David Green: The best HR & People Analytics articles of June 2025
AI is reshaping industries, companies, workforces and the way we work. As with previous industrial revolutions, this will mean that companies will need fewer people to perform some tasks, and more people to undertake other (including many new) tasks. Amazon CEO, Andy Jassy, addressed this very topic in a recent message to Amazon’s employees while recent remarks by Dario Amodei, CEO of Anthropic, that AI could wipe out half of all entry-level white-collar jobs — and spike unemployment by 10-20% in the next one to five years have been widely reported. The truth is that it is probably too early to judge how this will play out over time, and whether this industrial revolution will differ from all others in history by being a net destroyer rather than a net creator of jobs. Whatever direction we go in, it’s clearly going to be a disruptive few years ahead. HR needs to play an active role in terms of leading organisational transformation, redesigning work, upskilling the workforce, building a culture of continuous agility, and transforming the HR function itself. HR can be the crucial link ensuring employees can thrive alongside technology.
This month’s collection of resources addresses many of these topics, and if I could highlight one in particular, it would be a new Stanford paper on the Future of Work with AI Agents, which amongst other findings lays out a framework for human-agent collaboration. Enjoy!
This edition of the Data Driven HR Monthly is sponsored by our friends at Draup
Prepare your workforce for the AI Era
Prepare your workforce for the AI era | Strategic HR Insights | Etter
Etter is Draup’s flagship AI transformation engine designed to help enterprises systematically reimagine job roles, skills, and workforce structures in the AI era. Built as an adaptive, modular solution, Etter integrates proprietary labor intelligence, enterprise data, and market signals to provide hyper-contextual, execution-ready recommendations for HR and business leaders.
Etter’s methodology is anchored on three foundational pillars:
Draup Models: This includes the Role Disruption Index, Workload Disaggregation, Skills Evolution, and Talent Density Models to identify which roles are most susceptible to AI disruption, what tasks can be automated or augmented, and how skills are shifting across industries. It generates AI-ready job descriptions and quantifies AI’s productivity and time-saving impacts at a task level.
Agentic Workflows: These simulate real-time strategic decisions—like reskilling paths, CoE creation, and role redesign—tailored to the organization’s structure, metrics, and technology ecosystem. They dynamically adapt to changes in business strategy or external environments such as regulatory shifts.
Sustainability Engine: Ensures responsible transformation by embedding fairness, inclusion, and long-term workforce resilience into every recommendation. Real-time dashboards track transformation maturity and enable scenario planning to balance automation with talent retention.
The document details advanced models like Tech Stack Mapping, Similar Role Identification, and Location Optimization to help organizations design AI-augmented ecosystems. It also outlines the data needed—from job descriptions to transformation signals—and a 4–6 week pilot approach to assess 10–12 roles for quick wins.
Etter moves beyond theoretical AI strategy to deliver measurable, role-level change—empowering CHROs, CTOs, and transformation teams to redesign workforces that are future-proof, agile, and ethically AI-enabled. Learn more about Etter here.
To sponsor an edition of the Data Driven HR Monthly, and share your brand with more than 140,000 Data Driven HR Monthly subscribers, send an email to dgreen@zandel.org.
Invitation: If you are a people analytics leader, participate in the 6th annual Insight222 People Analytics Trends survey...
The Insight222 People Analytics Trends study is now in its sixth year, and has grown to be the biggest and most important annual study in the field of people analytics. The survey for 2025 is open, and is intended to gain insights into: (1) HR's role in shaping your AI strategy. (2)AI usage & adoption (3) Upskilling and enabling factors, and AI outcomes
If you are the people analytics leader at your company and would like to participate in the People Analytics Trends study for 2025, click this link and please join over 400 companies and complete the survey by the new closing date of July 6.
JUNE ROAD REPORT
A trio of highlights from June:
I finally got to attend TALREOS, which is curated and organised annually by Deborah M. Weiss and Derek Gundersen at Northwestern in Chicago. It proved to a memorable three days, with 200 participants and plenty of learning, collaboration and networking. I had the privilege of speaking on two panels. The first, hosted by the inimitable Ian OKeefe, and also featuring Dan Trares, Nicholas Garbis and Cole Napper, discussed how to build a successful people analytics function. The second, which I moderated, and featured Dean Carter, Courtney McMahon and Ryan Colthorp, discussed the critical topic of how to create and measure the value of people analytics.
Participants at TALREOS 2025
From Chicago, it was a short hop to Toronto for the first ever Canadian Peer Meeting for 40 members of the Insight222 People Analytics Program, which was hosted by Don Dela Paz and the team at RBC. Speakers over the two days included Don as well as Ujjwal Sehgal, Maria Grazia (Grace) Guma, Rachel Beaulieu-Salamido, Kunal Thakkar, MS, PMP, Rob Dees, Travis Windling, Patrick Joseph Tuason, David Holmes, Foteini Agrafioti and Arjun Asokakumar, MMA, CHRL.
Participants at the Insight222 Peer Meeting at RBC in Toronto, June 2025
Finally, last week saw David Duewel and his team at BT Group host a Peer Meeting for more than 60 European members of the Insight222 People Analytics Program in London. Speakers over the two days included: Elaine Bergin, Julie-Anne Sivajoti, Fiona Vines, Stefaan De Keyser, Julien Legret, Stefanos Adamantiadis, Nick Hudgell, Mariana Allain Carrasqueira, Olly Britnell and Ashar Khan.
Across all three events I left with a number of reflections including: (1) When people analytics is closely with business strategy it delivers exponential value. (2) AI is elevating and disrupting people analytics in equal measure. (3) Employee listening is the 'human' face of people analytics.
Just to highlight to my Indian network and readers that I'm speaking at TechHR India 2025 in Delhi, which is organised by People Matters, at the end of July. I'll be delivering a keynote on July 31 after a pre-conference workshop on July 30 on The Science of Better Decisions - I hope to see some of you there.
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Enjoy reading the collection of resources for June and, if you do, please share some data driven HR love with your colleagues and networks. Thanks to the many of you who liked, shared and/or commented on May’s compendium.
If you enjoy a weekly dose of curated learning (and the Digital HR Leaders podcast), the Insight222 newsletter: Digital HR Leaders newsletter is usually published every other Tuesday – subscribe here – and read the latest edition.
HYBRID, GENERATIVE AI AND THE FUTURE OF WORK
IBM - 5 Mindshifts to Supercharge Business Growth
It’s no longer a question of whether to use AI—but where AI will give you the greatest lift and how you should redeploy your people to accelerate growth.
IBM’s recently published 2025 CEO Outlook is required reading for all chief people officers and heads of people analytics. The study highlights that talent recruiting and retention is ranked #2 in the top challenges of CEOs (see FIG 1). The report highlights five mindshifts to supercharge growth in the age of AI – all of these apply for HR too: (1) Make courage your core (“The power and potential of AI is pushing organizations to transform faster, even if they’re not sure what exactly what that entails.”) (2) Embrace AI-fuelled creative destruction (“Establish metrics and monitoring systems to assess AI effectiveness and create a culture of accountability.”) (3) Cultivate a vibrant data environment (“Start with data. If CEOs get their data environment right, they can accelerate change, impact, and stakeholder value.”) (4) Ignore FOMO, lean into ROI (“Only 25% of AI initiatives have delivered expected ROI—and only 16% have scaled enterprise-wide. Fail fast and move on.”) (5) Borrow the talent you can’t buy:
CEOs are looking to reskill the talent they already have (build), hire the talent they need (buy), add AI assistants and agents to workflows wherever they can (bot), and rely on partners to borrow what they can’t find another way (borrow).
FIG 1: Top CEO Challenges 2025 (Source: IBM Institute for Business Value)
MCKINSEY - Seizing the agentic AI advantage
To realize the potential of agents, companies must reinvent the way work gets done—changing task flows, redefining human roles, and building agent-centric processes from the ground up.
According to McKinsey, there is a ‘GenAI paradox’ with nearly eight in ten companies reporting they are using Gen AI—yet just as many reporting no significant bottom-line impact. To break out of this morass, the authors argue that Agentic AI—autonomous, goal-oriented systems—is the true game-changer, poised to automate complex processes and fundamentally transform workflows. For HR leaders guiding workforce transformation, the core insight of the study is profound: successful integration means redesigning work around AI agents, not merely layering AI onto old processes. This strategic pivot promises enhanced operational agility, accelerated execution, and newfound organisational resilience. However, realising this potential hinges on critical human factors. Driving adoption and earning trust are paramount, alongside robust governance for agent autonomy. This necessitates a shift from fragmented AI initiatives to strategic, cross-functional programs, coupled with significant upskilling across the workforce. While the article doesn't explicitly detail the Chief People Officer's role, the implications are clear: HR must champion the human-AI partnership, ensuring ethical deployment and preparing talent for this profound evolution of work. Kudos to the authors: Alexander Sukharevsky, Dave Kerr, Klemens Hjartar, Lari Hamalainen, Stéphane Bout, and Vito Di Leo, with Guillaume Dagorret.
HR must champion the human-AI partnership, ensuring ethical deployment and preparing talent for this profound evolution of work.
FIG 2: Maximising value from AI agents requires process reinvention (Source: McKinsey)
STANFORD - Future of Work with AI Agents: Auditing Automation and Augmentation Potential across the U.S. Workforce Project | Paper | COBUS GREYLING - The Future of Work with AI Agents — Insights from a Stanford Study | SERENA HUANG - AI Agents Are Ready to Work With Us, but Are We Ready to Work with Them?
