Inspired by the recent Wharton People Analytics Conference, in this special episode of the Digital HR Leaders Podcast, David Green takes us on a journey through the history, present and future of people analytics.

Incorporating insightful conversations with many influential leaders in people analytics, such as Prasad Setty, former Head of the People Analytics team at Google, and Dawn Klinghoffer, the Global Head of People Analytics at Microsoft, this episode will be exploring the evolution of people analytics over the past decade, its growing impact on businesses, and the future trends that will shape this field.

Throughout this episode, expect to learn more about:

• The Five Ages of People Analytics Model

• How people analytics has transformed over the past decade

• The growing influence of people analytics on organisations, as data-driven insights reshape decision-making processes and enhance business performance

• The key trends that will define the future of people analytics, including emerging technologies, ethical considerations, and the evolving role of HR professionals.

Whether you are an HR professional, business leader, or simply curious about the transformative potential of people analytics, this episode is a must-listen.

Support from this podcast comes from Charthop. You can learn more by visiting: charthop.com/digitalhr

David Green: Hi, I'm David Green, and welcome to a very special edition of the Digital HR Leaders podcast.  Today's episode was inspired by the Wharton People Analytics Conference, which I recently attended along with several of my Insight222 colleagues.  This year's event was momentous for two reasons.  One, it was the first in-person Wharton People Analytics Conference since the pandemic; and two, it was the 10th anniversary edition of the event. 

Since the first edition of the conference, the field of people analytics has advanced significantly and Wharton PAC, as it is affectionately known, has played an important role in influencing the field and enhancing the learning and curiosity of people analytics professionals all over the world.  Indeed, I know a number of practitioners and tech entrepreneurs who were inspired to get into the field, thanks to attending Wharton PAC over the last decade. 

Perhaps fittingly, the first session in this year's Wharton People Analytics Conference was titled The Next Ten Years, and saw the two people analytics leaders who have perhaps done more than most to inspire and shape the field, Dawn Klinghoffer and Prasad Setty, in conversation with Wharton Professor, Matthew Bidwell.  Together, Dawn, Prasad and Matthew discussed where people analytics has come from and where it is likely to go in the future. 

We thought that this would make a perfect theme for this episode of the Digital HR Leaders podcast.  So in the next 45 minutes or so, we will first look back at the history of people analytics, particularly in the last decade and how it has grown; then second, we'll reflect on the role the pandemic and other recent macroeconomic events have played in elevating people analytics from a principal focus on HR to a much more impactful focus on enhancing business value and the employee experience; and then third and finally, we'll also discuss the main factors shaping the future of people analytics, along with the key opportunities and challenges. 

To help tell the story, I will refer to the Five Ages of People Analytics model Jonathan Ferrar and I developed for our book, Excellence in People Analytics.  Along the way, you'll also hear insights from Prasad Setty, who for 14 years until 2021 led the people analytics team at Google, and Dawn Klinghoffer, the Global Head of People Analytics at Microsoft.  You'll also hear from other people analytic professionals we spoke to at the Wharton People Analytics Conference, and these include Tanu Dixit, Director of HR Data Science at Pfizer; Matthew Cohen, Head of Recruiting and Selection Analytics at Capital One; Sandy Zou, People Analytics Enablement Leader at Takeda; Jessica Smith, People Analytics Principal at Intuit; Ayanna Matlock, Deputy Chief Transformation Officer at Southeastern Pennsylvania Transportation Authority; and Garima Khator, Workforce Analytics Manager at Healthfirst. 

I hope you enjoy this episode, but before we get started, here's a word from the sponsor of this series of the Digital HR Leaders podcast. 

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Welcome back to this special episode of the Digital HR Leaders podcast inspired by the recent Wharton People Analytics Conference, where we will discuss where people analytics has come from, where it is today, and where it is likely to go in the future.  In this first part, which you will hear from me, we will look at the history of people analytics, being mindful that to understand where the field is today and where it may go in the future, we can learn a lot from the past.  In the research we undertook for our book, Excellence in People Analytics, Jonathan Ferrar and I concluded that there are five ages to describe the history and future of people analytics. 

