How To Make Productivity Soar: Four Stages of AI TransformationWe’ve been doing a lot of advisory work on skills and job design and now that AI tools have arrived, we’re reinventing work faster than ever. So let me give you some thoughts on this process, and you can also learn more from my recent podcast.
As you know, there are many types of AI business tools: Copilots, Assistants, Agents, Talent Intelligence Systems, and embedded applications. Each of these products are built on an AI-first foundation and they layer on domain expertise, use-case analysis, and iterative design to build smarter and smarter systems.
Self-driving cars started as voice assistants, automatic braking, and lane warnings. Now they keep you in the lane and slow your car when the speed limit changes. And soon enough they’ll be driving for us, so we can sit in the back seat and read a book.
Our HR Assistant Galileo started as a research and problem solving tool, and it’s rapidly becoming an AI coach, benchmarking tool, recruiting, and change management system. So all these tools go from simple use-cases to deeper applications and autonomy over time.
As the tools get smarter and more domain focused we are going to have to rethink our jobs and business processes. And unlike ERP, where we essentially trained people to “adopt” the system, now a lot of the groundbreaking applications come from the bottom up. Individuals will discover capabilities for AI and then apply them in increasingly innovative ways.
And over time, as they get smarter, our jobs move more to “supervisors” and “trainers” of AI, not just consumers. For example if our self-driving car took a bumpy route, we may “retrain it” to take a longer but smoother road.
As I discuss in the podcast, I believe there are four stages of adoption today. And we’re in the middle of doing all four at the same time.
Level 1: Make existing work easier. (Same job, better tools.)
This is where we click on the Microsoft Copilot or Zoom or Teams and the system analyzes a meeting, summarizes emails, or writes a document with our help. We do our jobs the same way we did before, but we now have a “super-productivity” tool to make it easier. These “add-on” use cases are emerging everywhere, and they already feel like a commodity.
In most cases employees see 10-15% or more improvements here, but life isn’t that much different. And sometimes the tool slows us down (Copilot doesn’t create slides well at all yet) and may actually get in the way. But we can expect this mode to continue and most of us figure this out on our own.
Level 2: Major steps eliminated, but the job is the same. (Same job, tools eliminate work.)
At level 2 we automated a lot. Software engineers now use copilots to develop 70% of their code, so they’re spending more time testing and prompting the AI. Their individual coding skills may atrophy, but they can now work on more architectural issues.
The “job” of software engineer may still be the same, but the output is far greater. So we’re making the same pay, doing the same work, but using highly automated tools.
This includes scenarios like chip designers, software engineers, supermarket checkout clerks, nurse scheduling jobs, and even recruiting assistants. Paradox customers, for example, virtually eliminate “scheduling assistants” for recruiting.
At this level companies can see 50-75% productivity improvement, and free time to focus on quality management, customer service, and ongoing improvements to the tools.
Level 3: Re-engineered work, partnered with agents. (New job, redesigned process, agents automate work.)
At level 3 we go further: we re-engineer the process and the work. Imagine how McDonald’s replaced its counter workers with a kiosk, eliminating the “may I take you order please?” role.
This took some major design effort but resulted in a whole new set of roles, workflow, and management structure in the restaurants. The “cost per burger” went down, and the customer experience is almost as good (not quite).
Here we need to be careful because sometimes the “self-service, AI-enabled” experience doesn’t work. A good example is the supermarket self-checkout. It rarely works well and usually takes longer than standing in line. But it will get better, and the resulting experience is faster throughput, more data (the self-service agent might offer you a discount since it knows your buying history), and far superior employee roles.
In level 3 the employees are still involved, and we are more or less “working with the machine,” aiding and supporting the process.
Level 4: Autonomous intelligent agents, people training and managing the AI. (New job, redesigned process, people “manage” the agents.)
At level 4 we go even further. Imagine an AI recruiter (Paradox does this) that could email a hiring manager and his team, gain feedback and requirements on a job and role, consolidate input, and create a total description. This Agent could then review this job against the company culture and pay policies, compare the job against similar jobs in the external market, and tweak the level, job title, and description to be competitive. And then it could start sourcing, and give the hiring manager and human recruiter a set of candidates ranked by various criteria.
That process, which takes dozens of steps for a recruiter, could be fully automated and vastly improved. The Agent could even look at prior hires and get even smarter about who to source based on the success of other candidates.
Now the human job is to “train” and “monitor” and “manage” this AI Agent, who has effectively become a digital employee. (Note: Salesforce is doing a terrific job of building this out for sales and service.)
The Rise of the SuperWorker
Our thesis is that AI is not a “job-replacement” technology, it’s a “SuperWorker empowerment” technology. In other words, most of these scenarios result in higher value jobs, higher pay, and value creation (not cost reduction) in the business.
This is happening fast.
We’re in the middle of a big study in this area and I’ll be explaining this more in our upcoming 2025 Predictions report. The upside of all this will be new and higher paying jobs, faster response to business change, but a lot of IT, design, and data management to do. But based on our research, this is coming soon.
Productivity
2024年12月01日
Productivity
Josh Bersin:Digital Twins, Digital Employees, And Agents Everywhere2025 年,数字员工和人工智能助理的崛起将彻底改变人力资源运营,改变招聘、数据分析和员工管理等任务。 这些技术包括数字双胞胎和智能代理,它们将与人类专业人员一起工作,以提高生产力和优化工作流程。 随着人工智能工具成为日常业务不可或缺的一部分,人力资源领导者必须拥抱这些创新,同时继续关注技能培训、心理健康和包容性工作环境。 向人工智能的转变还将重塑团队动态,这对人力资源部门重新设计角色和流程以保持竞争力提出了挑战。
I recently heard Elon Musk predict that every citizen would have multiple Optimus robots in their homes within five years. And while I often ignore his predictions because they’re exaggerated, I think he’s on to something. We are about to witness an explosion of Digital Employees in our companies, and these may be the “robots” we’ve heard about for years.
Let me explain. This week I talked with dozens of vendors and clients at Unleash and then visited our development partner Sana Labs in Stockholm. It’s now clear that we’re going to be working with multitudes of “digital employees” in the year ahead.
(And as Dario Amodei, the founder of Anthropic explains, AI can do many more positive things in business, science, and health than we ever imagined.)
By “digital employee” I mean a software powered agent that can talk with us, answer detailed questions, solve complex analytic problems, and navigate a multitude of systems. ChatGPT and its peers, which introduced the idea of an agent, has now spawned dozens of “agentic” use cases, which I’d be willing to refer to as personalities.
Let me start with a “Digital Twin.” Imagine you have a superb customer service agent with years of experience helping your most demanding clients. If you load the last five years of their emails, coupled with all their internal documentation, and a log history of their last two years of service calls, you can essentially “create him or her” digitally with all the knowledge, style, and internal contacts this person has developed. This twin, which may look initially like an AI assistant, could then carry on this employee’s work when the real life worker is on vacation.
One of our clients, a large insurance company, has already built “digital twins” for claims processing. If you think about the complexity and workflow of processing a claim, much of it could be learned by an agent, making the “claims robot” an expert on this important process. And as you change claims rules and limits, the agent will learn new guidelines in only seconds.
Our AI assistant Galileo, a trained expert on HR (Galileo is trained on 25 years of research and thousands of conversations with clients and vendors), is essentially a “digital twin” of me and the other analysts in our firm. I’m not saying Galileo is as fun to talk with as we are, but I can assure you that he (or she) is as knowledgeable and supportive. And Galileo is even smarter than I am: he has instant knowledge of skills models, compensation benchmarks, turnover statistics, and other data bases which I can only access by looking them up on demand.
And using the Sana platform we can configure Galileo to have multiple personalities. Galileo the “Recruitment Agent” might have in-depth knowledge of screening, interviewing, and candidate skills assessment and he may have direct linkage to SeekOut, Eightfold, or any other sourcing applications. In his candidate facing personality he may be able to answer candidate questions, explain shift schedules, and “sell” the company to top job candidates. (This is what Paradox has done for years and vendors like Eightfold and LinkedIn are launching now.)
But there’s more. Imagine that this “digital twin” or “digital employee” has intimate knowledge of Workday, SuccessFactors, or a variety of other systems. Now the assistant can not only answer questions and help solve problems, he can also process transactions, look things up, and run reports against multiple system. The digital employee has turned into a “digital analyst,” who can find things and do work for you, saving you hours of effort in your daily life. (Vee from Visier is designed for this.)
Suppose you ask your digital friend to attend meetings for you, participate in conversations on certain topics, and alert you in real time when urgent issues come up for discussion. He could help you scale your time, keep you informed about decisions you need to know about, and help you manage your action items. And the list goes on and on and on.
Best of all, what if your digital twin can talk to you. Suppose he “checks in” with you about the project you asked for help with last week, so you inform him how things are going and he gets “smarter” about what you may need next. Galileo does this today, prompting you to dig into a problem and explore areas you may not have considered. And if you ask him about management or people issues, he could give you advice and coaching, based on the leadership models or even CEO interviews in your own company. (BetterUp, Valence and others are working on this.)
This is not science fiction, my friends. All this is becoming reality and will certainly be common next year.
Every vendor has a slightly different focus. The Microsoft Copilot specializes in MS Office-related activities, ServiceNow’s focuses on internal service and support, Galileo is focused on the needs of HR, and Joule is an expert on all the functions of SAP. Each of these “digital employees” needs training, feedback, and connections to stay current and relevant. So it’s doubtful that one digital employee will do everything. (Training a digital employee means managing his or her corpus of information, which will be a major new role in HR.)