[As] AI agents start to enter the workforce, key human competencies may be shifting from information-processing skills to interpersonal and organizational skills.
For anyone looking to understand how the AI agents might shape the future of work, I recommend diving into a new study from Stanford University – warning, you may get lost as the paper is absorbing! The paper presents a framework, the Human Agency Scale (HAS – see FIG 3), which has a five-level scale from H1 (no human involvement) to H5 (human involvement essential) and is designed to help quantify the desired level of human involvement across various tasks. Other findings from the study include: (1) Lack of trust (45%) is the most common fear workers have about AI automation in their work. (2) Workers want automation for low-level and repetitive tasks with 46.1% expressing positive attitudes towards AI automation. (3) Workers generally prefer higher levels of human agency, potentially foreshadowing frictions as AI capabilities advance. Kudos to the authors of the Stanford Study: Yijia Shao, Humishka Zope, Yucheng Jiang, Jiaxin Pei, David Nguyen, Erik Brynjolfsson, Yang Diyi. I also recommend the shorter and more accessible summaries of the key findings from the paper and their potential implications by Cobus Greyling and Serena H. Huang, Ph.D. (see links above) as well as Ross Dawson (see here).
FIG 3: Levels of Human-Agency scale (Source: Stanford University, Shao et al)
PETER CAPPELLI AND RANYA NEHMEH – Hybrid Still Isn’t Working | BRIAN ELLIOTT - When Academics Ignore Research (and Reality)
The contentious debate about the merits – or otherwise – of hybrid work continues as these two articles demonstrate. Firstly, in their article for Harvard Business Review, Peter Cappelli and Ranya Nehmeh present the case that hybrid is harming collaboration, deepening social isolation, weakening culture, and is leading to lower performance. They argue that this is primarily because of the way that many companies manage hybrid and remote workers: “You can’t effectively manage remote and hybrid workers using the same methods you did when employees were still all together in the office.” They then suggest eight strategies including: creating and enforcing rules, revamping performance appraisals, and establishing in-office anchor days. Brian Elliott, who along with the likes of Nick Bloom (see latest WFH Research here) and Annie Dean (listen to my podcast discussion with Annie on using behavioural science for distributed working) is one of my go-to experts on hybrid and distributed work, provides a 'teardown' (his words!) of Hybrid Still Isn’t Working. He examines some of the research cited in the HBR article and compares this to the available data e.g. contrary to everyone going back to five days in the office, Brian highlights Flex Index data (see FIG 4) showing that hybrid dominates at 43% of firms. Brain also highlights that the article ignores research on return to office mandates such as: “no financial benefit, no stock market boost, but declining engagement and retention issues among experienced talent and women at 3X the rate of men.” I’ll let readers make their own minds up but recommend that any companies considering a change in their approach analyse their own data and make considered decisions. As Brian concludes in his article:
Instead of debating days per week, focus on what drives results: clear team goals, intentional collaboration rhythms, and management practices that work anywhere. The magic isn't in the location—it's in how well you lead distributed teams doing complex work.
FIG 4: Structured Hybrid continues to dominate as the preferred work model for US companies (Source: Flex Index)
PEOPLE ANALYTICS
MICHAEL ARENA AND AARON CHASAN - The social signals behind employee retention
Research has long shown that employees at the center of an organizational network—those with many active connections—are 24 percent less likely to leave.
In their article, Michael Arena and Aaron Chasan highlight an important insight: employee connection, not just engagement, is the true bedrock of retention: “In today’s networked workplace, social withdrawal is often the first—and most reliable—indicator that someone’s already halfway out the door.” For HR to genuinely impact business performance and employee experience, we must leverage social signals to build robust internal networks. The authors outline four high-impact ways HR can proactively employee connection and significantly reduce attrition: (1) Utilise network analysis: Identify early flight risks by spotting employees with few or declining connections. (2) Facilitate connection moments: Deliberately create opportunities for interaction, especially in hybrid settings, using tools like interest-based matching. (3) Support relationship-rich teams: Encourage cross-functional initiatives and invest in psychologically safe team cultures. (4) Routinely pulse central employees: Their engagement profoundly influences the entire network.
In today’s networked workplace, social withdrawal is often the first—and most reliable—indicator that someone’s already halfway out the door.
PIETRO MAZZOLENI AND ERIC BOKELBERG - The right owner, the right impact: mastering people analytics accountability
Clear ownership ensures that sensitive data is handled responsibly, analytics initiatives are aligned with business priorities, and AI solutions deliver trustworthy, actionable insights.
Pietro Mazzoleni and Eric Bokelberg provide guidance on mastering people analytics by defining clear ownership – a cornerstone for unlocking business value from people data. Many organisations falter due to unclear accountability, risking inefficiencies and mistrust. Pietro and Eric outline four essential domains for assigning ownership: (1) Data Governance. (2) Stakeholder Management. (3) Data & AI Platforms. (4) Functional AI. They then recommend ownership across five key functional roles: the People Analytics Team, CHRO and HR Leadership Team, Business Function Leaders, Chief Data Office, and IT/AI Technology Team. By aligning accountability with expertise, HR leaders can ensure data is handled responsibly, initiatives drive strategic priorities, and AI delivers trustworthy, actionable insights, ultimately generating real business impact.
LUDEK STEHLIK AND COLE NAPPER - Beyond Prediction: Exploiting Organizational Events for Causal Inference in People Analytics | KEITH MCNULTY – R for People Analytics | MARIA NOLAZCO MASSON - The People Analytics Staircase | PATRICK COOLEN – People Analytics Spotlight: Oliver Kasper, Giovanna Constant, and Marcela Mury
In each edition of the Data Driven HR Monthly, I feature a collection of articles by current and recent people analytics leaders. These are intended to act as a spur and inspiration to the field. Four are highlighted in this month’s edition: (1) Ludek Stehlik, Ph.D. and Cole Napper examine one of the Holy Grails of people analytics – understanding causality, including exploring why randomised experiments (see FIG 5) are the ‘gold standard’ (but rarely feasible), and how real-world organisational events can be used as natural experiments. (2) Keith McNulty offers a set of open source materials for a 2-day course on explanatory technical methods in People Analytics using R. (3) For anyone early in their people analytics career and looking to accelerate their development, I recommend diving into Maria Nolazco Masson’s excellent series: The People Analytics Staircase, which provides a practical framework to advance in People Analytics, from foundational concepts to deep strategic dives. (4) Finally, in this section, I recommend checking out Patrick Coolen’s excellent People Analytics Spotlight Series, which to date has insights from Oliver Kasper, Giovanna Constant and Marcela Mury.
FIG 5: Randomised controlled trial (Source: Simply Psychology)
THE EVOLUTION OF HR, LEARNING, AND DATA DRIVEN CULTURE
MICHELLE CHAN CROUSE, TED MOORE, ANNA PENFOLD, BRAD PUGH, AND ALISON HUNTINGTON - The CHRO of the future: How CHROs and organizations can prepare for what’s next
The CHRO role is no longer just about managing human capital—it's about unleashing the potential of your workforce, whether they’re a human or a bot.
This report by Russell Reynolds Associates dissects the evolving role of the Chief Human Resources Officer (CHRO) and provides a helpful guide on how the CHRO can lead workforce transformation. It is structured into three chapters: (1) How the CHRO role has changed: highlighting the CHRO's transition from operational support to a strategic leader, now deeply embedded in C-suite succession, transformation, and even technology, crucial for organisational stability. (2) Who will be the CHROs of the future? capturing the need for a new CHRO profile, demanding broader strategic, technological, and operational experience beyond traditional HR, coupled with acute emotional intelligence to navigate complex stakeholder landscapes. This chapter also highlights new roles and responsibilities that may emerge in the HR function including a ‘Chief HR Bot’ reporting to the CHRO and responsible for data-driven decision making. (see FIG 6). (3) How CHROs and organisations can prepare for the future: with actionable guidance, emphasising the responsible integration of AI, significant investment in HR data and analytics, and clear communication around workforce transformation, ultimately elevating HR's strategic influence. This analysis by Michelle Chan Crouse, Ted Moore, Anna Penfold, Brad Pugh and Alison Huntington reinforces that the future CHRO is a critical architect of business success, leveraging data and strategic acumen to shape adaptive, resilient organisations.
FIG 6: Potential roles in the HR team of the future (Source: Russell Reynolds)
DAVE ULRICH, DICK BEATTY, AND PATRICK WRIGHT - What Competencies Define an Effective HR Professional? Past, Present, and Future
In their article, Dave Ulrich, Dick Beatty, and Patrick Wright analyse a number of different HR competency models including their own, which has been developed through eight studies since 1987 across 120,000 participants. Their analysis leads them to recommend expected and emerging competencies across six HR skills domains (see FIG 7): (1) Accelerate business, (2) Advance human capability, (3) Make change happen, (4) Use GenAI and analytics for information, (5) Create organisation culture, and (6) Demonstrate personal proficiency. For HR leaders and professionals looking to learn more, I recommend learning about the Global HR Learning Experience programthat Dave, Dick and Patrick have developed.