The first three of these relate to the past: the Age of Discovery, the Age of Realisation, and the Age of Innovation.  First, the Age of Discovery, which ran for a century and started with Frederick Taylor's book, The Principles of Scientific Management, in 1911.  Taylor's ideas sought to optimise tasks, drive efficiency and maximise productivity through measuring everything employees did.  A notable Taylorist of that era is the Ford Motor Company, which famously used scientific analysis to automate processes in the car manufacturing plant and therefore provide efficiencies and increase production speed. 

The Age of Discovery was long and took in milestones such as mass industrialisation in the era after World War II, as well as the emergence of the role of the industrial organisational psychologist, a core capability in leading people analytics functions of today.  The age of discovery also saw the evolution of the human resources function in the 1980s and 1990s, from a sole focus on personnel administration to a wider focus on recruitment, development, reward and performance management.  This created a need to measure processes and the efficiency by which people were hired, deployed and developed across the workforce. 

This led eventually, in the first few years of the 21st century, to a number of pioneering organisations hiring people into formal HR analytics or employee engagement functions.  The onset of the internet and the ability to collect quantitative and qualitative data in large volumes changed the desire and ability to measure more than just the human resources processes.  These early teams in large multinational organisations, which included Google or Microsoft, often consisted of only a few people delivering work such as annual employee engagement surveys.  Overall, people analytics functions of the Age of Discovery were administrative, white-glove functions, tackling data collection, statistics, reporting and business diagnosis, typically for a handful of senior executives and only occasionally undertaking analyses on complex business topics at the behest of the CEO. 

It was the 2008 Global Financial Crisis that changed everything for the field of people analytics.  Ushering in the Age of Realisation, it wouldn't be the only global crisis that would propel people analytics forward.  The advent of big data and the use of analytics by business functions such as marketing, combined with a desire to measure and monitor everything with an adequate level of efficiency and effectiveness, led to the realisation that analytics was critical.  People analytics teams that delivered insights to senior business executives allowed these organisations to flourish in the post-Global Financial Crisis era. 

The Age of Realisation was epitomised by the development of maturity models and the emergence of leading practices in big technology companies in particular.  Large teams established in companies, like Google, Microsoft and IBM, could use their external products teams' expertise to translate this into a similar experience for their employees.  These teams grew fast and focused on often complex predictive analytics projects.  With senior executive sponsorship, they could then scale these solutions, harness their technology prowess, and deliver significant value. 

In the early 2010s, under the stewardship of Prasad Setty, who you'll hear from in part two and part three of this episode of the Digital HR Leaders podcast, Google took people analytics mainstream with Project Oxygen, which scientifically communicated the commonly held belief of the attributes of managers, validated in Google language for Google as a company.  A number of mainstream media, such as The New York Times, published glossy pieces on Project Oxygen.  It acted as a catalyst for people analytics by helping to change how business executives and HR leaders saw the value of human resources processes, as well as how analytics could predict the capabilities and behaviours needed to achieve competitive advantage. 

Google followed up Oxygen with Project Aristotle, a brilliant study that looked how to build the perfect team with accuracy.  Google's journey in people analytics was memorialised by its then Head of People Operations, Laszlo Bock, in his 2015 book, Work Rules!, while he, Prasad Setty, and other senior Google HR and people analytics professionals spoke at conferences such as Wharton PAC. 

The mid-2010s marked a change in trajectory for the people analytics field, as the Age of Realisation transitioned into the Age of Innovation.  The primary driver was executive expectation.  Chief Human Resources Officers were increasingly being asked to modernise their workforce in response to market demands.  The Age of Innovation was characterised by new models, new uses of technology, specialisation, an increase in the number of practitioners entering the people analytics profession, and new approaches to creating business value through people data. 

The Age of Innovation saw people analytics shift from being a supplementary function within HR to a core component of the people strategy of the business overall.  By 2017, a study by the Corporate Research Forum found that 69% of organisations with 10,000 employees or more had a people analytics team.  By the end of the decade, people analytics teams had been founded in organisations of all sizes, industries and geographies. 