One thing is very clear: we are going to be living and working with these guys. And as we use them and see what they’re capable of, we’re going to redesign work. Little by little we’ll offload tasks, projects, and workflows. And as we do, we’ll get smarter and smarter about redesigning our teams.
I liken the process to that of a carpenter who gets a new multi-function power drill. Before the drill he may have manually drilled holes, carefully selecting the drill bit and the level of pressure based on wood density. Now he drills holes faster, more accurately, and with more precision. Soon he just speeds through the process, spending more time on cabinet fit, finish, or design.
The same thing will happen to our HR tasks, projects, and designs. And these new digital employees are programmable! So once we figure out what they’re capable of we can adjust them, customize them, and connect them together. Eventually we’ll have intelligent assistants that operate as entire applications. And that’s the threat to incumbent software companies – the agents hollow out many of our existing applications.
How Do Our Digital Employees Impact Our Own Work?
One more observation. Many a few of the clients I talked with kept asking “what about our softskills?” What work is truly human?
I think that’s the wrong question. Rather we should ask the opposite: how much can I delegate to my new friends as fast as possible!
Have you been upset that your vacuum cleaner took away the rewarding human work of sweeping a floor? How much joy do you get from washing dishes? Did your dishwasher make you feel deflated when you stopped splashing around in the soapy water?
Of course not – these tools eliminated tasks we considered to be “drudgery.”
Well today, thanks to digital assistants, creating a pivot table to do cross-tab analysis has become drudgery. You can stop getting your hands wet with that task – ask Galileo or Copilot to analyze the data, and then ask him to chart it, add more data, and try new assumptions. The more we learn to use these new digital employees the more “drudgery” we can stop doing.
And consider complex “human-centered” activities like “change management.” A client asked me “how could Galileo help me with change management for our new HCM system?”
I answered her with dozens of ideas: ask Galileo for case studies of other companies and have it build a checklist to consider based on what other companies did. Then ask Galileo to build a training plan; ask it to read the user documentation and create a table of what features are new; then ask Galileo to rewrite that change plan by role. And finally ask Galileo to write a press release about success, craft some compelling communications to employees, and ask it to compute the ROI of all the steps eliminated.
These are all “manual” human tasks we do today and they take time and ingenuity to figure out. If you went through this process in Galileo you could ask your digital employee to save these steps and prompts in a “template,” and you have just taught your digital employee how to do change management. The next time you need him he can step you through the process.
As I started to explain this to my client I stopped and said: wait a minute. I can’t possibly show you everything Galileo can do. You have to try it for yourself.
And that’s my big message. Don’t wait for a vendor to drop a finished solution in your lap. These are intelligent, trainable, digital experts. You have to get to know them so you can figure out where they fit in your job, your projects, and your company. Just like you do with any new hire.
I say it’s time to get started. No more sweeping floors or washing dishes by hand. Let’s meet our digital employees, tell them about our projects, and ask for their help. Step by step, day by day, we can redesign our jobs to be more more productive, liberating us to do greater things.
The best HR & People Analytics articles of September 2024
September has been a phenomenal month. Indeed, in the ten years I’ve been writing the Data Driven HR Monthly, I can’t recall a month when there has been so much insightful content to choose from. I believe this is indicative of the journey HR is on from its traditional role as a support function to becoming a true strategic partner to the CEO and the board. As Janine Vos, Managing Board Member and CHRO at Rabobank, highlighted this past week at the Insight222 Global Executive Retreat, people analytics has an important role to play in elevating the HR function and enabling it to successfully navigate this transition:
People Analytics helps give the chief human resources officer credibility (with the executive team and board).
This edition of the Data Driven HR Monthly is sponsored by our friends at Worklytics
A New Way to Approach Manager Effectiveness
If you’re using eSat scores to evaluate Manager Effectiveness, you’re moving too slowly.
eSat scores are a lagging indicator of how it’s going. And in today’s distributed work environment, you can’t afford to wait.
Instead, use ONA-powered outcome driver analysisto identify what your best managers are doing differently.
You might measure behaviours like:
Manager Cross-Department Connectivity
Co-Attendance in Directs’ Meetings
Manager-Driven Disruptions (Slack DMs)
Curious to see what that looks like in practice? Find out how your managers stack up.
To sponsor an edition of the Data Driven HR Monthly, and share your brand with more than 135,000 subscribers, send an email to dgreen@zandel.org.
The Changing Role of the People Analytics Executive
My personal highlight of September was the 7th annual Insight222 Global Executive Retreat, which took place from September 24 to 26 at the Duin en Kruidberg for member companies of the Insight222 People Analytics Program®. I’ll share more about the Retreat in a separate blog in a few days time, but for now I'll highlight this year’s theme: The Changing Role of the People Analytics Executive, and the stellar cast of inspirational speakers:
Janine Vos discussed the strategic influence of the CHRO and the close partnership she has at Rabobank with the people data and innovation team led by Marc Jansen.
Prasad Setty shared insights from his 14 years leading people analytics at Google as well as painting a vision of the future of people analytics in the age of generative AI.
Kevin Friesen, Neora Myrow PhD, and Nancy Duarte delivered an interactive workshop on influencing through data storytelling.
Erin Meyer ended proceedings with a tour de force masterclass on leading across cultures I global organisations.
The Retreat is one of the services included as part of the Insight222 People Analytics Program. If you are a people analytics leader and would like to find out more, you can contact the team here.
Attendees at the Insight222 Global Executive Retreat 2024, Duin en Kruidberg, Amsterdam
September and October World Tour
As well as the Retreat, I’m speaking at and attending a number of events in October. This week, I’m in New York, moderating a panel on Workestration at the New York Strategic HR Analytics Meetup (Sept 30), and chairing People Analytics World (Oct 2 and 3). The next stop after that will be Paris, where I’ll once again have the privilege of hosting the main stage at UNLEASH World (Oct 16 and 17) - thanks to Marc Coleman and the team. Then it’s back to the US for the North America Peer Meeting for member companies of the Insight222 People Analytics Program®, which will be hosted by Phil Willburn and his team at Workday in Pleasanton (Oct 22 and 23). I hope to see some of you at one of these events. Thanks too to Marcus Downing for hosting me at the recent Mercer event in London where I had the pleasure of sharing the stage with Ravin Jesuthasan, CFA, FRSA (see here), and Jennifer Neumann for inviting me to speak at Workday Rising in Las Vegas (see here), where it was great to meet up with the likes of Priyanka Mehrotra, Richard Rosenow, and Cory Edmonds.
Speaking onstage at Workday Rising, Las Vegas, 2024
Register for an Insight222 webinar on October 10: Building the People Analytics Operating Model
Join me and the Insight222 team on October 10 when we’ll be hosting a webinar on the recently published research on. You can register for the webinar here.
Share the love!
Enjoy reading the collection of resources for September 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 August’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 published every Tuesday – subscribe here.
HYBRID, GENERATIVE AI AND THE FUTURE OF WORK
ANDY JASSY - Message from CEO Andy Jassy: Strengthening our culture and teams | JOSE MARIA BARRERO, NICHOLAS BLOOM, SHELBY BUCKMAN, AND STEVEN J. DAVIS - The Survey of Working Arrangements and Attitudes – September 2024 | ANNIE DEAN – Lessons Learned: 1,000 Days of Distributed at Atlassian
This special on hybrid work was inspired by Amazon CEO Andy Jassy’s announcement that Amazon is going back to five days in the office: “to further strengthen our culture and teams.” This comes hot on the heels of KPMG’s CEO Outlook Survey, which finds that CEOs are hardening their stance on returning to pre-pandemic ways of working, with 83 percent expecting a full return to the office within the next three years. Forensic analysis by Bruce Daisley (here), Phil Kirschner(here) and Nick Bloom (here) examines Amazon’s move and the validity of KPMG’s claim. This confirms that (1) Amazon is an outlier. (2) The findings by KPMG contradict the WFH Research that Nick is publishing every month, which shows working from home has remained flat since early 2023 and has stabilised at around 25% (see FIG 1). As Bloom suggest “shock sells,” which explains the extent of the media coverage about Amazon and the KPMG survey. To balance things out, I recommend reading about Dropbox’s Virtual First model (which chief people officer, Melanie Rosenwasser explains has “led to clear benefits, including higher employee engagement and retention.”). I also recommend reading a new report authored by Annie Dean summarising the findings from the first 1,000 days of Atlassian’s Team Anywhere approach to distributed work. As Rabobank’s CHRO Janine Vos urged in her session at Insight222’s Global Executive Retreat this week, the role of HR and People Analytics teams is to provide data that steers executive decision making around hybrid and return to office. It would be interesting to learn what data (if any) was used to inform Amazon’s decision to return to the office five days a week.
FIG 1: WFH is stable at c35% of days (Source: WFH Research)
BCG HENDERSON INSTITUTE - GenAI Doesn’t Just Increase Productivity. It Expands Capabilities
The ability to rapidly take on new types of work with GenAI - particularly tasks that traditionally require niche skills that are harder to find, such as data science - can be a game-changer for individuals and companies alike.