FIG 7: Expected and emerging competencies for HR professionals (Source: Dave Ulrich et al)
WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS
JEN STAVE, RYAN KURT AND JOHN WINSOR – Agentic AI is Already Changing the Workforce
AI agents are fast becoming much more than just sidekicks for human workers. They’re becoming digital teammates—an emerging category of talent.
The advent of Agentic AI is no longer a distant future; it's here, fundamentally reshaping our workforce. In their article, Jen Stave, PhD, Ryan Kurt and John Winsor explain that these autonomous, goal-oriented AI systems aren't just tools; they're becoming digital colleagues, capable of complex tasks and decision-making. For HR and business leaders, this demands a seismic shift in how we approach talent, roles, and organisational design. The article outlines seven critical actions to help your organisation thrive: (1) Map work tasks and outcomes (“Deconstruct each role or project into its component tasks and outcomes.”) (2) Assess AI capability. (3) Integrate your hybrid team (“Develop a hybrid-workforce strategy to define which tasks AI will own, which tasks people will own, and how the escalation of problems should happen.”) (4) Redesign your business and workforce model (“Envisioning new ways to procure and deploy talent, including full-time employees, temporary hires, freelancers and AI.”) (5) Set legal and ethical ground rules. (6) Capture value continuously as it evolves. (7) Remain human-centric (“AI reduces the need for people to conduct mundane tasks and elevates the importance of high-value, human-led tasks.”). For more from John Winsor, I recommend listening to his conversation with me on the Digital HR Leaders podcast: Addressing the Global Skills Shortage with Open Talent Strategies.
EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING
MICROSOFT WORK TRENDS INDEX - Breaking down the infinite workday
The future of work won’t be defined by how much drudgery we automate, but by what we choose to fundamentally reimagine.
In this follow-up to their recently published 2025 Work Trend Index Annual Report, this article from Microsoft exposes the modern "infinite workday" – a relentless cycle starting pre-dawn, peppered with incessant emails and messages, hijacked by meetings, and relentlessly spilling into evenings and weekends (see FIG 8). It's a chaotic, fragmented existence that HR leaders, focused on productivity and wellbeing, must address. The critical insight is that AI demands rethinking how work is structured and experienced. This isn't about simple automation; it's about fundamentally redesigning the rhythm of work. The article proposes a clear "path forward" with three vital starting points: (1) Follow the 80/20 rule: Leverage AI to streamline low-value tasks, allowing focus on the 20% that drives 80% of outcomes. (2) Redesign for the Work Chart: Shift from static teams to agile, outcome-driven units, using AI to bridge skill gaps. (3) Become an agent boss: Empower employees to utilize AI agents to supercharge their work and focus on high-quality insights. While the article itself doesn't explicitly detail the opportunity for HR and People Analytics to lean in and shape this future, the implications are clear: these functions are pivotal in orchestrating this transformation, ensuring a focused, productive, and ultimately more human-centric work environment.
FIG 8: The infinite workday bleeds into evenings and weekends (Source: Microsoft Work Trends Index)
LEADERSHIP, CULTURE, AND LEARNING
MEGAN REITZ AND JOHN HIGGINS - Create Mental Space to Be a Wiser Leader
We live in complex times that demand complex thoughts and conversations — and those, in turn, demand the very time and space that is nowhere to be found.
In their article for MIT Sloan Management Review, Megan Reitz and John Higgins explain the need for leaders and workers to balance ‘doing’ and ‘spacious’ modes (see FIG 9) and present their research that finds in our rush to do more we’re losing the critical space to think deeply. This has a detrimental effect on leadership and organisation effectiveness. In order to help leaders develop the capacity for the spacious mode, the authors present their SPACE Framework (Safety, People, Attention, Conflict, Environment). By consciously creating environments that foster reflection and broader thinking, HR can empower leaders to transcend short-term noise, perceive critical interdependencies, and ultimately drive superior business outcomes and a more human-centric employee experience.
FIG 9: The Attentional Mode Framework (Source: Reitz and Higgins)
ROB CROSS AND MOLLIE LOMBARDI - Leading from Anywhere: Driving Results in the Age of Distributed Work
Improving the performance of bottom-quartile leaders yields a 32% productivity impact.
In their recently released study for The Institute for Corporate Productivity (i4cp), authors Rob Cross and Mollie Lombardi highlight that leading distributed work is a greater challenge than is commonly acknowledged. While 86% of organisations say work has become more distributed, 58% of leaders admit they are only "somewhat" effective in this new environment, which increases burnout and limits productivity. The paper identifies six capabilities of leadership effectiveness of top-performing leaders that help employees thrive in a distributed work environment (see FIG 10). Three other key insights from the report are: (1) Fix the bottom, not just the top: Elevating poor managers to just average can result in a 32% productivity gain—and a 33% boost in engagement. (2) Culture is the new productivity engine: Leaders who curate healthy team cultures see a 34% overall market performance lift. (3) Distribute leadership, not just work: Empowering teams with ownership and shared leadership responsibilities is key to sustainability and innovation. Thanks to Heather Muir and Kevin Oakes for highlighting the study.
FIG 10: Capabilities that most distinguish high-performing leaders (Source: i4CP)
KATHI ENDERES AND STELLA IOANNIDOU - Pacesetters in the Superworker Era: The Six Secrets of High-Performing Organizations
Pacesetters are reimagining HR through systemic approaches that integrate talent management, workforce planning, and organizational development to drive AI-powered transformation
Kathi Enderes and Stella Ioannidou present the findings from a four-year collaborative study between The Josh Bersin Company and Eightfold, which analyses the leadership and HR strategies of ‘Pacesetter’ companies - the top 5% performers in every industry – with regards to AI transformation. The article – and paper – identifies six secrets as being key to AI transformation, which these companies approach as a people – rather than technology – transformation: (1) AI Transformation for Growth, Not Cost Control (“[Pacesetters] use AI to improve forecasting, personalize the employee experience, and significantly boost productivity across the enterprise”). (2) Continuous Innovation at the Core (“Pacesetters embed innovation skills, experimentation platforms, and design thinking capabilities across the entire organization”). (3) Productivity-Based Work Redesign (“Instead of layering new tools on top of old workflows, they strip out bureaucracy, clarify accountability, and focus on high-value, meaningful work”). (4) Talent Density: Skills Quality over Quantity (“[Pacesetters] continuously redesign work: removing friction, unlocking capability, and structuring around value rather than legacy” – see FIG 11). (5) From Change Management to Change Agility (“Pacesetters excel at identifying and nurturing the skills needed to navigate change, ensuring their workforces are equipped to adapt to new technologies and processes”). (6) Systemic HR®, Powered by AI (“Pacesetters are reimagining HR through systemic approaches that integrate talent management, workforce planning, and organizational development to drive AI-powered transformation”).
FIG 11: The Four Stages of Work Redesign (Source: The Josh Bersin Company)
DIVERSITY, EQUITY, INCLUSION AND BELONGING
CURTIS L. ODOM, CHARN P. MCALLISTER, AND RYAN SOFFER - Why Belonging Matters More Than Just Diversity
When leaders commit to fostering a culture of belonging, the connection between management practices and diversity-related outcomes becomes clearer
In their article for MIT Sloan Management Review, Curtis Odom, Ed.D., Charn McAllister and Ryan Soffer argue that belonging and psychological safety are the true strategic goals of DEI. For HR leaders focused on impact, this is key. The authors critique the common misstep of viewing diversity as an end in itself, stressing that its value only materialises when people feel genuinely included and safe. Crucially, it outlines three targets for effective DEI. First, establishing belonging and psychological safety as the ultimate aim. Second, urging organisations to move beyond single-approach diversity practices, advocating for a multifaceted, integrated strategy. And third, emphasising the need for persistence to sustain diversity efforts through consistent, long-term action. This isn't just about ticking boxes; it's a strategic imperative for HR to unlock human potential, drive innovation, and deliver tangible business outcomes through a truly inclusive culture.
HR TECH VOICES
Much of the innovation in the field continues to be driven by the vendor and analyst community, and I’ve picked out a few resources from June that I recommend readers delve into:
GABE HORWITZ – The Evolution of the People Analytics Leader - In a great post, Gabe Horwitz of Paradox, breaks down the evolution of the people analytics leader from ‘The Data Analyst’ of 2020 to ‘The Decision Architect’ of today (see FIG 12).
FIG 12: The evolution of the people analytics leaders (Source: Gabe Horwitz)
RICHARD ROSENOW - The Uncharted Path of a People Analytics Career - Richard Rosenow examines what a career in people analytics looks like (see FIG 13), why the path to leadership is still mostly undefined, why it's hard to grow and provides some tips on how to overcome these challenges.
FIG 13: The People Analytics Leader's Journey (Source: One Model)
ZANELE MUNYIKWA - White-Collar Workers Are Getting the Blues – Zanele Munyikwa shares more insightful research from Revelio Labs highlighting a slowing of demand and stagnating wages for white collar jobs with the latter being more pronounced for early career roles (see FIG 14).
FIG 14: Wage stagnation is most pronounced in early-career roles (Source: Revelio Labs)
DEGREED – How the Workforce Learns GenAI in 2025 – According to this new report by Degreed, while 48% of surveyed professionals expect their responsibilities to shift due to GenAI, 78% lack the confidence and skills to use Gen AI tools. The report urges collaboration between CHROs, CLOs and CIOs, and highlights that: “When CHROs and CIOs align on AI upskilling, cross-functional collaboration, and ethical governance, companies are three times more likely to develop a Gen AI-ready workforce.” Thanks to Todd Tauber for sharing.