It was during the Age of Innovation that specialist conferences, like the Wharton People Analytics Conference, helped inspire the field, accelerate its growth, and support the learning of people analytics professionals, especially through providing examples of how fields like sport and medicine were using analytics to drive high performance, create value, and improve the wellbeing and experience of people.  As Google had been the poster child of people analytics during the Age of Realisation, so Microsoft took on the mantle during the Age of Innovation, and indeed to this day. 

Just as Prasad Setty and Laszlo Bock, together as Head of People Analytics and Head of HR, had inspired the field and catalysed interest in people analytics through their work at Google, so Dawn Klinghoffer and Kathleen Hogan did the same through the work they were leading at Microsoft.  As a new decade dawned, people analytics was well positioned to continue its growth, but the emergence of a new deadly disease in Wuhan, the largest city in the Hubei Province of China, was about to propel people analytics forward into a new age, the Age of Value. 

We'll discuss this and hear from Prasad, Dawn, and other people analytics professionals about the impact of the Covid-19 pandemic on people analytics after the break. 

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Welcome back to this special episode of the Digital HR Leaders podcast on the past, present and future of people analytics, inspired by the recent 10th anniversary edition of the Wharton People Analytics Conference.  In the first part of the episode, we learned about the first three ages of people analytics, the Age of Discovery, the Age of Realisation, and the Age of Innovation, which took us up to 2020.  In part two, we'll look at the impact of the pandemic on people analytics, how it propelled people analytics into the Age of Value, and hear from Prasad Setty, Dawn Klinghoffer, and others as to where the field of people analytics is today. 

2020 was a pivotal year in people analytics.  Just as the global financial crisis had propelled people analytics into a new age a decade earlier, so the triple crises of the global Covid-19 pandemic, racial inequality, and financial uncertainty did the same in 2020.  This ushered in what Jonathan Ferrar and I described in Excellence in People Analytics as the fourth age of people analytics, the Age of Value.  Jonathan and I wrote that the age of value was characterised by a shift in emphasis for the field where people analytics is not just about HR, but people analytics is about the business. 

At the Wharton People Analytics Conference, we asked Prasad Setty, who was Head of People Analytics at Google for 14 years, what impact the pandemic and other crises of this decade has had on people analytics?

Prasad Setty: It absolutely has had a tremendous impact on what is really valued, right?  The context of organisations has shifted as well as the expectations of people, especially because of what has happened in society.  And I think in the US over the last few years, I think there have been things that have happened that have truly influenced how corporate America thinks about diversity, equity, and inclusion.  I think those have all been forces that have been for the good, and we are trying to really reflect in our workplaces how we can shift away from racial- and gender-based injustices that have just been part of society for a long time. 

So I think that really shifted a whole bunch of attention within people analytics to try and understand how we can design fair and equitable processes and systems on the people side, because people decisions are so valuable, so important, and there have been a lot of historic issues with how those decisions were made.  So that was one big shift that I think certainly is not something that we will solve in a little bit of time, but it's one where I see continued attention and investment, both on the people analytics side, as well as in the priorities of corporate America, which is, I think, good. 

The second one, certainly the global pandemic forced the largest natural experiments that we have seen in terms of how and where and when people work.  And certainly, there is a continued conversation about hybrid work or remote work or in-office work, but also about when people work and how they get together.  And when I was at Google, I was leading a response on the people side for COVID and thinking about the future of work, and we would talk about three outcome variables that were all important for us to solve for: productivity, both at the individual and team level; wellbeing, physical as well as mental; and then connectedness, how connected you are to the organisation and to the team.  And all of those are important for long-term sustainability and the viability of the organisation. 

So, as we thought about all the parameters that we could shift in terms of the location that people were working in, and how they got together, those were always the outcome variables that we came back to; are we trying to influence them in ways that work for us?  And so, again, a lot of people analytics was all in that sense of experimentation, but a lot of feedback and voice back from the employees about what is working for them, right?  And so, I felt that it was really an involved process and it still continues too.  So, those are at least a couple of examples of how I think recent shifts externally have influenced what organisations need to work on.

David Green: We also spoke to Dawn Klinghoffer, who has been leading people analytics at Microsoft for the last 20 years.  She agreed with Prasad and highlighted how the pandemic and other macroeconomic events had shaped the work of her team at Microsoft.