The BCG Henderson Institute follow-up their first landmark study on GAI in the workplace (see: How People Can Create - and Destroy - Value with Generative AI). The sophomore experiment tests how workers can use GenAI to complete tasks that are beyond their current capabilities. The findings from the study are illuminating: (1) Participants were able to instantly expand their aptitude for new data-science tasks, even when they had no prior experience in coding or statistics. (2) Those with moderate coding experience performed better on all three tasks, even when coding was not involved. This suggests that an engineering mindset - which coding helps develop - could be a key success factor for workers adapting to GenAI tools. The article also provides guidance on: When and how to pair humans with GenAI (see FIG 2), as well as visualising and detailing the workforce change-management implications (see FIG 3). (Authors: Daniel Sack, Lisa Krayer, PhD, Emma Wiles, Mohamed Abbadi, Urvi A., Ryan Kennedy, Cristián Arnolds, and François Candelon).
FIG 2: When and How to Pair Humans and GenAI (Source: BCG Henderson Institute)
FIG 3: Workforce and Change-Management Implications (Source: BCG Henderson Institute)
GARTNER - Hype Cycle for the Future of Work, 2024
Only 14% of organizations have reached the level of maturity where they are able to empower workers to embrace new ways of working.
Gartner’s inaugural Hype Cycle for the Future of Work (see FIG 4) highlights the core technologies set to transform how work is done by augmenting and enhancing human capabilities with intelligent technology. Five standouts from the analysis are: (1) Workers want a more personalised experience, and are building it for themselves. (2) CEOs are captivated by AI and are investing in new strategies. (3) Low digital workplace maturity is a barrier to improving worker productivity and time to competency. (4) Data Storytelling and Generative AI (already!) have entered the Trough of Disillusionment. (5) Hybrid Work and Self-Service Analytics are on the Slope of Enlightenment. The article also contains some illuminating analysis on a number of the ‘on the rise’ innovations including Exoskeletons (Tori Paulman), Cyberpsychology (Cynthia P.), Digital Twin of the Employee (Helen Poitevin) and Workforce Nudgetech (Rania Stewart). Thanks to Phil Kirschner for alerting me to this work in his excellent LinkedIn post on the study, which linked to an insightful article Phil co-authored with Natasha Ouslis, PhD and Dr. Julia Sperling-Magro on applying behavioural science and nudging to the workplace.
FIG 4: Hype Cycle for the Future of Work, 2024 (Source: Gartner)
NICKY DRIES, JOOST LUYCKX, AND PHILIP ROGIERS - What 570 Experts Predict the Future of Work Will Look Like
While it’s impossible to know exactly what the future of work will look like, it doesn’t stop (lots of!) people from having opinions. In their study, Nicky Dries, Joost Luyckx, and Philip Rogiers from KU Leuven, asked 570 experts to rank the likelihood of predictions made by technologists, economists and journalists. They landed on the sequence of events laid out in FIG 5, which get increasingly concerning and dystopian by the decade. Not one for the faint hearted!
FIG 5: A timeline of future of work predictions (Source: Dries et al)
MCKINSEY - Charting a path to the data- and AI-driven enterprise of 2030
Generative AI has increased the focus on data, putting pressure on companies to make substantive shifts to build a truly data-based organization.
These are the opening words to a recent article by McKinsey’s Dr. Asin Tavakoli, Holger Harreis, Kayvaun Rowshankish, and Michael Bogobowicz, which provides guidance on seven essential priorities for leaders to focus on to realise the data-driven enterprise of 2030. They argue that the key enabler to realising the potential of GenAI is data: “Without access to good and relevant data, this new world of possibilities and value will remain out of reach.” Three of the seven priorities outlined are (1) Data Leadership (“Companies need to find leaders skilled in governance and compliance, engineering and architecture, and business value"). (2) Talent (see FIG 6), and (3) Digital Trust.
FIG 6: New skills to manage GenAI will likely lead to both expanded and new data roles (Source: McKinsey)
PwC - 2024 Workforce Radar Report Executive Summary | Full Paper
The workforce of today won’t become the workforce of tomorrow unless businesses act right now.
But how? That’s the exam question that PwC’s inaugural Workforce Radar study attempts to answer across an insightful and thought-provoking report of 48 pages. The research identifies five workforce signals (see FIG 7) that business leaders and chief people officers can use to deliver enterprise-wide transformation. (1) Taking both a talent magnet and talent factory approach (e.g. levers such as meaningful work, skill-building, and culture). (2) Devising a location strategy that appreciates over time. (3) The intelligent enterprise – through HR harnessing and taking the lead on GenAI (see FIG 8). (4) Empowering transformation with a workforce balance sheet. (5) Investing in building transformative leadership. Kudos to the authors: Anthony Abbatiello, Julia Lamm, Reid Carpenter, Craig O'Donnell, and Christopher Hannegan.
FIG 7: Five Workforce Radar Signals (Source: PwC)
FIG 8: Emerging areas for Leading Digital HR Leaders to lean-in (Source: PwC)
PEOPLE ANALYTICS
NAOMI VERGHESE, JONATHAN FERRAR, AND JORDAN PETTMAN - Building the People Analytics Ecosystem: Operating Model v2.0 ARTICLE | FULL REPORT
In the August edition of the Data Driven HR Monthly, I highlighted the new Insight222 study on the evolution of the people analytics operating model. This month I’d like to highlight one specific aspect of the report about the role of the people analytics leader. The research, which was conducted by my colleagues, Naomi Verghese, Jonathan Ferrar and Jordan Pettman, found that three profiles of people analytics leader are emerging (see FIG 9): (1) Data and Analytics Specialist Leader (focused on a scope for data and analytics research, insights and analytical product development and deployment). (2) Analytics-led Strategy Leader (encompassing a broad set of analytics responsibilities: consulting, research, employee listening, product development, reporting, data governance, workforce planning and AI). (3) Portfolio Analytics Leader (responsibility for people analytics and one or more other closely associated topic, such as people strategy, HR technology, HR operations, skills management, or employee experience). Read the report for more detail on each of the profiles together with examples of each leader persona Featuring Anthony Ferreras, Aashish Sharma, and Alexis Saussinan.
FIG 9: Responsibilities of the three people analytics leader personas, aligned to the People Analytics Ecosystem (Source: Insight222)
COLE NAPPER, JIN YAN, AND BEN ZWEIG - What is happening to people analytics? A 15- year trend (Part 1)
How has people analytics employment changed in the last 15 years, and specifically how has the environment changed in the last two years? That was the question that Cole Napper along with Jin Yan and Ben Zweig sought to answer after being inspired by Alexis Fink to analyse these topics. The study identified a number of interesting – and perhaps counterintuitive – findings. These include: (1) People analytics positions in the US have actually declined in the last two years – the data suggests more than 1,000 people have left the field during this time (see FIG 10). (2) 83% of people leaving the field move to roles outside people analytics but mostly in HR. (3) People analytics positions are sensitive to changes in interest rates and money supply.
FIG 10: People analytics positions have been decreasing in the last two years (Source: Revelio Labs)
PIETRO MAZZOLENI - People Data Excellence: Driving Quality through Empowerment, Standardization, and Automation
Ensuring high-quality (people) data is crucial for building leaders' trust in data-driven talent decisions and reducing the need for manual reconciliation. Moreover, maintaining top-tier data quality is essential for the successful implementation of AI and GenAI technologies.
In the latest edition of his excellent People Data Platform newsletter, Pietro Mazzoleni breaks down the three ingredients IBM brought together to build Workforce 360, IBM’s internal people data platform, and deliver people data excellence: (1) Empowerment (“Putting Data & Knowledge in the Hands of Users”). (2) Standardisation (“Establishing a Unified Approach for data and processes”). (3) Automation (“Enhancing Efficiency Through Technology”).
FIG 11: Source – Pietro Mazzoleni
HENRIK HÅKANSSON - People Analytics: Generative AI | AMIT MOHINDRA – Definitions of People Analytics | KEITH MCNULTY - The Three Most Common Statistical Tests You Should Deeply Understand | LAURA HILGERS - How to Measure Quality of Hire, According to 4 Experts | JILL BARTH - How people analytics transformed this org’s HR from old-school to inspirational
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. Five are highlighted in this month’s edition. (1) Henrik Håkansson highlights a common predicament for people analytics leaders – stakeholder requests to implement GenAI. He offers sage advice on the ideal response: “GenAI is a solution. So naturally I ask: What is the problem? What is the value? Why would GenAI be better than what we are doing today? Are we trying to save money and cut costs, or actually do things better or faster?” (2) Amit Mohindra assembles a handy list of definitions of people analytics. (3) As Keith McNulty explains, hypothesis testing is one of the most fundamental elements of inferential statistics. In his article, Keith uses an example to show three common hypothesis tests (Welch’s t-test, Correlation test, and Chi-square test of difference in proportion) and how they work under the hood, as well as showing how to run them in R and Python and to understand the results. (4) Laura Hilgers’ article on the elusive quality of hire metric is a must-read for people analytics and talent acquisition professionals. It features guidance from four experts in the field: Hung Lee, Tim Sackett, SPHR, SCP (see FIG 12 for Tim’s equation to measure quality of hire), Stacey A. Gordon, MBA, and Jennifer McClure. (5) Finally, Sonia Boyle, CHRL - chief people officer at Gore Mutual, explains to Jill Barth HR Tech Editor how people analytics has been at the centre of the company’s HR transformation.
FIG 12: How to measure Quality of Hire (Source: Tim Sackett)
THE EVOLUTION OF HR, LEARNING, AND DATA DRIVEN CULTURE
DAVE ULRICH - Realizing Talent Advantage: Evidence and Implications from the Organization Guidance System
In 2020, Dave Ulrich and his colleagues at The RBL Group, developed the Organization Guidance System (OGS), which was designed to align desired stakeholder outcomes across four human capital pathways: talent, organisation, leadership and human resources. Five years on, in a new series of articles, Dave provides an update on the key findings to date. In this article, Dave focuses on the talent pathway, highlighting ten talent investments that deliver stakeholder value, and then presents analysis from 187 companies on the relative impact of these investments across five stakeholder outcomes (see FIG 13). The article then describes how individual companies can use the OGS to guide investment in the areas that will provide them with the greatest return.
