winning insurgents do not organize around professional managers or use spans and layers as their default technique to handle growth. Insurgents value individual contributors just as highly as managers, and some (e.g. Tencent5 and Shopify,6 two of numerous examples) organize career paths around the choice to become a manager or not.
Jensen Huang, founder and CEO of NVIDIA, the platform computing firm powering much of the current AI advance, has somewhere between 50 and 60 direct reports.7 His logic is that CEOs can have a large number of reports because the people who report to a CEO require the least amount of oversight, leaving CEOs with more bandwidth than other managers. This is a very different way of leading than the traditional “6 to 12” direct CEO reports that became the norm 30 years ago.
We have moved on. We are well advanced into the first phase of the era of scale insurgency. With that move, the norms of talent management are going to change.
This is the moment, and as it meets the mystery, we are seeing an explosion of experiments in people management.
The experiments still have a long way to go before we settle on a set of new norms. The playbook is always being tinkered with and adjusted for special situations. This can be exciting for those in the labs designing the experiments and for the subjects, all of us who work. In one regard, though, the designers in the human resources (HR) labs have gone too far and need to reset.
It is now the conventional wisdom in some parts of the world that what matters above all else is for humans to find their meaning and purpose in their work.
Our research tells a different story. The search for individual meaning and purpose through work, or at work, is very important … but only to some workers. An extreme version of this search is described in Professor Carolyn Chen's 2022 book Work Pray Code.8 Chen explores how Silicon Valley tech companies bring religion into the workplace, replacing traditional forms of worship, blurring the line between work and religion, and transforming the nature of spiritual experience in modern life.
The workers she studies, many of whom are engineers, entrepreneurs, and founders at tech firms, exhibit behaviors associated with religious devotion, such as long hours, zealous commitment to their work, and a sense of mission or calling. Work satisfies their needs for belonging, identity, purpose, and transcendence that religion once met. This must be sensationally satisfying for them.
It is true that in some developed, Western societies including the United States, there is a well‐documented retreat from organized religion and from the joining of groups and clubs that historically promoted trust and community cohesion. There is a rise in loneliness and isolation. A vacuum has appeared in some people's lives that work could step in to fill.
But we should not make sweeping, averaged‐out assumptions about why people go to work and what they are looking for when they get there. Their answers vary so much. For many, it is to provide for the needs of themselves and their family. For others, it's to be with friends and enjoy camaraderie. For others, it's about learning and exploring through work. For others, it's about pursuing milestones and being recognized. None of these motivations should be considered somehow “higher” or “lower” in a hierarchy than the others – they are simply the ones that mean most to that worker at that time in their life. We risk allowing what may be a WEIRD (Western Educated Industrial Rich Democratic) perspective about meaning and purpose at work to obscure the reality for the great majority of workers.
Even if we stay in the United States and pull back the camera a little from the intensely narrow confines of Silicon Valley, we will find Beverley, a 45‐year‐old senior manager at a telecommunications company, who puts it this way: “Honestly, my job is just a job. My meaning and purpose come after I'm done with my work.”