Dawn Klinghoffer: Recent macroeconomic events and just this notion of hybrid work has been such a critical component of the work that we have been doing and the research we've been doing at Microsoft.  Both of those just rely on truly understanding what your employee population needs from managers and leaders at this time.  And so, I feel like our employee listening systems have really helped us to shape a lot of the programs that we're developing.

David Green: We also spoke to other people analytics practitioners at the Wharton People Analytics Conference; all agreed with Prasad and Dawn that the pandemic had acted as a catalyst in increasing the importance and influence of people analytics in their organisations.  We'll hear from three of those practitioners now.  Firstly, from Garima Khator, Workforce Analytics Manager at Healthfirst.  Garima highlighted how the pandemic is impacting the type of analyses they do at the company.

Garima Khator: I think pandemic was almost like a pivoting point for the role of people analytics in the organisation.  Even today, when we turn out report and analysis, we do a pre-pandemic analysis, and then we do a during-pandemic and a post-pandemic analysis, that could be hires, headcount, terminations.  Everything changed during the pandemic, everything changed the way we look at some of these processes and what impacts these processes.

David Green: We also spoke to Matthew Cohen, Head of Recruiting and Selection Analytics at Capital One.  He talks to how the pandemic saw an increase in the frequency and volume of employee surveys.

Matthew Cohen: So the pandemic has not actually changed the way that people analytics is done, but it has changed some of the topical areas of focus.  The areas of focus that obviously have come more into view, given the pandemic, are things like return to work or how you understand whether we can operate in a hybrid environment; how people are feeling about these environments has become even more paramount.  And I actually will revert back and say that there is one key way that has changed things, which is we've altered our approach to surveying and have invested more in being able to do more frequent or quick surveys and have faster turnaround times, because there's issues that come up that need answers and leaders are willing to accept and be guided by those answers today.

David Green: The final practitioner we'll hear from in this second part of this special episode is Tanu Dixit, Director of HR Data Science at Pfizer, who of course were one of the companies that developed a COVID vaccine.  Tanu talks about the impact of the pandemic on people analytics at the company.

Tanu Dixit: So I would say representing my company, Pfizer, I think it's shaped us quite well.  I think we took in it a challenge, and rightly so, to produce the vaccine we did.  And with it came this belief that -- so our purpose as a company is breakthroughs that change patients' lives, and I think this was a living example, even more so of it, for us as a company.  And I think what that brought up is this whole notion coming from top leadership down that if we can make a vaccine in this breakthrough time, in the crunch situation we were in, could we think about just generally doing all our work this way, right?  I know part of it has burnout challenges, has wellbeing at play on one side, but is also the idea that do we really need to get caught up in a lot of what could be done better and faster and make things move along in the right manner. 

So I think that, for one, has worked to our advantage both as a company and as a people analytics function, and we've got this great opportunity to try out some very cool, yet very informative, analytics projects, which rightly so will inform a lot of these changing dynamics at Pfizer.  So looking forward to that.

David Green: So the pandemic has certainly led to an acceleration in the growth of people analytics, its importance and its influence on leaders.  It supported companies in areas such as business continuity, employee wellbeing, and of course in helping to formulate return-to-office strategies and approaches to hybrid.  But as we'll hear in part three of this episode, which looks towards the future, people analytics still has a lot of room to grow.  First, let's take a short break. 

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Welcome back to this special episode of the Digital HR Leaders podcast on the past, present and future of people analytics, inspired by the recent 10th anniversary edition of the Wharton People Analytics Conference.  In the first two parts of this episode, we looked at the past and present of people analytics and learned how the pandemic has accelerated its growth and impact, and in many respects shaped the work and priorities of people analytics teams today. 

In this third and final part, we'll look to the future.  You'll hear a lot more from Prasad Setty and Dawn Klinghoffer and others, but first back to the Five Ages of People Analytics.  You'll remember that at the start of part two, I highlighted how the pandemic propelled people analytics into a new age, the Age of Value, as Jonathan Ferrar and I wrote in our book, Excellence in People Analytics.  When we look to the future, Jonathan and I envisage that once the value from people analytics is accepted and delivered at scale repeatedly across the business as a whole, globally, then people analytics will move into a fifth age, which we called the Age of Excellence. 