FIG 13: Heatmap of impact of ten talent initiatives on five stakeholder outcomes (Source: Dave Ulrich)
JILL GOLDSTEIN, CHRIS HAVRILLA, CHACKO THOMAS, AND CATHY FILLARE - Reimagine human potential in the gen AI era: Revolutionizing work to boost business value
With their unique perspective and understanding of organizational culture, workforce needs, skills development, and change management, HR leaders are well-positioned to take a leadership role in their organization’s future of work strategy.
A new study by the IBM Institute for Business Value and Oracle, highlights the top concerns facing executives around the future of work, including the need for a skills-focused foundation and a well-defined strategy. The big takeaway for HR leaders is that while executives acknowledge that HR contributes to their organisation’s future of work strategy, not enough of them are in the driver’s seat. Only one in five executives say HR owns the future of work strategy in their organisation today. The report provides guidance to HR leaders on possible actions: (1) Build a future-ready culture that encourages experimentation. (2) Give your workforce a voice in the future of work strategy. (3) Drive technology transformation and champion AI use case adoption. The report also highlights critical workforce skills that will increase in demand by 2026 (see FIG 14). (Authors: Jill Goldstein, Chris Havrilla, Chacko Thomas, and Cathy Fillare).
FIG 14: Critical workforce capabilities—increases from today to 2026 (Source: IBM Institute of Business Value)
WORKFORCE PLANNING, ORG DESIGN, AND SKILLS-BASED ORGANISATIONS
MCKINSEY - The gen AI skills revolution: Rethinking your talent strategy
Developing the software talent companies need to grow means thinking in terms of skills rather than roles to navigate this period of uncertainty around talent.
According to McKinsey research, nearly 70 percent of top economic performers, versus just half of their peers, use their own software to differentiate themselves from their competitors. GenAI offers an opportunity to multiply this value. In the article, Alharith Hussin, Anna Wiesinger, Charlotte Relyea, Martin Harrysson, Suman Thareja, Prakhar Dixit and Thao Dürschlag, provide guidance on: (1) The new skills software teams will require. (2) How their evolution will alter roles and risks. (3) How companies can orient their talent management practices toward developing skills for greater flexibility and responsiveness. This includes grounding strategic workforce planning in business needs and skills.
The talent transformation starts with HR leaders developing a strategic workforce plan that’s built around skills.
FIG 15: Generative AI affects every phase of the software development life cycle (Source: McKinsey)
EMPLOYEE LISTENING, EMPLOYEE EXPERIENCE, AND EMPLOYEE WELLBEING
VOLKER JACOBS – Squaring the Circle: Why the old promise of P&O transformation –more for less – can finally be fulfilled
With effective, generative AI, P&O transformations can deliver a better, friction-free work experience for managers and employees. With a friction-free experience for managers and employees, we enable higher productivity and engagement levels. And it goes without saying that with AI taking on P&O tasks we can reduce cost of the function: More for less. Squaring the circle. Three ingredients: Data, AI, and EX.
In his thoughtful paper, Volker Jacobs, CEO at employee experience experts TI PEOPLE, highlights how HR transformations have historically undelivered their promise of more business value at lower cost. Instead, Volker argues, with the capabilities offered through AI and digitisation allied to rising expectations for better work experiences, the scene is now set to realise the dream of ‘more for less’. The catalyst? A shift from transformation focus on process to data as one of three ingredients to square the circle: Data, AI and Employee Experience leading to the business outcomes including improved productivity, better customer experience, and lower cost (see FIG 16).
FIG 16: Shifting HR transformation focus from process to data (Source: Volker Jacobs, TI People)
MALISSA CLARK - A Workaholic’s Guide to Reclaiming Your Life
In the latest edition of the Harvard Business Review, the Big Idea Series focuses on an increasingly important topic: Overcoming Overwork and Workaholism. Workaholism is defined in the lead article, by Malissa Clark, as: “Workaholism is when work dominates your thoughts and your activities, to the detriment of other aspects of your life, including but not limited to your relationships and your health.” Does that sound uncomfortably familiar? If so, like me you’ll probably welcome the six coping strategies Malissa outlines in her article: (1) Redefining “urgent”. (2) Reinventing the to-do list (see FIG 17). (3) Learning to say “no” and delegate. (4) Fixing the workaholic clock. (5) Controlling rumination. (6) Embracing rest and recovery.
Through mechanisms such as redefining what is and is not urgent, fixing the workaholic clock, and embracing rest and recovery, workaholics can unlearn toxic behaviors and reclaim their time and lives.
FIG 17: The Eisenhower Matrix (Source: Marissa Clark, Harvard Business Review)
LEADERSHIP, CULTURE, AND LEARNING
PER HUGANDER AND AMY EDMONDSON - Skills Training Links Psychological Safety to Revenue Growth
Organizational performance can be improved by viewing psychological safety as a trainable skill that individuals develop with practice.
Hugander Per and Amy Edmondson present a case study from Nordic bank SEB where training for executives on psychological safety and perspective taking was identified as the catalyst that enabled the investment bank to achieve revenues 25% above yearly targets in a strategically important market segment. The article provides four recommendations for leaders who want to make progress on strategic challenges and improve financial results by leveraging psychological safety and perspective-taking: (1) Focus on two levels in parallel: individuals and teams. (2) Expand leadership responsibility. (3) Keep strategy and performance front and centre. (4) Link skills to short-term gains to counteract perceived costs. For more on psychological safety, tune in to Amy’s conversation with me on the Digital HR Leaders podcast: How Learning to Fail Can Help People and Organisations to Thrive.
ANDREW WHITE, ADAM CANWELL, AND MICHAEL SMETS - Is Your Organizational Transformation Veering Off Course?
Leaders who achieve successful transformations create and maintain an environment where people can experiment, learn, and take ownership of their work — and ultimately feel good about their effort
According to a study by Andrew White, Adam Canwell and Michael Smets, 96% of all organisational transformations face significant challenges that can derail the whole program. Their research identified that changes in a team’s emotional energy (“the collective mood, vibe, and intensity of emotions within a group”) can signal when a transformation is in danger (see FIG 18). They then reveal the three-step process successful leaders use to navigate a turning point – increasing transformation performance by 12 times from 6 to 72 per cent: (1) They look for shifts in the team’s emotional energy (e.g. lack of clarity on how to proceed, ineffective collaboration, decreased engagement). (2) They dig into the underlying issue at play – by involving the whole team to decide the course of action. (3) They get to action — quickly (e.g. by creating team alignment, adjusting organisational priorities, and investing in the skills and mindset required for the transformed company).
FIG 18: How emotional energy can signal a transformational turning point (Source: White et al)
DIVERSITY, EQUITY, INCLUSION, AND BELONGING
LORI NISHIURA MACKENZIE, SARAH A. SOULE, SHELLEY J CORRELL, AND MELISSA C. THOMAS HUNT - How DEI Can Survive This Era of Backlash
When they’re given adequate support — like protected time, advancement opportunities, leadership development, and compensation for their DEI work — ERG leaders can act as a strategic conduit between employees and organizational leaders.
Despite recent backlash against and cuts to organisational DEI initiatives, researchers from the Stanford VMware Women’s Leadership Innovation Lab - Lori Nishiura Mackenzie, Sarah Soule, Shelley J. Correll, and Melissa C. Thomas-Hunt - argue in their Harvard Business Review article that DEI isn’t dead in the U.S. Instead, they say it’s experiencing a period of what social movement scholars call “closed doors,” where the obvious route for change is no longer easily accessible. They recently convened a gathering of 14 chief diversity officers (CDOs) to unpack what’s happening in their world. In the article, they highlight the striking similarities between current DEI strategies and the tactics used by feminist movement builders during times of closed doors — and present four strategies for continuing the important work of DEI while it’s under attack: (1) Sustain networks of people engaged in DEI work. (2) Preserve the collective memory. (3) Reframe and rename the work for survival. (4) Nurture the collective identity within the DEI community.
HR TECH VOICES
Much of the innovation in the field continues to be driven by the vendor community, and I’ve picked out a few resources from September that I recommend readers delve into:
JASON CORSELLO AND THOMAS OTTER | ACADIAN VENTURES - 2024 Future of Work 100 - An excellent resource compiled by Jason Corsello and Thomas Otter of Acadian Ventures counting down the top 100 venture-backed companies building businesses that make work better, fairer, more meaningful, and ultimately more productive. Together, the Future of Work 100 has raised a cumulative $29.5 billion with a total market valuation over $140.3 billion.
FIG 19: Source – Acadian Ventures
PHIL WILLBURN - Global Workforce Report: Top Talent Is Hard to Find, Harder to Keep – Phil Willburn, head of people analytics at Workday summarises the key findings of the recently released Workday Global Workforce Report: Restoring Trust Before Your Top People Leave covering hiring, turnover of top performers, meaningful work, and internal mobility. Phil also highlights the key actions for business leaders: (1) Rebuild trust through transparency. (2) Make work meaningful. (3) Personalise your employee experience efforts based on tenure. (4) Embrace AI strategically. An absolute must-read.