FIG 15: How to build GenAI confidence (Source: Degreed)
LACE PARTNERS - What are sunrise and sunset skills and how do you use them? – A helpful primer from LACE Partners on ‘sunrise’, ‘evergreen’, and ‘sunset’ skills (see FIG 16) and when to use them. Thanks to Aaron Alburey for highlighting.
FIG 16: Skills mapping horizon (Source: LACE Partners)
PODCASTS OF THE MONTH
In another month of high-quality podcasts, I’ve selected four gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below):
JORGE AMAR, BROOKE WEDDLE AND BRYAN HANCOCK - The future of work is agentic – In a fascinating episode of McKinsey Talks Talent, Jorge Amar, Brooke Weddle, and Bryan Hancock join host Lucia Rahilly to discuss AI agents, how they’re being used, and how leaders can prepare now for the workforce of the not-too-distant future.
KRIS SALING - The US Army & Data Driven Talent Management – Kris Saling, Director of Talent Innovation at the U.S. Army, joins host Cole Napper on the Directionally Correct podcast to discuss her book, Data Driven Talent Management, implementing people analytics in the US Army, and integrating data and analytics into talent management programs.
ALEXIS FINK, SEUNG WON YOON, AND BRAD SHUCK – How to Implement People Analytics – In this masterclass masquerading as a podcast, Alexis Fink, Seung Won Yoon, and Brad Shuck discuss how to implement people analytics.
BAS DEBBINK - Stop Guessing: How J&J Gets Precise About Skills – Bas Debbink, learning strategist at J&J, joins Stacia Sherman Garr and Dani Johnson on Workplace Stories to discuss how J&J utilises both talent leader insight and AI-driven inference to build a skills-based ecosystem that actually works, without overwhelming employees or managers.
VIDEO OF THE MONTH
NICKLE LAMOREAUX AND TEUILA HANSON: How IBM built a skills-based organisation
LinkedIn has recently released an excellent report, CHRO Case Studies: Leading from the Front, which features case studies from five top-notch CHROs, which examine how BCG (Amber Grewal) has fully embraced AI; how IBM (Nickle LaMoreaux) has rethought performance management; how leaders at Allianz (Bettina Dietsche) are modelling the change they want to see; how Wood ( Marla Storm ) is addressing burnout and well-being; and how LinkedIn ( Teuila Hanson ) has introduced Coaching for All. The video featuring Nickle speaking to Teuila, provides a snapshot of the content in the report, and focuses on how IBM has built a skills-based organisation by starting with the data and tracking how skills are changing for each and every job role.
BOOK OF THE MONTH
ROSS SPARKMAN - Strategic Workforce Planning: Developing Optimized Talent Strategies for Future Growth
Ross Sparkman is widely recognised as one of the most accomplished expert practitioners in workforce planning, and the first version of Strategic Workforce Planning was an excellent guide to the fundamentals of this critically important business practice. The second edition provides a deep dive into what it takes to embed SWP and provides new guidance on areas such as: SWP in the age of GenAI, skills-based SWP, leading the SWP function and the future of SWP.
RESEARCH REPORT OF THE MONTH
FRACTIONAL INSIGHTS – The Adaptive Organization: Building and Evolving Culture Across Growth Stages
The latest white paper from the Fractional Insights team of Shonna Waters, PhD, Laura Lomelí Russert, Ph.D. and Erin Eatough, PhD, provides an immensely helpful, research-backed framework for building and evolving culture intentionally, as your business scales. The paper details a stage-based model to guide culture through four stages of growth: early, growth, mid-size and enterprise as well as tools to align systems, behaviours, and values, practical insights from organisational psychology and systems thinking, and pitfalls to avoid as complexity increases.
FROM MY DESK
June saw four new episodes of the Digital HR Leaders podcast – three sponsored by HiBob (thanks Louis Gordon ), and a special bonus episode sponsored by Gloat (thanks Ruslan Tovbulatov ), as well as a round-up of series 47, and a role-reversal as I guested on the HR Leaders podcast.
JANINE VOS – The CHRO’s Playbook: How to Build an Agile and Data-Driven HR Function – Janine Vos, Chief Human Resources Officer and Managing Board Member at Rabobank, joins me to discuss how she has built an HR function that's not only agile and data led but also grounded in trust and strong relationships across the business.
MATTHEW BROWN - From Deployment to Impact: Maximizing Business Value with HR Tech - Matthew Brown, Director of Research, HCM at ISG (Information Services Group) joins me to discuss why the disconnect between HR and tech adoption persists, and how to bridge it.
RAMI TZAFRIR – Why HR must confront 'Covering' to build inclusion and psychological safety - Rami Tzafrir, Senior Director of Talent, Organisation and Learning at HiBob, to unpack powerful new research on covering in the workplace. Together, we explore why this behaviour is not just a personal issue but a signal of deeper organisational challenges - and what HR can do about it.
PATRICIA FROST AND RUSLAN TOVBULATOV - The AI Pivot: Seagate’s Workforce Transformation in the Age of AI - Patricia Frost, Chief People and Places Officer at Seagate Technology, and Ruslan Tovbulatov, Chief Marketing Officer at Gloat, the platform partner behind Seagate’s internal talent marketplace, TalentLink, join me to share insights from Seagate’s workforce transformation journey.
DAVID GREEN - How can HR use AI to improve Employee Experience and Wellbeing? – Highlights from series 47 of the podcast featuring episodes with Dave Ulrich, Volker Jacobs, Janine Vos, Matthew Brown, and Rami Tzafrir.
DAVID GREEN - How people analytics is driving organizational excellence – At the recent UNLEASH America show in Las Vegas, I had the pleasure of speaking to Christopher Rainey as part of a marathon series of interviews he conducted at the event for HR Leaders and Achievers. Chris and I discussed the past, present and future of people analytics and evidence-based decision making in HR.
BONUS RESOURCES
There continues to be so much interesting content around on AI and its impact on business, leadership and HR that this month’s bonus resources are all focused on aspects of this topic:
ANNA OTT - How AI is Rewriting the Playbook for Talent in European Tech Startups - Anna Ott analyses a dataset of 1,800+ job postings across nearly 100 European startups in HV Capital's portfolio to answer the question: How should founders and HR leaders adjust their workforce planning to this new landscape?
ETHAN MOLLICK - Using AI Right Now: A Quick Guide - Wharton professor Ethan Mollick's One Useful Thing is the go-to blog for all things AI. In a recent post, Ethan examines what AI tool you should use for specific tasks (see FIG 17) with Claude, Gemini and Chat GPT being the three systems he recommends.
FIG 17: Source - Ethan Mollick
LASZLO BOCK - The Impact of AI on the Future of Work - Laszlo Bockshares the deck he is using to speak about AI and the future of work. As Laszlo astutely observes:
HR is uniquely positioned to make sure the future of work is both productive and humane.
TOMAS CHAMORRO-PREMUZIC - Want to Use AI as a Career Coach? Use These Prompts - As ever, Dr Tomas Chamorro-Premuzic provides an insightful guide on how you can use Gen AI tools for career coaching, with practical prompts and strategies to maximise your experience, learnings, and success.
STEVEN KIRZ - Why CHROs are critical to unleashing the transformational productivity of AI - Writing for UNLEASH, Steven Kirz explains why when CHROs treat AI as another tech tool, they are missing out on opportunities. Instead, he urges, they need to see AI as a form of talent, not a technology, particularly in this new era of AI agents.
LOOKING FOR A NEW ROLE IN PEOPLE ANALYTICS OR HR TECH?
I’d like to highlight once again the wonderful resource created by Richard Rosenow and the One Model team of open roles in people analytics and HR technology, which now numbers over 500 roles with 60% these being new.
THANK YOU
Million Podcasts for including the Digital HR Leaders podcast at number 6 in their list of the Top 100 Future of Work Podcasts of 2025
Max Blumberg for conducting and publishing an experiment: ?????? ????? ????? ??????? ??'? ????: ??? ????? ????????? ?????? ???????????