So to judge how long into the future this could be, we asked the practitioners we interviewed at the Wharton People Analytics Conference three questions about the future of the field.  First let's hear from Prasad Setty, who as a reminder, led people analytics at Google for 14 years until 2021.  We asked Prasad first to highlight the key factors that will shape the future of people analytics and as you'll hear, he outlines three waves of impact a people analytics function can have on HR, on the organisation and critically and significantly, on employees. 

Prasad Setty: I think what we have seen over the last 10 to 12 years is people analytics is no longer a new and novel concept or capability, but instead it is something that is recognised as an asset or as an important part of the people puzzle.  And so, I really love that where we are.  And so, that then means that we are in a position to try and see where we take the field from here, right?  And so, for me, some things that remain the same are what our focus is on.

A lot of people analytics team start off with trying to optimise for the HR department because that is usually where they are housed.  And so it's really about, "Hey, can I do a better job with recruiting or with compensation or with benefits or employee development?", etc, and that, I think, has to be perhaps the first set of problems that organisations tackle with this capability. 

A second set of higher impact capabilities is to optimise organisational health.  So look beyond the HR department, think about the organisation that you work for and how you make sure that information is flowing well, that people are collaborating and not stuck in silos, that it has good leadership and teams that work well together.  All of those are components of organisational health and there's a lot that the people analytics capability can add to diagnosing, diagnosing how things are working, generating insights on what could be done better, and truly leading action towards that. 

Then, for me, the third and highest order sort of impact of people analytics is to improve the lives of people.  And so when I joined Google, my first decision was to rename the name of the group from HR Analytics to People Analytics, because I wanted it to be truly for the people of Google.  And so I think it's really about helping everyone get to live their fullest potential.  And that could be in terms of career development and growth, skills enrichment, but it could also be about their health and about their retirement savings and so on. 

So there's a lot that we can do to empower people to make better decisions for themselves, and so those are certainly the arcs that I would see for the community.

David Green: In her answer to the same question on the factors that will help to shape the future of people analytics, Dawn Klinghoffer, who leads people analytics at Microsoft, talks about the importance of building capability in HR professionals by giving them tools and techniques to ask good questions. 

Dawn Klinghoffer: So I think in the future, we're going to have to teach people how to ask the right questions.  It's different right now; we're really focused on building capability for HR professionals to understand data and use data; but in the future, they're going to have to be able to go to an intelligent engine and ask questions in a way that's going to yield really good insights that they can use to make decisions.  And so if folks know how to ask the right questions, they'll get accurate information.  If they're not asking questions in the right way, then they might get information that's not actually helpful.

David Green: So as Dawn said, building capability in HR professionals is one factor that will help shape the future of people analytics and the ability to scale it successively across organisations.  Let's hear now from Matthew Cohen, Head of Recruiting and Selection Analytics at Capital One.  Matthew highlights three other key factors: regulation, technical capabilities and people.

Matthew Cohen: I think there's two key factors, I should say three key factors, that shape the future of people analytics: one is going to be regulation; two is going to be actually advances in capabilities, technical capabilities; and three is going to be people.  I listed regulation first because the regulatory environment in which we have to operate will obviously change the direction or setting for what is able to be done when it comes to difficult topics, like diversity and inclusion, or even just the use of more advanced modelling and techniques to make better decisions. 

Obviously that is predicated on a belief that all of the analytics and capabilities are going to move forward at this pace that we've been seeing in the last few months.  And then I listen to people because people power all of that, and I think there's been more and more people interested in this type of work, so they're coming in and building their capabilities.  And that means that the mindsets will shift in terms of how you solve the problems, which helps unlock those capabilities, which hopefully we won't regulate too tightly.

David Green: Perhaps not surprisingly, a big topic of conversation at the Wharton People Analytics Conference concerned ChatGPT and its potential impact on the world of work, and also people analytics.  Sandy Zou, People Analytics Enablement Lead at Takeda, highlighted this when we interviewed her as one of two factors she believes will shape the future of people analytics. 