FIG 20: Current use of AI and ML for recruiting (Source: Workday)
CATHERINE COPPINGER - Manager Facetime: Why It's Useful and How to Measure It – The latest in a series of insightful articles by Catherine Coppinger of Worklytics analyses the importance of manager facetime and provides guidance on how to use the insights identified to improve team effectiveness.
FIG 21 – Source: Worklytics
BEN COWAN - You Don’t Need to Abandon Jobs to Become a Skills-Based Organization – Ben Cowan of Degreed explains that while jobs aren’t likely to disappear this shouldn’t hinder efforts by companies to adopt skills-based talent practices: “The reality is that moving away from jobs is not something most organizations are likely to do in the near term and it does not need to hold you back from adopting other skills-based practices.”
FRANCISCO MARIN - Towards a Network-First Future of Work – Francisco Marin of Cognitive Talent Solutions provides an insightful breakdown of the differences between Hierarchy-First and Network-First approaches across then organisational concepts (see FIG 22): “While hierarchies have long been the norm, favoring clear lines of authority and collaborative control, the network-first model prioritizes collaborative freedom, decentralization, and the strength of informal relationships.”
FIG 22: Hierarchy-First vs. Network-First Approach (Source: Francisco Marin)
PODCASTS OF THE MONTH
In another month of high-quality podcasts, I’ve selected five gems for your aural pleasure: (you can also check out the latest episodes of the Digital HR Leaders Podcast – see ‘From My Desk’ below):
JEREMY SHAPIRO AND CHRIS SHULTZ - HR, Workforce Automation, and GenAI at Merck – Jeremy Shapiro and Chris Shultz join Stacia Sherman Garr and Dani Johnson on RedThread Research’s Workplace Stories podcast to share how (and why) Merck is embracing AI to streamline HR processes, support innovation, and maintain ethical considerations.
COURTNEY MCMAHON – People Analytics at Colgate-Palmolive – Courtney McMahon joins Cole Napper and Scott Hines, PhD on the Directionally Correct podcast to discuss how to get a smaller people analytics function to punch above its weight, and how Colgate-Palmolive is using One Model to scale people analytics to HRBPs and the business.
KEITH MCNULTY – Applying Mathematical Principles to People Analytics Part 1 | Part 2 – In a two-part episode, Keith McNulty joins hosts Matthew Lampe, PsyD, Natasha Ouslis, PhD, and Bilal Alperen Ergun on the ScienceForWork podcast to discuss how mathematical principles can be applied to organizational data and people analytics.
JEFFREY PFEFFER - How Modern Work is Creating a Health Crisis - Jeffrey Pfeffer, professor of organizational behaviour at Stanford University and author of Dying for a Paycheck, joins Lars Schmidt on Redefining Work to discuss employee well-being and explore the harmful effects of workplace stress and poor working conditions on employee health.
SUE CANTRELL AND TRAVIS DION - Beyond productivity: Rethinking performance metrics – In an episode of Deloitte’s Capital H podcast, host David Mallon, talks to Susan Cantrell, and Travis Dion about moving beyond traditional employee productivity metrics —followed by a roundtable discussion featuring David, Sue, Julie Duda, and Diane Sinti.
VIDEO OF THE MONTH
LASZLO BOCK - Former Google exec talks about what makes a strong CHRO candidate
In an interview with Human Resource Executive, Laszlo Bock, former Head of HR at Google and a arch proponent of people analytics, provides guidance on what makes a strong chief people officer. He emphasises the need for HR executives to develop their understanding of business beyond a simple familiarity with their company’s products and services: “It’s not that (CHRO candidates) don’t understand that we make widgets. It’s that they don’t understand why we’re willing to pay $1.3 billion to buy a company but not $1.4 billion.” For aspiring chief people officers, I’d also recommend investigating the Berkeley Transformative CHRO Leadership Program, where Bock is co-faculty director.
BOOK OF THE MONTH
RAVIN JESUTHASAN AND TANUJ KAPILASHRAMI – The Skills-Powered Organization: The Journey to the Next-Generation Enterprise
Ravin Jesuthasan, CFA, FRSA and Tanuj Kapilashrami provide a step-by-step guide to designing, implementing and activating the skills-powered organisation. They outline why and how jobs are giving way to skills as the currency of work and why this pivot requires us to rethink everything we know about work. The inspiring cases presented in the book discuss how leading companies are reinventing themselves to be skills-based organisations and how this is helping them to transform value for customers, communities, and stakeholders.
RESEARCH REPORT OF THE MONTH
MARGRIET BENTVELZEN, CORINE BOON, AND DEANNE N. DEN HARTOG - A person centered approach to individual people analytics adoption – In their paper, Margriet Bentvelzen, Corine Boon, Deanne Den Hartog study people analytics adoption through the lens of the implementation of people analytics technology. They identify four profiles related to differences in user satisfaction and the frequency and versatility of PA technology use. They demonstrate that performance benefits, social influence, required effort, and facilitating conditions jointly affect the use of PA technology, but that the latter two might be the most influential factors. FIG 23 demonstrates the four user profiles identified in the paper: the skeptic diplomats, the optimistic strugglers, the optimists, and the enthusiasts. Thanks to Dirk Jonker for highlighting this insightful contribution to the field.
FIG 23: Source – Bentvelze, Boon and Den Hartog (2024)
FROM MY DESK
September saw the return of the Digital HR Leaders podcast after its summer sojourn with the first four episodes of Series 41, kindly sponsored by our friends at Visier Inc.. Thanks to Adedamola Adeleke and the team.
LYNDA GRATTON AND DIANE GHERSON - The Key Role of HR In Successfully Integrating a Blended Workforce – Lynda Gratton and Diane Gherson join me to discuss the impact of a blended workforce on organisational structures, the evolving role of managers, and the opportunities and challenges for HR.
ANGELA LE MATHON - How GSK is Using Data, Analytics and AI to Drive its HR Transformation - Angela LE MATHON, Vice President of People Data and Analytics at GSK, joins me to explore how GSK is utilising data-driven strategies and AI integration to future-proof their HR initiatives.
KEITH BIGELOW - HR’s Strategic Role in Managing the AI-driven Talent Restructure – Keith Bigelow, Chief Product Officer at Visier, joins me to explore the critical role HR plays in leading digital transformation—and how AI is changing the game.
TANUJ KAPILASHRAMI AND RAVIN JESUTHASAN - How to Build the Skills-Powered Organisation – Tanuj Kapilashrami and Ravin Jesuthasan, CFA, FRSA join me to share insights from their book, The Skills-Powered Organisation: The Journey to the Next-Generation Enterprise (see Book of the Month). Tanuj also shares insights from the skills journey at Standard Chartered, including how the bank quantified a saving of $60,000 per person by upskilling and reskilling employees to redeploy talent from sunset jobs to sunrise jobs.
Skills [are] becoming the currency of work and work flowing not to jobs, but to skills... If done well, it has the massive power to unlock untapped productivity potential within the company.
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 close to 500 roles – and has now been developed into a LinkedIn newsletter too.
THANK YOU
Srikant Chellappa and the team at Engagedly Inc for including me in their 8th annual list of the 2024 Top 100 HR Influencers
Hallie Bregman, PhD for her wonderfully generous post following our meeting at the Boston People Analytics MeetUp organised by Ramesh Karpagavinayagam – Hallie, it was wonderful to meet you too.
Paul Daley for referencing the Digital HR Leaders podcast episode with Diane Gherson and Lynda Gratton in his post on how HR strategy needs to support the independent / blended / contingent workforce of the future
Similarly thanks to Olimpiusz Papiez for his post sharing his takeaways from the podcast episode with Diane and Lynda
Thanks also to Jaqueline Oliveira-Cella for her post, are you ready for the shift, which was also inspired by the podcast episode with Diane and Lynda
Piyush Mathur for providing his takeaways on insight without outcome is overhead in relation to his speaking sessions at the Peer Meetings in New York and Vevey for member organisations of the Insight222 People Analytics Program
Esther Abraas for including my article, The role of Organisational Network Analysis in People Analytics, in her excellent list of ONA resources.
Wayne Tarken for his post on How AI can Help HR, which was informed by the digital HR Leaders podcast episode with Nickle Lamoreaux on how AI is transforming HR at IBM.
Thomas Kohler for including the podcast episode with Keith Bigelow in his weekly round-up of future of work resources.
The Talent Games for including me in their list of HR Leaders redefining the Future of Workin recognition of HR Professionals Day.