Alexandra Nawrat for including my contribution in her article summarising some of the key takeaways from the recent UNLEASH America: Analyst takeaways: UNLEASH America 2025 raised ‘the bar for what a HR technology conference should be’
Finally, a huge thank you to the following people who either shared the June edition of Data Driven HR Monthly and/or posted about the Digital HR Leaders podcast, conferences or other content. It's much appreciated: Charlotte Copeman Gareth Flynn Gulce Guleli Scott Rogers Piyush Mathur AJ Herrmann James Griffin Hernan Chiosso, CSPO, SPHR ? Rochelle Carland Jesse Clark, MBA Miralem Masic Helder Figueiredo Kevin Le Vaillant Emily Killham Marina Pearce, PhD Lida Chahipeyma Dr. Christoph Spöck Dr. Tobias Bartholomé Sergio Garcia Mora Shujaat Ahmad Ali Nawab Lindsey McDevitt Cristian Gabriel Alvarez Nirit Peled-Muntz William Werhane Amardeep Singh, MBA Tsevelmaa Khorloo Debbie Harrison Aravind Warrier Scott Reida Joy Kolb Emily Klein Graham Tollit Dan George Sai Bon Timmy Cheung 張世邦 Margad B Catriona Lindsay Erin Fleming Fiona Jamison, Ph.D. Lewis Garrad Francesca Caroleo (SHRM-SCP, ICF-ACC) Judi Casey Kouros Behzad Rupert Bader Rosemary Byde Preetha Ghatak Mukharjee Amy Huber-Smith Danielle Farrell, MA, CSM Aline Costa Timo Tischer Meghan R. Lowery, Ph.D., M.S. David Simmonds FCIPD Prabhakar Pandey Adam McKinnon, PhD. Greg Newman Kyle Forrest John Barrand Elson P. Kuriakose Jeffrey Pole David van Lochem Hanadi El Sayyed Matt Elk Al Adamsen Kyle Winterbottom Luka Babic Eric Guidice Monika Manova Ankit Saxena, MBA Kirsty Coral Baynton ??? Irada Sadykhova Dawn Klinghoffer Dr. Denise Turley AI.Impact.Equity Evan Franz, MBA Philip Arkcoll Toby Culshaw Dan Riley Sanja Licina, Ph.D. Daniyal Wali Azima Mavlonazarova Julius Schelstraete ? Angela LE MATHON Joonghak Lee, Serap Zel, PhD, Milou Wesdijk, Ingi Finnsson ?, Joanna Thompson (Kempiak), Heather Muir, Summer Pan, Anna Kuzmenko, Olivier Bougarel, Marino Mugayar-Baldocchi, Tobias W. Goers ツ, Bence Gősi, Roxanne Laczo, PhD, Michelle Deneau, Don Gray, Marc Caslani, Claire Masson, Fabian Stokes, MBA, SWP, Delia Majarín, Barry Swales, Narelle Burke, Stela Lupushor, Anna A. Tavis, PhD, Jeremy Shapiro, Kanwal Rai, Patrick Davis, Placid Jover, Francisco Marin, Matthew Shannon, Rashmita Lenka, Henrik Håkansson, Alexandre Monin, Dale Clareburt, Dana Shoff, Warren Howlett, Agnes Garaba, Greg Pryor, Phil Inskip, Stephanie Murphy, Ph.D., Gaëtan Bonny, Nicola Forbes-Taylor FCIPD, Ian Grant FCIPD, Neil Vyner, Joseph Frank, PhD CCP GWCCM, Mila Pascual-Nodusso, Adam Treitler, Fábio Priori, Johann Cheminelle, Alex Browne, Dolapo (Dolly) Oyenuga, Megan Kraus Langdon, Bill Banham, Tom Reid David Balls (FCIPD) Juan Antonio Vega Frankie Close Asaf Jackoby, John Gunawan, Daisy Grewal, Ph.D. Amit Mohindra Sonia Mooney Oliver Auty Caitie Jacobson Mikulis Pedro Pereira Ben Berry Natasha Fearon Andrew Spence Ravin Jesuthasan, CFA, FRSA
ABOUT THE AUTHOR
David Green ?? is a globally respected author, speaker, conference chair, and executive consultant on people analytics, data-driven HR and the future of work. As Managing Partner and Executive Director at Insight222, he has overall responsibility for the delivery of the Insight222 People Analytics Program, which supports the advancement of people analytics in over 100 global organisations. Prior to co-founding Insight222, David accumulated over 20 years experience in the human resources and people analytics fields, including as Global Director of People Analytics Solutions at IBM. As such, David has extensive experience in helping organisations increase value, impact and focus from the wise and ethical use of people analytics. David also hosts the Digital HR Leaders Podcast and is an instructor for Insight222's myHRfuture Academy. His book, co-authored with Jonathan Ferrar, Excellence in People Analytics: How to use Workforce Data to Create Business Value was published in the summer of 2021.
MEET ME AT THESE EVENTS
I'll be speaking about people analytics, the future of work, and data driven HR at a number of upcoming events in 2025:
July 31 - August 1 - People Matters TechHR India 2025, Delhi
August 13-16 - GCHRA Africa, Accra, Ghana (I will join virtually)
September 25 - Visier Outsmart Local London, London
October 7-9 - Insight222 Global Executive Retreat, Atlanta (exclusive to the people analytics leader in member companies of the Insight222 People Analytics Program®)
October 15-16 - People Analytics World, New York
October 21-22 - UNLEASH World, Paris
November 12-13 - HR Forum 2025, Oslo
More events will be added as they are confirmed.
Josh Bersin :劳动力市场已完全改变：您真的准备好了吗？Josh Bersin 最新撰文谈到，随着以婴儿潮一代为主的劳动力队伍的衰落和具有独特期望和职业模式的新一代的崛起，劳动力市场发生了巨大的变化。这一新劳动力的特点是偏好组合职业和副业，他们要求尊重、灵活性和精心设计工作的机会。企业在适应这些变化时面临着挑战，职位普遍空缺，人员流动增加。文章强调，企业需要采用一种动态的组织模式，优先考虑授权、内部流动性和员工积极性，以便在这个新的劳动力市场中茁壮成长。这种适应的关键在于了解劳动力现在寻求的是成长、灵活性以及他们的价值观与工作之间有意义的结合。
英文原文如下，推荐了解
The labor market has changed before our eyes. Employers and HR teams better watch out.
Over the last five decades baby boomers defined the workforce. Today things could not be more different, and this change impacts all of us.
I was born in the 1950s, growing up in a world where the middle class experienced steadily increasing standards of living. My father was a scientist, my mother sold art, and my brother and I had a nice middle-class life.
This included a three stage career: education | work | retirement. I went to college, studied hard, and got a good job as an engineer. My career went on a predictable path. I worked for Exxon and then IBM – each company giving me training, development, and potential for long-term career. I met many great people, learned about work, got married and had a family.
My cohort, the baby boomers, was huge. Companies built entire talent systems for us – onboarding, training, predictable career growth, developmental assignments, leadership development, and retirement programs. We strapped ourselves in and enjoyed the journey.
Fast forward to now: things are very different.
Today’s working population bulge (median age 33, born in the early 1990s,) entered the workforce in a disrupted world. They joined companies during a boom, experienced the pandemic in their 20’s, and live in a world where everything is on the internet. While my generation revered our employers, these workers see every corporate mistake in real-time. They expect their bosses to earn their respect, otherwise they’ll “quietly quit” or start moonlighting on the side.
While my generation expected to work for only a few employers during a career, today people build what Lynda Gratton calls “a portfolio career.” More than 2/3 of workers have side-hustles and their resume is filled with projects, businesses, activities, and professional interests. If you look at the LinkedIn profiles of most high performers they look like personal journeys, far different from the linear career paths we had in the past.
While most of these changes came slowly, the end result is profound: the expectations, needs, and demands of workers are different. And businesses have struggled to keep up. Companies have vast amounts of unfilled positions, we suffer high turnover in almost every role, and labor unions are growing in number.
What do companies do? We have to accept and understand that the labor market has totally changed.
We live in a world where employees will live into their 100s. Young workers are postponing getting married and having children and they see their career as a long series of experiences. The norms of a long-term linear career have ended: people try new things, change industries, and live in what I call a “pixelated” job market.
And rather than blindly trust employers, people bring high expectations to work. Young workers don’t expect to “become the job,” they want the job to “become them.” (Often called “job crafting.”) And given the shortage of workers in every role, this trend is just getting bigger.
While economists believe the job market will soften and employers will have more power over time, I think those days are over. Life just isn’t going back to the way it was. Despite the growth of AI, companies are more dependent on their workforce than ever. And with 70% of the jobs now service-related (healthcare, retail, hospitality), employees really are our product.
I look at it this way. Companies and employers live in a pool of labor: it’s the needs and expectations of people who decide what we can and should do. People are upset about inflation. They’re worried about climate change. They want CEOs to behave ethically. And they want flexible work that lets them live a joyful life.
And every year the workforce becomes more educated and connected. (The percentage of US workers with degrees has gone up to 54%, up from 38% fifteen years ago.) People know about the company’s financial results or other issues far before an announcement even comes out.
While many of these trends are obvious, many companies aren’t ready. Last year I talked to the CHRO of Boeing and he told me the problems were highlighted by employees years ago. They simply were not listening, and now they’re a company in crisis. And that leads to the topic of “employee activation.”
In the old days senior leaders made decisions, workers carried out the orders. Ideas and strategies were “top-down.”
Today much of the intelligence we need to grow our companies is sitting with front-line workers. We need to “activate employees” and listen to them directly. The worker in the store, plant, or front office who feels frustrated by some system or process is the person who should advise us what to do. The old idea of “management by walking around” must come back. (Our Org Design Superclass explains this in detail.)
I don’t mean chaos, holacracy, or lack of controls. Successful companies have a clear mission, a series of strategic initiatives, and budgets to hold people accountable. But they empower everyone to be a leader, unleashing power from the bottom up. (Come to Irresistible and learn about how Marriott and Delta airlines exemplify this model.)
The key is building what we call a “Dynamic Organization” – one which is flat, team-centric, connected, and accountable. Our research shows that only 7% of companies operate this way: most are still very hierarchical and slow to adapt. But change is coming, as companies like Delta, Marriott, Telstra, Unilever, Novartis, Seagate, and Bayer have found out.
(This week the CEO of Bayer announced a radical transformation to a team-centric management model, dramatically reducing the number of “bosses.”)
A dynamic organization does two things well. First, it adapts to change, sees new markets, and mobilizes quickly for change. But even more importantly, it empowers people, encourages internal mobility, and focuses on meritocracy, skills, and collaboration to thrive. (Read about Talent Density to learn more.)