Finally, a huge thank you to the following people who shared the August edition of Data Driven HR Monthly and other content in the last few weeks. It's much appreciated: Craig Forman Zornitza Iankova, SPHR Brandon Merritt Johnson Hrvoje Bulat Rebecca Hone Michael Arena Emma Mercer (Assoc CIPD, MLPI) Dr. Max Muge Bakkaloglu Priyanka Mehrotra Kerry Ghize Deviprasad Panda Richard Stein Stela Lupushor David Balls (FCIPD) Emily Ricci Danielle Farrell Dan George Patrick Coolen Catriona Lindsay Katrina A. Stevens, CHRE Kouros Behzad Kathleen Kruse Martha Curioni Adam McKinnon, PhD. Greg Newman Dr Philip Gibbs Sally Smith Hanadi El Sayyed David van Lochem Amardeep Singh, MBA Rick Rome Ken Oehler Vaibhav Deshmukh María Victoria Sáinz Roshaunda Green, MBA, CDSP, Phenom Certified Recruiter Aysun Öz Serena H. Huang, Ph.D. Nelson Spencer Tristan Hack Penny Newman Vivek Ojha Aravind Warrier Francisca Solano Beneitez Kalifa Oliver, Ph.D. Stephanie Murphy, Ph.D. John Healy Greg Pryor Lewis Garrad Jose Luis Chavez Vasquez Audrey Burke-McCarthy, MBA, Adv Dip Coaching, MII Grad Aurélie Crégut Max Blumberg (JA) ?? Vanessa Monsequeira Shujaat Ahmad Jeff Wellstead Jackson Roatch Maria Alice Jovinski Rafael Uribe Truong Hong Ha (Mr Niem Tin) Dan Weiss David Hodges Toby Culshaw David McLean Dr. Peter Schulz-Rittich Timo Tischer Stephanie Denino Jacqui Brassey, PhD, MA, MAfN ?️ (née Schouten) Gianni Giacomelli Terri Horton, EdD, MBA, MA, SHRM-CP, PHR Placid Jover Andrews Cobbinah, MLPI, ACIHRM Emily Killham Al Adamsen Tim Frazier Tim Peffers Julie Asselin Chandresh Natu Anabel Fall Ralf Buechsenschuss Anna A. Tavis, PhD Marcela Niemeyer Meta McKinney, MLIS Aritra Majumdar Gustavo Araujo Vijaya Das Kirsten Edwards Graham Tollit Joy Kolb Remco van Es Ahmed Salah ?? Sebastian Knepper Melissa Beasley Bo Vialle-Derksen Malgorzata Langlois Abhilash Bodanapu Isabel Naidoo Marino Mugayar-Baldocchi Nirit Peled-Muntz Ron Ben Oz Littal Shemer Haim (ליטל שמר חיים) Joseph Frank, PhD CCP GWCCM Bob Pulver Jaejin Lee Kristhy Bartels Geetanjali Gamel Chris Hare Alicia Roach Caitie Jacobson John Gunawan Doug Shagam Davey Nickels Paul Davies Tatu Westling Mia Norgren Nick Lynn Alexandra Nawrat Gal Mozes, PhD Dave Millner Prachi Agasti Jacob Nielsen Matt Elk Chris Long Kimberly Rose Ilse Venter Søren Kold Irada Sadykhova Dave Fineman Agnes Garaba Sebastián Mestre Victoria Holdsworth Elpida Ormanidou Megan Buttita, MLIS Danielle Bushen Robert Bolton Stephen Hickey Dolapo (Dolly) Oyenuga Higor Gomes Irene Wong Ludek Stehlik, Ph.D. Sonia Mooney Mariami Lolashvili Joonghak Lee Raja Sengupta Swechha Mohapatra (IHRP-SP, SHRM-SCP, CIPD) Alfonso Bustos, Ph.D. Marcela Mury Olivier Bougarel Martijn Wiertz Veronika Birkheim
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 90 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 2024:
September 30 - New York Strategic HR Analytics MeetUp - Workestration: Working across human, digital and physical workplace dimensi (New York)
October 2-3 - People Analytics World (New York)
October 16-17 - UNLEASH World (Paris)
October 22-23 - Insight222 North American Peer Meeting (hosted by Workday in Pleasanton, CA) - exclusively for member organisations of the Insight222 People Analytics Program
November 12-14 - Workday Rising EMEA (London)
November 19-20 - Insight222 European Peer Meeting (hosted by Merck in Darmstadt, Germany) - exclusively for member organisations of the Insight222 People Analytics Program
More events will be added as they are confirmed.
Productivity
2024年09月29日
Productivity
Josh Bersin: With Thoughtful Design And Culture, Dropbox Proves Remote Work Is A WinnerDropbox, a company with a $7 billion market cap and over $2.5 billion in revenue, has adopted a "Virtual First" strategy in response to the pandemic, transforming its work model from lavish San Francisco offices to a remote-first approach. This shift was led by CEO Drew Houston and Chief People Officer Melanie Rosenwasser, moving away from an office-centric culture to enhance productivity and teamwork through remote work. The strategy includes home office stipends, Dropbox Studios for face-to-face interactions, and innovative meeting management services. Despite initial challenges, this approach has led to high employee satisfaction and a strong talent strategy, allowing Dropbox to thrive in a competitive tech landscape.
One of the most interesting tech companies we’ve studied is Dropbox, a $7 billion market cap rocket ship generating more than $2.5 billion in revenue. This kind of company, which sells a platform that competes with Microsoft, Google, and other major players, lives in a world of brutal competition: competition for product leadership, sales deals, and talent. And today, as AI engineers are in short supply, Dropbox has to attract the best and brightest to continue its growth.
In its early days, Dropbox was a typical San Francisco-based tech company with gourmet food, gorgeous offices, and a culture of lavish benefits. In the pre-pandemic 2010s this was the rage, and Dropbox became a hot place to work.
The pandemic upset that applecart. Not only did “work at home” obsolete the company’s real estate and gourmet investments, it forced the company to rethink its culture. The Chief People Officer, Melanie Rosenwasser, told me that the first few months of the pandemic were traumatic. Employees were upset by working at home and weren’t sure what the company stood for. She and Drew Houston, the CEO, had to rethink the whole operating model.
As Melanie described it to me, they took a risky, irreversible move. They decided to totally shift their operating model from that of “San Francisco gourmet offices” to “energized, empowered, team-based, remote work.” Not an easy decision.
Note that just this week Eric Schmidt, the ex-CEO and board member at Google, blamed Sundar Pichai for “remote work laziness” as cause for Google’s “falling behind in AI.” So the debate about remote work continues, and some of the most successful leaders still haven’t figured it out.
Well Drew, Melanie, and the Dropbox team placed a bet. Knowing that the pandemic had interrupted their campus investments, they dramatically shifted to a “Virtual First” strategy. And they told the company “we are moving away from an office-centric culture” and going to a model of remote-first work. And this included converting offices to Dropbox Studios as well as a carefully architected approach to teamwork, collaboration, and periodic face-to-face activity.
Rather than ask people to “come in 3 days a week” (this kind of policy bugs people because they drag themselves into the office just to zoom with others at home), they designed one of the most sophisticated approaches I’ve seen. Employees receive a generous stipend for home office improvements and the company now offers a series of programs, services, and tools to make team and personal productivity thrive.
While it seemed risky it worked exceedingly well. By holistically thinking about culture, management, teamwork, and productivity, the company developed a set of innovations that empower people to work at their best, meet with their teams at least one week per quarter, and come together when and where it makes sense. And this model, which looks like an HR innovation, became a business innovation that helps the company thrive.
While Dropbox lost a significant number of employees at first, now the company has one of the highest Glassdoor ratings in its industry (4.3, 85% recommend CEO, higher than Google). Dropbox wins awards for employment brand. And not only does Virtual First create productive operations, it helps the company build “tools for the new world of work,” which is where every company is going.
Work at home is complicated. In between dogs, kids, gardeners and delivery people we’re futzing with MS Teams, Zoom, Webex, Google Docs, and dozens of other tools. Most of them work well but they’re each different and inconsistent. Dropbox, as a “system designed for remote work” simplifies this enormously. Virtual First helps Dropbox test its products on itself.
Why has Virtual First succeeded? As Melanie and the team explains, the shift turbo-charged its talent strategy. Now Dropbox can hire people from any geography in the world (reducing labor cost) and they look for high-energy, passionate, high-performers (not employees who like the offices). Teamwork is stronger than ever.
I know, from our company, that this works well. We have 40+ people in our organization and we rely on frequent face-to-face meetings, an open culture, and tremendous amounts of training and communication to grow. Back when I ran our company in an office we hardly talked with each other unless we had a meeting. Things are much more collaborative and productive now.
Dropbox has proven this at scale.
You can read about Virtual First on the Dropbox website, but one of the innovations I want to point out is the company’s “concierge service” for meetings. (The Offsite Planning Team.)
When you as a leader want to have a meeting, this team helps you decide your objectives, reviews the outcomes you want to achieve, and then puts together a detailed plan (location, logistics, agenda, tools) to help you make it work. This removes enormous amounts of wasted time from managers and helps the company operate productively.
I cannot tell you how much time I’ve wasted “managing offsite meetings.” To have a seasoned, professional group that helps with this entire strategy in process is a godsend. For Dropbox, this team now knows precisely how the teams work and can continuously improve its consulting services to make sure face-to-face meetings are impactful. A “new manager introduction” meeting, for example, is different from a “get product ready for launch meeting” as you can imagine.
How does this apply to your company? Regardless of industry, I guarantee you have remote work teams. Many companies have front line workers (healthcare, retail, manufacturing, transportation) who have to locate with customers. But think about finance teams, IT teams, scientific teams, and HR. We all need productive remote work practices, and Dropbox has proven that a strategic focus on this area will pay off.
Melanie and I will be doing a webcast in the near future and she is joining us at our Irresistible 2025 Conference as well. Dropbox has taken the lead in this new world, and they want to share their learnings with all of us.
Productivity
2024年08月30日
Productivity
Josh Bersin: When Will The Trillions Invested In AI Pay Off? Sooner Than You Think.近年来,生成式人工智能(GenAI)的投资已达数万亿美元,但围绕其回报问题的争论不断升级。一些分析师,如麻省理工学院教授达隆·阿西莫格鲁(Daron Acemoglu)和纽约大学心理学与神经科学教授加里·马库斯(Gary Marcus),对AI的经济影响持悲观态度,认为其对美国生产力和GDP增长的推动作用有限,甚至可能导致市场崩溃。相反,另一派如高盛的全球经济学家则乐观地认为,AI有望在未来十年内大幅提高生产力。然而,文章指出,生成式AI的真正价值在于其特定领域的应用。例如,Paradox和Galileo等HR技术平台通过高度专业化的解决方案,显著提升了招聘和人才管理的效率。最终,文章强调,AI行业仍处于早期阶段,成功的关键在于找到具有专注性和精确性的创新解决方案。
In the last few weeks there has been a lot of concern that Gen AI is a “bubble” and companies may never see the return on the $Trillion being spent on infrastructure. Let me cite four analyst’s opinions.