While these ideas are not new, urgency is critical. Employees demand growth, flexibility, and agency – and we can’t deliver it unless our reward and development systems change. Today more than 70% of US jobs are in the service sector: health care, retail, entertainment, and transportation. If we don’t empower people in these roles our products and services will suffer.
Let me conclude with this: we just woke up in a totally new labor market. If you don’t focus on empowerment, growth, and employee activation, talent will just go elsewhere.
Talent density
2024年03月31日
Talent density
Josh Bersin谈How To Create Talent Density 如何打造人才密度
Josh Bersin发表文章谈到：在过去几年里，我注意到大公司的表现开始不如小公司。我们现在看到苹果和谷歌都出现了这种情况，而微软应对这一挑战也有相当长的一段时间了。 随着公司的发展，帮助我们推动组织绩效的一个重要理念就是人才密度。这篇文章讨论了人才密度的概念，即公司中技能、能力和表现的质量和密度。强调传统的员工绩效评估模型已导致平庸。建议采用人才密度方法，包括招聘增加或乘数效应的人才，基于帕累托分布管理绩效，以及专注于赋权、反馈和领导力。文章强调，为了创新和市场竞争力，尤其在AI和技术进步的背景下，维持高人才密度的重要性。
In this (long) article, I want to talk about a new concept called Talent density. And as I pondered the concept I think it represents one of the more important topics in management. So I hope you find it as interesting as I do.
First of all, the concept of talent density, pioneered by Netflix by the way, is simple.
Talent Density is the quality and density of skills, capabilities and performance you have in your company.
So, if you have a company that is 100% high performers, you’re very dense. If you have a company that’s 20% high performers, you’re not very dense. It’s easy to understand, but hard to implement, because it gets to the point of how we define performance, how we select people to hire, how we decide who’s going to get promoted, how we decide who’s going to work on what project and how we’re going to distribute pay.
So before I explain talent density, let’s talk about the basic beliefs most companies have. Most organizations believe that they’re operating with a normal distribution or bell curve of performance. I don’t know why that statistical model has been applied to organizations, but it has become almost a standard policy. (Academics have proven it false, as I explain below.)
Using the bell curve, we identify the “mean” or average performance, and then categorize performance into five levels. Number ones are two standard deviations to the right and number fives are two standard deviations to the left.
The people operating at level one get a big raise, the people operating at level two get medium raise, the people operating at level three get an average raise, the people operating at level four get a below average raise and the people operating at level five probably need to leave. Lots of politics in the process, but that’s typically how it works.
As I describe in The Myth of The Bell Curve, these performance and pay strategies have been used for decades. And at scale they create a mediocrity-centered organization, because the statistics limit the quantity and value of 1’s. If you’re operating at 1 level and you get a 2, you’ll quit. If you’re operating at 3 level, you’re probably going to coast. You get my drift. And since the bulk of the company is rated 2 or 3, most of the managers are in the middle.
As the saying goes, A managers hire A people, B managers hire C people. So over time, if not constantly tuned, we end up with an organization that is almost destined to be medium in performance.
Now I’m not saying every company goes through this process, but if you look at the productivity per employee in large organizations it’s almost always below that of smaller organizations. Why? Because as organizations grow, the talent density declines. (Netflix, as an example, example, generates almost $3M of revenue per employee, twice that of Google and 10X that of Disney. And they are the only profitable streaming company, with fewer than 20,000 employees and a $240 billion market cap.)
The traditional model was fine in the industrial age when we had a surplus of talent, jobs were clearly defined, and most employees were measure by the “number of widgets they produced.” In those days we could swap out a “low performer” for a “high performer” because there were lots of people in the job market.
We don’t live in that world anymore. The world we now live in has sub 4% unemployment, a constant shortage of key skills, and a growing shortage of labor. And thanks to automation and AI, the revenue or value per person has skyrocketed, almost an order of magnitude higher than it was 30 years ago.
So we need a better way to think about performance in a world where companies with fewer people can outperform those who get too big. Look at how Salesforce, Google, Apple, who are essentially creative companies, have slowed their ability to innovate as they get bigger. Look at how OpenAI, who is a tiny company, is outperforming Google and Microsoft.
Today most businesses outperform through innovation, time to market, customer intimacy, or IP – not through scale or “harder work.”
How do we maintain a high level of talent density when we’re growing the company and hiring lots of people? Netflix wrote the book on this, so let me give you the story.
First, the hiring process should focus on talent density, not butts in seats. Rather than hire someone to “fill a role” we look for someone who is additive or multiplicative to the entire team. Hire someone that challenges the status quo and brings new ideas, skills, and ideas beyond the “job” as defined. Netflix values courage, innovation, selflessness, inclusion, and teamwork, for example. These are not statements about “doing your job as defined.”
Netflix’s idea is that each incremental hire should make everybody else in the company and everybody else in the team produce at a higher level. Now this is a threatening thing for an insecure manager because most managers don’t want to hire somebody that could take their job away. But that’s why we have this problem.
Second, we need to manage or create some type of performance management process that is built around the Pareto distribution (also called the Power Law) and not the normal distribution. In the Pareto distribution or the power law, we have a small number of people who generate an outsized level of performance, you can call it the 80/20 rule or the 90/10 rule. (20% of the people do 80% of the work)
Studies have shown that companies and many populations work this way, and it makes sense. Think about athletes, where a small number of super athletes are 2-3 better than their peers. The same thing is true in music, science, and entertainment. It’s also true in sales and many business disciplines.
Research conducted in 2011 and 2012 by Ernest O’Boyle Jr. and Herman Aguinis (633,263 researchers, entertainers, politicians, and athletes in a total of 198 samples). found that performance in 94 percent of these groups did not follow a normal distribution. Rather these groups fall into what is called a “Power Law” distribution.
In every population of human beings there are a few people who just have God-given gifts to outperform in the job, and they just naturally seem to be far better than everyone else.
Bill Gates once told the company that there were of the three engineers that he felt made the company of Microsoft. And I’ve heard this in many other companies, where one software engineer and the right role can do the work of 10 other people.
Now, this is not to say that everybody will fall into one level of the Pareto distribution. At a given point in time in your career, you may be in the 80% and over time, as you learn and grow and find the things that you’re naturally good at, you’ll end up in the 20%. But in a given company this is a dynamic that’s constantly taking place. And that’s what Netflix is doing – constantly working on talent density.
What does this mean for performance management? It means that in order to care for a population like this, we have to hire differently, avoid the bell curve, and pay high performers well. Not just a little more than everybody else, a lot more. And that’s what happens in sports and entertainment, so why not in business.
If you look at companies like Google, Microsoft, and others, there are individuals in those companies that make two to three times more than their peers. And as long as these decisions are made based on performance, people are fine with it.
What obviously does not work is when person making all the money is the person who’s the best politician, best looking, or most popular.
And that leads me to item three: In the Netflix culture there’s a massive amount of empowerment, 360 feedback, candor and honesty. You’ve probably read the Netflix culture manifesto: it’s all about the need for people to be honest, to speak truth, to give each other feedback, and to focus on judgement, courage, and accountability. Netflix only recently added job levels: they didn’t have job levels for many years.
Giving people feedback is a challenge because it’s uncomfortable. So this has to to start at the top and it has to be done in a developmental, honest way. This does not mean people should threaten or disparage each other, but we all need to know that at the end of a project or the end of the meeting it’s okay for somebody to tell us “here’s what was great about that and here’s what wasn’t great about it.”
One of the most important institutions in the world, the US military lives, eats and dies by this process. If you’re in the military and you mess something up, you can guarantee that somebody’s going to tell you about it, and you’re going to get some help making sure you don’t do it again. We don’t have life or death situations in companies, but we can certainly use this kind of discipline.
The fourth thing that matters in talent density is leadership and goal setting. One of the things that really gets in the way of a high performing company is too many individual goals, too many siloed projects and responsibilities and people not seeing the big picture.
If your goal setting and performance management process is 100% based on individual performance you are sub-optimizing your company. Not only does this work against teamwork, but there really isn’t a single thing in a company that anybody can do alone. So our performance management research continuously shows that people should be rewarded for both their achievements as well as that of the team. (Here’s the research to explain.)
Why is talent density important right now? Let me mention a few reasons.
First, we’re entering a period of low unemployment so every hire is going to be challenging. And thanks to AI, companies are going to be able to operate with smaller teams. What better time to think about how to “trim down” your company so it’s performing at its best?
Second, the transformations from AI are going to require a lot of flexibility and learning agility in your company. You want a highly focused, well aligned team to help make that happen. And while AI will help every company improve, your ability to leverage AI quickly will turn into a competitive advantage (think back about how web and digital and e-commerce did the same).
(I firmly believe the companies with the most ingenious applications of AI will disrupt their competitors. I’m still amazed at Whole Food’s hand recognition checkout process: I can see self-service coffee, groceries, and other retail and hospitality coming.)
Third, the post-industrial business world is going to start to devalue huge, lumbering organizations. Many big companies just need a lot of people, but as Southwest Airlines taught us long ago, it’s the small team that performs well. So if you can’t break your company into small high-performing teams, your talent density will suffer.
When the book is written on Apple’s $10 Billion car, I bet one problem was the size and scale of the team. We’ll see soon enough. By the way, I still recommend everyone read “The Mythical Man-Month,” which to me is the bible of organizing around small teams.