Will Today’s Massive AI Investments Pay Off?
MIT professor Daron Acemoglu estimates that over the next ten years AI will impact less than 5% of all tasks, concluding that AI will only increase US productivity by .5% and GDP growth by .9% over the next decade. As he puts it, the impact of AI is not “a law of nature.”
On a similar vein, Gary Marcus, professor emeritus of psychology and neural science at New York University, believes Gen AI is soon to collapse, and the trillions spent will largely result in a loss of privacy, increase in cyber terror, and a lack of differentiation between providers. The result: a market with low profits and big losses.
Goldman Sachs Head of Equity Research Jim Covello is similarly pessimistic, arguing simply that the $1 Trillion spent on AI is focused on tech that cannot truly automate complex tasks, and that vendors’ over-focus on “human-like features” will miss the boat in delivering business productivity. (He studies stocks, not the economy.)
And Goldman Sachs Global Economist, who is a fan, estimates that AI could automate 25% of work tasks and raise US productivity by 9T and GDP by 6.1% over the next decade. He follows the traditional business meme that “AI changes everything” for the better.
What’s going on? Quite simply this new technology is very expensive to build, so we’re all unsure where the payoffs will be.
Buyers Are Looking For A Return Soon
If we discount the work going on at Google, Meta, Perplexity, and Microsoft to build AI-based search businesses, which make money on advertising (Zuckerberg essentially just said that in a few years AI will guarantee your ad spend pays off), corporate IT managers are asking questions.
An article in Business Insider pointed to a large Pharma company that cancelled their Microsoft Copilot licenses because the tool was not adding any significant value (Chevron’s CIO was quoted similarly in The Information).
Another quoted a Chief Marketing Officer who stated Google Gemini’s email marketing tool and the new AI-powered ad-buying tool performed worse than the human workers it was intended to replace (or support).
Given that these tools almost double the “price per user” for the productivity suites, I think it’s fair that CIOs, CMOs, to expect them to pay for themselves fairly quickly.
What’s Going On? The Big Wins Will Be Domain Specific
As with all new technologies that enter the market quickly, “the blush on the rose” is over. We’ve been dazzled by the power of ChatGPT and now we’re searching for real solutions to problems. And unlike the internet, where research was funded by the government, there’s going to be a lag (and some risk) between the trillions we spend and the trillions we save.
Given that ChatGPT is less than two years old and OpenAI has morphed from a research company into a product company, it’s easy to see what’s happening. Every vendor and tool provider is narrowing its AI “strategy” and not just pasting little AI “stars” on their websites, looking for useful things to do. And this process may take a few years.
In the world of HR, I think we can all agree that a “push the button job description generator” is a bit of a commodity. However if the AI analyzes the job title, identifies the skills needed through a large skills engine, and tunes the job description by company size, industry, and role, then it’s a fantastic solution. (Galileo does this, as does SeekOut, SAP, and some other vendors.)
The more “specific” and “narrow” the AI is, the more useful it becomes. Generic LLMs that aren’t highly trained, optimized, and tuned to your company, business, and job are simply not going to command high prices. So while we all thought ChatGPT was Nirvana, we’re now figuring out that highly specialized solutions are the answer.
Let me give you some examples.
The first is the platform built by Paradox, a pioneering company that started work on AI-based recruiting agents in 2016. Paradox, now valued at around $2 Billion, delivers an end-to-end recruitment platform that automates the entire process of candidate marketing, candidate experience, assessment, selection, interview scheduling, hiring, and onboarding. Most people believe its a “Chatbot” but in reality it’s an AI-powered end-to-end system that radically simplifies and speeds the recruitment process in a groundbreaking way. Companies like 7-11, FedEx, GM, and others see massive improvements in operational efficiency and both candidates, managers, and recruiter adore it. It took Paradox eight years to build this level of integrated solution.
The second is our platform Galileo. Galileo, which is now licensed by more than 10,000 HR professionals, is a highly tuned AI agent specifically designed to help HR professionals (leaders, business partners, consultants, recruiters, and other roles) do the “complex work” HR professionals do. It’s not a generic LLM: it’s a highly specialized solution designed specifically for HR professionals, and we’ve added specialized content partners and are building special integrations with other HR platforms. Our clients tell us it’s saving them 1-2 hours a day.
The third is the platform HiredScore, that was recently acquired by Workday. Founded in 2012, the HiredScore team built tools to help identify “fit” between individuals and jobs, and tuned its AI to be highly explainable, unbiased, and very easy to use. It took Athena Karp and the team a few years to nail down the use-cases and user interface but now HiredScore is considered one of the most powerful recruitment “orchestration” tools in the market, and is also used for internal hiring and many other applications. Every customer I talk with tells me it’s essential and saves them months of manual, error-prone effort.
The fourth is the platform Eightfold, which was invented in 2016 as a way to build “Google-scale” matching between job seekers and jobs. Through many years of engineering, product management, and ongoing sales process the company has become the leader in a new space called “Talent Intelligence,” now a billion dollar rapid-growing category. The company is about ten years old and now has some of the world’s largest companies building their hiring, career management, and talent management processes using AI. Companies like EY, Bayer, and Chevron now use it for all their strategic talent programs.
Each of these vendors, including others like Gloat, Sana, Arist, Lightcast, Draup, Uplimit, Firstup, and hundreds of others have patiently taken the power of Generative AI and applied it with laser precision to their solutions. Each of these companies is different, and as we work with them we see lightning bolts of innovation: not in AI itself, but in finding new ways to solve problems and do what I call “crawling up the value curve.”
This is the path for AI in the coming years. As with all new technologies, the “trough of disappointment” is always followed by the “bowling pin” of hitting the nail on the head. Innovators, entrepreneurs, and startup founders are the ones who will take GenAI and apply it in unique ways to solve problems. And soon enough, “AI-powered” will be a phrase we barely even need to say.
The Best Solutions Will Be Narrow Not Wide
GenAI solutions require a large “platform” of data, infrastructure, and software. That alone is not where the value resides. Rather, the big productivity advantages come after years of effort, focusing the data sets and working with customers to find the features, UI designs, and data sets that add enormous value. And we are still in the early stages.
If you want to learn more about HR Technology and AI, join me at the HR Technology Conference on September 24-25 in Vegas, or at Unleash in Paris in October 16-17. While I can’t predict who will win the core AI platform game (Microsoft, OpenAI, Google, Meta, Amazon will fight it out), I can predicts this: Generative AI will deliver massive improvements in business productivity. You just have to shop around a bit and wait for just the right solutions to arrive.
The Key to a Thriving Workforce? A Smart Approach to AI微软的最新数据强调了人工智能对员工赋权、活力和生产力的积极影响。领导者可以通过关注其员工队伍是否在“繁荣”中来促进良好表现,微软将“繁荣”定义为被赋予权力和充满活力地进行有意义的工作。员工信号调查显示,人工智能的使用能通过减少乏味工作并促进有意义的工作来提高生产力、努力和影响。人工智能工具还与更高的赋权和活力得分相关,表明员工队伍的“繁荣”。成功的关键在于将人工智能与支持性文化相结合,提供必要的培训,并使人工智能项目与公司目标保持一致。
New data reveals how access to AI can help employees feel more empowered and energized, and find more meaning in their work.
what’s the best way for leaders to foster good performance? How can they tell if their efforts are successful or not? Often, companies try to answer these questions by measuring metrics like engagement or financial results. And while those are critical to business success, at Microsoft, we also want to explore whether the workforce is thriving.
“Thriving has become the North Star for how we understand employees,” says Microsoft VP of People Analytics Dawn Klinghoffer, who leverages data to help leaders understand and improve employee’s experience. “We define thriving as being empowered and energized to do meaningful work. Are people excited to come to work every day, excited about the opportunities ahead?”
One of the ways we gauge this at Microsoft is with our Employee Signals survey, a biannual company-wide poll. The recent results not only offered insights into the tangible benefits of thriving, they also uncovered a key catalyst for fostering it: access to AI.
The Benefits of Thriving
We are focused on fostering a culture of thriving because our research suggests that doing so can boost how effective our workforce perceives itself to be. We also found that employees who are thriving are likely to have the highest scores on our indicators of high performance, like productivity, effort, and impact
Additionally, survey results suggest that employees who are thriving are more likely to go above and beyond what is expected of them. They take more pride in their work and they are less apt to look for employment elsewhere.
Recent Employee Signals survey results give us some new insights about what it means to thrive in this new era of work. We discovered that higher scores on what we’ve identified as the most important factors that support thriving—finding meaning in work, feeling empowered, and feeling energized—also translate to a measurable boost in productivity. Furthermore, access to AI seems to correlate with higher scores on each of these pillars.
Meaningfulness: According to our data, employees who find their work meaningful are 59% more likely to say they are productive at work—and 28% more likely to say they put in extra effort. Key to that is minimizing time spent on tasks that don’t feel meaningful. This is where AI comes in: AI assistants can lighten the load by generating rough drafts, sifting through piles of data, or simply acting as a sounding board and brainstorming partner to help people nail down a plan of action. Crucially, incorporating AI into the day correlated to a 20% jump in scores relating to meaningful work.