What if you’re a healthcare provider, retailer, manufacturer, hospitality company? Does talent density apply to you? Absolutely! Go into a Costco and see how happy and engaged the employees are. Then go into a poorly run retailer and you’ll feel the difference.
In my book Irresistible I give examples of companies who embrace what I call “the unquenchable power of the human spirit.” Nobody wants to feel like they’re underperforming. With the right focus on accountability and growth we can help everyone out-perform their expectations.
Now is a time rethink how our organizations work. Not only should we promote and reward the hyper-performers, the Pareto rule and Talent Density thinking encourage us to help mid-level performers learn, grow, and transform themselves into superstars.
Let’s throw away the old ideas of bell curve, forced distribution, and simplistic performance management. Companies that push for everlasting high performance are energizing places to work, they deliver outstanding products and services, and they’re great investments for stakeholders.
AI中文翻译：
在这篇篇幅较长的文章中，我想探讨一个被称为“人才密度”的新概念。思考此概念时，我认为它是管理领域中极其重要的议题之一。希望您能像我一样发现其趣味性。
首先，Netflix首创的“人才密度”概念其实很简单。
人才密度指的是公司内部技能、能力和表现的质量与密集程度。
换句话说，如果你的公司全是高绩效人才，那么你的“人才密度”就很高。如果只有20%是高绩效人才，那么你的“人才密度”就不高。这个概念虽然容易理解，但实际执行起来却颇具挑战，因为它涉及到我们如何定义绩效、招聘员工的标准、晋升决策、项目分配以及薪酬分配。
在详细解释“人才密度”之前，让我们先看看大多数公司的基本信念。许多组织相信，他们的员工表现遵循一个正态分布或钟形曲线。这个统计模型为何被广泛应用于组织之中，我并不清楚，但它几乎已成为标准做法。（实际上，如我下文将解释的，学术研究已证明这一模型是错误的。）
采用钟形曲线，我们确定平均表现（即“平均线”），然后将员工的表现划分为五个等级。表现最好的被归为一级，标准为右偏两个标准差；表现最差的被归为五级，左偏两个标准差。
一级表现者获得大幅度加薪，二级表现者获得中等加薪，三级表现者获得平均水平的加薪，四级表现者加薪低于平均，五级表现者可能就需要离开公司了。虽然这个过程充满了政治操作，但这就是它通常的运作方式。
正如我在《钟形曲线的神话》中所述，这些关于绩效和薪酬的策略已经使用了数十年。而且，当这些策略在大规模下实施时，它们会造成以平庸为中心的组织文化，因为这种统计方法限制了顶尖人才的数量和价值。如果你是一级表现者却被评为二级，你很可能就会选择离职。如果你是三级表现者，你可能就会选择安于现状。你应该明白我的意思了。而且，由于大部分员工的评级为二级或三级，大多数管理者也就处于中等水平。
常言道，A级的管理者招聘A级人才，B级的管理者则招聘C级人才。因此，如果不持续进行优化调整，组织最终几乎注定会变得中庸。
我并不是说每家公司都会经历这一过程，但如果你查看大型组织的员工生产率，通常都低于小型组织的生产率。为什么呢？因为随着组织规模的扩大，“人才密度”往往会下降。（以Netflix为例，其每名员工创造的收入几乎为300万美元，是Google的两倍，是迪士尼的十倍。他们是唯一盈利的流媒体公司，员工不足20,000人，市值2400亿美元。）
在工业时代，人才供过于求，工作职责明确，大多数员工的表现以“生产的产品数量”来衡量。那个时候，低绩效者可以轻松地被高绩效者替换，因为劳动市场上有大量的人才可供选择。
但我们不再生活在那个时代了。在我们现在的世界里，失业率低于4%，关键技能持续短缺，劳动力整体也日益减少。而且，得益于自动化和AI技术，每位员工创造的收入或价值比30年前高出了几个数量级。
因此，在一个人员更少的公司可以超越体量更大的公司的世界中，我们需要一种更好的绩效思考方式。看看Salesforce、Google、Apple这些本质上依靠创新的公司，随着规模扩大，它们的创新能力如何变缓。再看看OpenAI，尽管是一个小公司，却在超越Google和Microsoft。
如今，大多数企业通过创新、市场响应速度、客户亲密度或知识产权而非规模或“更加努力的工作”来实现超越。
在我们不断发展公司并招聘大量人员的同时，我们如何保持高水平的“人才密度”？Netflix在此领域有着开创性的工作，让我来分享一下他们的故事。
首先，招聘过程应专注于提高“人才密度”，而不是仅仅为了填补空缺。我们寻找的不是简单地“填补一个角色”的人，而是能够为整个团队带来正面或倍增效果的人才。我们寻找的是那些能够挑战现状、带来新观点和技能，并超出传统“工作定义”的人。例如，Netflix重视勇气、创新、无私、包容和团队合作等价值观，并不仅仅是“完成既定工作”。
Netflix的理念是，每一次新增的招聘都应该使公司内每个人和团队的每个成员的生产力得到提升。这对于那些缺乏安全感的管理者来说可能是个挑战，因为大多数管理者并不希望招聘可能会取代他们的人。但正是这种思维方式导致了我们当前的问题。
其次，我们需要建立或改进一种围绕帕累托分布（也称作幂律分布）而非正态分布的绩效管理流程。在帕累托分布或幂律分布中，少数人贡献了超出常规的绩效水平，这可以称作80/20规则或90/10规则。（即20%的人完成了80%的工作）
研究显示，许多公司和人群实际上都是以这种方式运作的，这是合理的。想想那些在体育、音乐、科学和娱乐领域表现出色的人，其中少数顶尖人才的表现是同龄人的两到三倍。销售和许多商业领域也是如此。
2011年和2012年由Ernest O’Boyle Jr.和Herman Aguinis进行的研究（涵盖了633,263名研究人员、艺术家、政治家和运动员，共198个样本）发现，这94%的群体的表现并不遵循正态分布，而是呈现所谓的“幂律分布”。
在每个人群中，总有少数人因为天赋异禀，在工作中表现出色，自然而然地比其他人优秀得多。
比尔·盖茨曾经对微软说过，他认为公司中的三名工程师是公司的基石。我也在许多其他公司听到过类似的故事，其中一位软件工程师在合适的位置上可以完成其他十人的工作量。
这并不意味着每个人都将被归入帕累托分布的某一层级。在你职业生涯的某个阶段，你可能处于80%的群体中，但随着你不断学习、成长并找到自己真正擅长的领域，你最终可能进入20%的群体。但在任何一个公司，这种动态都在不断发生。这就是Netflix一直在努力提升“人才密度”的原因。
这对绩效管理意味着什么？这意味着，为了照顾这样一个群体，我们必须采取不同的招聘方式，避免使用钟形曲线，并且为高绩效者提供丰厚的薪酬。这不仅仅是支付比其他人稍微多一点的薪水，而是要多得多。这在体育和娱乐领域已经是常态，那么为什么不可以应用到商业领域呢？
如果你观察Google、Microsoft等公司，你会发现，这些公司中的个别人物赚取的收入是他们同事的两到三倍。只要这些决策基于绩效，大家通常都能接受它。
当然，不起作用的情况是，赚取高薪的是那些最擅长政治、外表最出众或最受欢迎的人。
这就引出了第三点：在Netflix的文化中，存在着大量的授权、360度反馈、直率和诚实。您可能已经读过Netflix的文化宣言，它强调人们需要诚实、坦诚、互相提供反馈，并专注于判断力、勇气和责任感。直到最近，Netflix才引入了职级制度——在很多年里，他们根本没有职级制度。
提供反馈是挑战性的，因为这会使人感到不适。因此，这个过程必须从高层开始，并以一种促进发展、诚实的方式进行。这并不意味着人们应互相威胁或贬低，但我们都需要明白，在项目结束或会议结束时，对方告诉我们“这是成功之处，这是失败之处”是完全可以接受的。
美国军队是世界上最重要的机构之一，它依靠这种过程生存、发展和克服困难。如果你在军队犯错，你可以确信会有人告诉你，并且你会得到帮助以确保你不会再犯同样的错误。虽然公司里没有生死攸关的情况，但我们完全可以借鉴这种纪律性。
在“人才密度”中很重要的第四点是领导力和目标设定。阻碍高绩效公司发展的一个常见问题是过多的个人目标、孤立的项目和职责，以及员工无法看到整体大局。
如果你的目标设定和绩效管理过程完全基于个人表现，那么你就在削弱你的公司。这不仅阻碍了团队合作，而且实际上没有什么是公司内任何人能够独立完成的。因此，我们的绩效管理研究不断表明，人们应该同时因其个人成就和团队成就而获得奖励。（这是相关的研究。）
为什么“人才密度”在当前尤为重要？我来列举几个原因。
首先，我们正处于一个失业率低的时期，因此每次招聘都将是一个挑战。而且，随着AI技术的帮助，公司将能够以更小的团队运作。在这样一个时刻，有什么比考虑如何“精简”你的公司、使其发挥最佳表现更合适的时机呢？
其次，随着AI的变革，你的公司将需要极大的灵活性和学习适应能力。你需要一个高度专注、良好协调的团队来实现这一目标。而且，尽管AI将帮助每个公司提高效率，但你快速应用AI的能力将变成一个竞争优势（回想一下网站、数字化和电子商务如何实现了同样的事情）。
（我坚信，那些能够巧妙应用AI的公司将会颠覆它们的竞争对手。我对Whole Foods的手掌识别结账过程仍感到惊讶：我预见到自助服务咖啡、杂货及其他零售和酒店业务的出现。）
第三，后工业时代的商业世界将开始贬低庞大、笨重的组织。许多大公司只是需要大量员工，但正如西南航空所示，小团队的表现通常更好。因此，如果你无法将你的公司划分为小型高效团队，你的“人才密度”将受到影响。
当有关Apple的100亿美元汽车项目的书籍编写时，我敢打赌问题之一将是团队的规模和规模。我们很快就会发现。顺便说一下，我还是推荐每个人阅读《神话般的人月》，对我而言，这本书是关于围绕小团队进行组织的经典之作。
如果你是医疗服务提供者、零售商、制造商或酒店业者，“人才密度”是否适用于你？当然适用！走进一家Costco，看看员工是多么的开心和投入。然后走进一个管理混乱的零售商，你就能感受到区别。
在我的书《不可抗拒》中，我列出了那些拥抱我所称之为“人类精神不可磨灭力量”的公司的例子。没有人愿意觉得自己表现不佳。通过适当的关注责任和成长，我们可以帮助每个人超越他们自己的期望。
现在是时候重新考虑我们的组织如何运作了。我们不仅应该提升和奖励顶尖表现者，帕累托法则和“人才密度”思维还鼓励我们帮助中等表现者学习、成长，并将自己转变为明星。
让我们抛弃旧的钟形曲线、强制分配和简单化绩效管理的想法。不断追求高绩效的公司是充满活力的工作场所，他们提供卓越的产品和服务，并且对投资者而言是极好的投资。
Talent density
2024年03月10日
Talent density
Don’t Be A Copy-Cat: People Analytics as the Antidote to HR Strategy Copy-CatsThis article is written to discuss: why copying the HR practices that everyone else uses doesn’t lead to the positive outcomes you assume it will.