“What we find is that AI is really there to help you take friction and toil out of the system, and to remove the drudgery of work,” Klinghoffer says. “And when people are able to remove some of that drudgery, we see that they’re more productive, and they thrive more.”
Empowerment: Survey results also point to a future in which AI empowers people in their jobs. People who are empowered do not feel they have resource constraints, and they aren’t overburdened with people telling them how to do their work, Klinghoffer says, “so they have more freedom to do things the way they want and need to get the job done.” Access to AI tools and resources, we found, correlated to 34% higher scores for questions related to empowerment.
Energy: Our employees who say they feel energized are 44% more likely to say they feel proud of their work, and 22% more likely to say they take the initiative to be productive and put discretionary effort into their work. All levels of AI use— learning about it, grasping its value, incorporating it into processes and products, or simply having AI resources—correlated to higher reported energy levels. In fact, scores on energy-related questions for those using AI jumped almost 27%.
These results offer solid evidence that AI can be a catalyst for thriving and high performance. But how a company goes about making AI available will determine whether the company can reap these benefits. If employees are equipped with the right knowledge, tools, training, and resources to leverage AI in their work, they can begin to tap the full potential of an AI companion.
The key to success, Klinghoffer says, is integrating AI in a way that spans culture, learning, and people management. That way, everyone will understand how AI can help them focus on the most meaningful work.
The ABCs of Thriving with AI
Klinghoffer recommends keeping the following blueprint top of mind.
Accelerate alignment: Strengthen connections between employees, the company’s mission, and the transformative potential of AI. Clarify how AI initiatives align with the company’s goals and employees’ roles. Celebrate contributions to AI projects to highlight their impact on the company and customers.
“Employees who felt more connected to the mission and really understood how their work fits into the larger system were also the ones who were really thriving,” says Ketaki Sodhi, Senior HR Data Analyst at Microsoft. “When we looked at Copilot and employee sentiment around AI, these were also the folks who were willing to experiment and find ways to use AI to take some of the drudgery out of the day-to-day.” Smart leaders should seek out those internal champions and offer them support and encouragement.
Be inclusive: Create an environment where all employees feel equipped to engage with AI. This includes providing AI education, training, and resources, as well as fostering a culture of innovation and supporting a safe space for experimentation. Regular check-ins and feedback sessions can help employees express concerns and share ideas related to AI. Once users are encouraged and equipped to explore the possibilities of AI, our research suggests that a time savings of just 11 minutes a day is all it takes for them to start to appreciate its value.
Cultivate collective growth: Create a culture that empowers employees to decide how to do their best work, while investing in moments that matter together. Provide employees with the flexibility to plan their days and create time to meaningfully engage with AI. Encourage them to explore how AI can help them free up time for creative and strategic work. Then highlight use cases and foster collaboration among teams to encourage knowledge sharing.
Collective growth encompasses in-role experiences (how do we create time and space for employees to learn within their role?) and beyond (what comes next for me? Is there a viable career that excites me at this company?). AI can help with both—by eliminating the drudgery that keeps employees from doing more creative work, and by facilitating positive employee movement. “You see a huge boost. People get excited doing something new, growing their skills and experiences, and furthering their career,” Klinghoffer says. “A couple of months ago on my team we had people who were interested in a different role raise their hands, and we facilitated changes for about 20% of my org.”
利用组织网络分析(ONA) - 衡量员工绩效并优化战略作者: Maya Bodan, Don Miller, Sue Cantrell, Gary Parilis, 和 Carissa Kilgour
在快速变化的工作环境中,传统的办公室、工作时间和组织结构已逐渐失效,组织需要新的洞察力来理解、衡量和评估员工的绩效。特别是现在,了解人们如何互动、互动模式如何影响业务结果以及如何调整行为以改善这些结果变得更加重要。数据分析和人工智能 (AI) 的创新使这一切成为可能。
组织网络分析利用网络科学和特定指标来分析和可视化组织内部的沟通和信息流动。通过收集和分析调查和工作应用中的数据,组织可以利用数据、分析和 AI 的力量。组织网络分析揭示了传统组织结构图中没有的洞察力,例如人们如何协作、谁在决策中起到关键作用或者独立工作,以及关于信任和影响的情感。组织网络分析可以帮助领导者理解人际关系、可视化关系并找出成功的潜在障碍(图1)。
图1: 组织网络分析可以帮助发现组织内部的协作
衡量员工绩效
业务结果可以通过多种方式衡量。有时具体的定量指标是适用的;例如,一个专注于生产力的网络营销团队可能会强调点击次数、下载次数或发布的社交媒体帖子数量。改进指标,如“将网络流量增加X%”,使团队能够创新实现这一目标的方法。其他业务结果包括质量率和客户保留率的衡量。
然而,仅靠容易衡量的关键绩效指标并不能完整地呈现员工的生产力和业务影响。推动关系、发展和其他非量化人类结果的软性目标的结果对业务至关重要,尽管难以衡量。
雇主需要创造员工重视的工作场所。德勤研究显示,79%的领导者认识到他们有责任为员工创造价值,但只有27%的员工认为他们的雇主正在取得有意义的进展。在当前质疑面对面工作价值的环境中,量化人类结果带来了挑战。组织网络分析为领导者提供了分析洞察,优先考虑以人为本的指标,优化工作场所策略以提升整体员工体验。
理解个人员工绩效
组织网络分析 (ONA) 的洞察力在结合评估个人和团队绩效时尤其有用,这些绩效衡量会影响业务结果或生产力。
组织网络分析通过衡量与生产力相关的行为模式来评估生产力(需要对不同团队、职能和业务的生产力进行客观定义)。这些定义可以通过专家判断、焦点小组和访谈确定,或者通过数据分析进行量化。哪种模式是最优的取决于业务情况和需求。例如,有时,广泛的网络互动(与团队外部合作)是必要的,而在其他情况下,这可能会分散注意力——与直接同事合作是最好的(孤立的团队也可以是好的)。
非正式影响者通常不同于组织的正式领导者,他们可以提供关于如何独立于正式层级结构高效工作的宝贵视角。这些洞察力展示了员工人口在整个网络中的分布,以及职能、业务单元或地理位置等因素如何影响团队动态和生产力。在一个无边界的组织中,员工绩效超越了传统指标,突出了对非正式协作可见性的重要性。组织网络分析可以揭示隐藏的洞察力,展示信息在组织内部的真实流动方式,给领导者提供做出明智决策和优化员工绩效的洞察。
利用 ONA 优化工作场所策略
组织在平衡面对面和虚拟互动方面面临挑战。尽管许多组织鼓励员工返回办公室,期望面对面的互动能提升员工绩效和创新,但需要对人们如何实际工作的细致理解。高管希望办公室工作能激发创造力和联系,但往往面临昂贵的长期房地产承诺未得到充分利用的压力,这增加了定义办公室目的和价值的难度。通勤也会增加环境足迹,员工可能不愿失去灵活性。
通过组织网络分析,领导者可以回答一些关键问题:
有多少团队成员是共址的?
在什么情况下以及为什么需要共址?
什么工作可以或最好独立完成?
哪些工具和应用程序最能支持不同地点的工作?
一个重要因素是现场密度,它衡量一个人在办公室内近距离合作者网络的比例。更高的现场密度与更高的面对面工作的认可度相关。领导者可以利用组织网络分析的洞察来了解谁应该在一起工作以及何时在一起工作。理解这些非正式网络和影响范围可以为领导者解锁巨大的价值,以确定哪些团队应该共址以及共址时如何组织空间。通过虚拟方式沟通的独立工作者可能在办公室工作中看到的收益有限。有趣的是,新的数据显示“在松散联系网络中更可能产生创意”,这意味着与自己的直接网络外的合作可以促进创新。
结论
组织应负责任地使用数据、分析和 AI,以实时洞察员工在当今工作环境中的操作、协作和战略。这种改进的理解可以在多个组织层面支持价值创造和决策。组织网络分析提供了有关员工如何在混合工作模式和远程工作模式中跨职能和地理“边界”协作的绩效洞察,可以帮助领导层制定工作场所策略和政策。
作者
Maya Bodan
Don Miller
Sue Cantrell
Gary Parilis
Carissa Kilgour
贡献者
Yuki Iwase
Shruti Kalaiselvan
Ramyasri T M
Brennan Conway
Katherine Arriola
尾注
1 Deloitte, “Using network analysis to build an agile organization: Create organizational collaboration in a remote workplace,” 2020年10月27日。 2 Stephen Lancaster-Hall 等人, Humanizing productivity and performance: Productivity and performance in times of disruption, Deloitte, 2020; Deloitte, Beyond productivity: The journey to the quantified organization, 2023年5月。 3 Deloitte, Beyond Productivity: The journey to the quantified organization, 2023年5月。 4 Sue Cantrell 和 Corrie Commisso, “Outcomes over outputs: Why productivity is no longer the metric that matters most,” Deloitte Insights, 2023年7月19日。 5 Steve Hatfield, “Rethinking the ways we look at productivity in a Work from Anywhere world: How to evaluate remote worker productivity post-pandemic,” Deloitte’s Capital H blog, 2021年8月24日。 6 Worklytics, “12 metrics for more effective meetings,” 访问时间 2024年1月4日。 7 Deloitte Insights, New fundamentals for a boundaryless world: 2023 Global Human Capital Trends Report, 2023, 第80页。
来源:https://www2.deloitte.com/us/en/blog/human-capital-blog/2024/harnessing-organization-network-analysis.html