DISCLAIMER: If you like the HR strategy at your organization, you can probably stop reading now… If not, feel free to keep reading.
Context
Childhood wisdom: No one likes a copy-cat.
We all remember being children once. Kids are known to tease each other from time to time. One common reason to be teased when you were a child was being called a “copy-cat”. It didn’t feel good, often because we knew that if we were labeled a copy-cat, it was likely true. We were copying someone else. It felt bereft, unoriginal, and commonplace. We knew we were capable of being more, but we had settled for less. We were better than that. HR strategy can be better than that too.
Fast forward to the present, in HR being a copy-cat is all the rage. A priestly caste of HR influencers, HR tech consultants, FAANG companies, and sometimes even academics determine what is considered ‘en vogue’ as an HR strategy. Then, early adopter HR departments fall in-line; followed by the early majority and late majority after a few HR monkeys get “shot into space” without injury. The laggards may never arrive because they are still trying to move away from using paper files stuffed in filing cabinets, but nonetheless, being a copy-cat all the sudden became cool. Why be original when you could be doing what everyone else is doing? Perhaps, this is why Forrester is forecasting an EX winter coming soon…
In the African savanna, large numbers of herd animals, such as wildebeest, zebra, and gazelles, travel in packs. Why do they do this? Because there is safety in numbers. A zebra with a single imperfection or mark is easily identified and pulled from the pack by predators. Is the same true for HR? Are we safer in a pack? Is there wisdom in being a copy-cat? Would anything different make us stand out and therefore be put in danger? I think not. I think the opposite is true, in fact.
If you do all the same things as your competitors, how can you expect to get different results?
Does this HR strategy sound familiar?
“We’re going to try to hire the best talent, but only pay at the 50th percentile.”
“We’re a performance-driven organization, but we’re going to do performance reviews once a year on a 5-point rating scale, and we’ve got to implement a pay-for-performance incentive structure.”
“Our HR operating model is to use HR Business Partners, Centers of Excellence, and Shared Services.”
“We’re going to copy what Google did 10 years ago, or what GE did in the 80s.”
“We’re going to make data-driven decisions. I know! Let’s create another HR dashboard.”
If your organization wants to be radically better, it’s going to have to try some things that are radically different. Did anyone see Coinbase’s recent blog on Talent Density? I’m not saying I agree with the changes to their HR strategy, but at least they are trying to differentiate their HR strategy to be something different. They are getting into the game, for better or worse.
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What To Do, What To Do?
HR strategy should be composed of elements that are as unique to your business as your business strategy is unique to your business. It’s really as simple as that.
HR Strategy is upstream of people analytics. A vanilla, copy-cat HR strategy is going to lead to vanilla, copy-cat people analytics. In my opinion, people analytics doesn’t spend enough of its resources trying to familiarize itself, influence, and control HR strategy. People analytics should speak in the social currency of the organization. We should embed ourselves and influence key decision making, and have a seat at the table by speaking in the language of the business. There is social capital to be had, and the more I learn, the more I realize the necessity of this alternative currency. We should drive strategy.
With generative AI disrupting the value that human capital brings to organizations, who are the organizations that are going to be the innovators of tomorrow? Who are the organizations who will get the message early? Who will treat the need for differentiation with the existential demand that it dictates? Who will survive?
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“Best Practices”
I’m tired of the term ‘best practices’. I’m at a point in my career where I bristle when I hear someone say it. Perhaps it's one of the reasons why some people hate HR.
Organizational research is important, but best practices are a road to mediocrity. No one ever got fired for going with IBM, and no one ever got fired for using best practices… Until the whole firm loses to its competition, and everyone gets fired. Read it again, and think about that. It’s a short-term vs long-term thinking dilemma. Obviously, balance the two, but make sure to think with the long-term in mind.
What if instead of copy-catting, you:
A/B tested your HR strategy against those of other firms
Used opposition research to understand your competitors HR strategy better, so you can do something different
Implemented evidence-based practices on commoditized work, but experimented with firm-specific practices in the most strategically-relevant work
Focused on first-principles thinking as to how firm value is derived by its talent
Choose function over fad, when it comes to HR strategy
Rebuild HR strategy like the Oaklands As (and the Houston Astros) tore down and rebuilt their teams based on talent derived from data. Embed data, measurement, accountability, and the “improvement feedback loop” into every single workstream that HR engages. Henry Ford once said “if you always do what you’ve always done, you always get what you’ve always got.” HR could be convicted of being mediocre. Average is over (or maybe even above average is over?). Differentiation is king. Strategic neglect (i.e., neglecting things that don’t add value) is also a valuable tool. Where do we need to be world class? Where can we be average? Answer those questions, then execute.
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Rebuilding HR Around Data & Measurement
In most HR functions, data is only used to validate, not to guide. No one thinks for themselves. Mimicry and mimesis abound.
People analytics is a competitive advantage for firms who use it properly. People analytics is the future of HR. Proclamations such as this have been made consistently in the past (e.g., HR is over, remote work is the future, there is no need for management, human tasks at work will be automated with AI, etc.), but this one is for real. Firms who are not embedding data into the way they do business, evaluating what they do with data, and projecting the future with data are going to be irrelevant.
In the future, even in the age of generative AI, there is only one currency, and that is truth. Truth can only be derived as data put into practice. Classical test theory states that all measurement is “truth-plus-error”, with error being any deviation between measurement and the truth. Some stakeholders believe that to mean that truth can never be attained because error will always exist. Practically, this is a misinterpretation. Organizations that can manifest the best data with the least error will be the closest to truth, and therein lies the root of competitive advantage via data. People analytics is not inherently useful. Data is not inherently useful. Only accurate data, with analysis and cogent results, derived into a form that facilitates timely and accurate decision making, and that is put into action, is useful. And across the aggregate of thousands, if not millions of small decisions made leads one organization to prevailing over another. May the odds ever be in your favor.
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Moving Forward
“Traditional HR” has been on the way out for decades. This article is for HR people who believe in challenging the status quo. Deep down they know there is a better way; a way forward for their organization. To not outsource their originality to others. To not be a copy-cat. Let’s focus on what the pathway forward looks like with a new highest principle – no longer “what is everyone else doing?” – but with data and measurement at the center. This article is for the HR professional who knows that HR can be smarter, faster, and better at their organization, and they are bound to make it happen. Join the movement. Don’t be a copy-cat. Let’s see how high we can fly together.
PS - I’m thinking of writing a book on this topic. If you’re a publisher and you are interested in this topic, or others I’ve written about before, please contact me directly.
Special shout out: Thanks to Brad Harris & Pat Downes for our previous conversations on this topic.
I hope you like this article. If so, I have a few more articles coming out soon. Stay tuned. If you are interested in learning more directly from me, please connect with me on LinkedIn.
Cole’s recent articles
What’s Old is New: The Quest for Excellence in Workforce Planning
A Historian, Demographer, & Data Scientist Walk Into a Bar…
The Phoenix & The Dragon
Why Buy When You Could Rent: SEC’s Push for Human Capital Disclosure
Elephant Hunting: Weighing Human vs. Algorithmic Input to Decision Making
For access to all of Cole’s previous articles, go here.
By: Cole Napper
原文来自：https://directionallycorrectnews.substack.com/p/dont-be-a-copy-cat-people-analytics
Talent density
Talent density
Talent density
Talent density
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