Sandy Zou: The main factors I think could impact the future work of people analytics I think firstly is the technology.  You probably know everyone is talking about ChatGPT, so how are we going to utilise this technology or resources to apply to our work day to day?  It could be a game changer because personally I've been using it a lot at my work and whether editing the emails, the speech, or even checking what's wrong with my code, it's very helpful, it comes very handy, and I can see it comes to be used for a lot of different ways, even helping me putting together the presentations, giving me more creative ideas on how to tell the story to leaderships about the data insights we've been seeing, or even recommended actions from what other organisations are doing.  So, that's the biggest, one of the biggest ones, I think, impact the work of people analytics. 

The second one, I think it could be the long-term impact from COVID on people's perspective on what does work actually mean to them.  I think before COVID, there were relatively less people thinking about what work truly means to them.  But nowadays, since people experience that pandemic period, they realise it can be less important or it can be even more important, so people have more thoughts putting into the meaning of work.  I think the feelings or the relationship they have with work definitely could impact our analytics future as well.

David Green: So clearly there are a number of factors that will help shape the future of people analytics and potentially propel it forward to the Age of Excellence.  One of the aspects I love the most about people analytics is the genuine passion and enthusiasm those of us that work within the space have about what can be achieved with people analytics, while being vigilant about areas such as ethics, privacy and bias. 

The final two questions we asked the practitioners we spoke to at the Wharton People Analytics were, one, what excites you most about the future of people analytics; and, two, what is your biggest concern about the future?  Let's hear again from Prasad Setty, first on what excites him about the future of the field. 

Prasad Setty: I think there are a few forces that are really exciting.  One is that we now have, through AI and ML, the capability with these large language models that are going to help us decipher and understand and derive more meaning from non-quantitative data.  There's a lot of qualitative work that is done in the people space, and there's a lot of information that we have collected in text and emails and so on, and I think there's a lot more value that we could derive from that.  So I think there is a part of people analytics that is going to use these new forms of data and have more insight.  So that is one part of it. 

The second part is that I think you will have the opportunity to have much more personalisation around these products.  So, a lot of analytics right now is done on large data sets and therefore you're trying to think about what is statistically significant for a group of people.  But each of us is different in our own ways, and we each might have a different inclination toward what makes us more productive, when we learn best, when we collaborate best, and so on, depending on our personality traits, depending on our starting set of skills, and so on. 

I actually think that by training these corpuses based on your own data, how you have learned in the past, who you interact with, what times you like to take your meetings, when you like your focus time, we might be able to have a much more personalised experience for you that rests on top of the basics of social sciences, and then is fine-tuned to your particular circumstances.  That, I think, is a great opportunity. 

That leads me to a third area, which is really about the productisation of people analytics.  And I think today, a lot of insights end in PowerPoint slides, or my favourite, Google Slides.  But still, that is where they end.  But I do think that there is a new set of amazing tools that are all using different types of HR technology.  So I think for people analytics, we'll be able to infuse our insights and push them in through products that everyone can use, managers, leaders, individual employees, they can all use these tools and that I think is very exciting too.

David Green: On the flip side, when addressing his concerns about the future of the field, Prasad focused on the ethical and responsible use of people analytics.

Prasad Setty: There's a lot of talk about how we want to do and deploy AI ML tools ethically and responsibly and that we want to make sure that we are compliant with regulations, new ones that might be coming around, as well as existing ones.  And so I think about it similarly for people analytics too.  I would love for every organisation to commit to a standard of what is an ethical and responsible use of people analytics. 

There are certain things that make me cringe for the profession when I hear about employee monitoring, whether they're tracking your keyboard strokes or monitoring whether you're looking at the screen and things like that.  Those are all the things that corrode trust and certainly don't build confidence that the organisation and the employee are working together.  And so those are the kinds of things that I think put the profession in a bad place, and so I would hope that by adopting better ethical standards about how people's data and privacy are protected, and how information is used responsibly to help them, not to control them, not to manage them, but to help them and empower them, that is what I would look for.

David Green: Similarly to Prasad, Dawn Klinghoffer highlighted HI both as an opportunity and a concern for people analytics in the future.

Dawn Klinghoffer: Well, I think what excites me the most is just this foray into AI and the different scenarios that we're going to get to tackle that really helps managers and leaders become more effective and successful in the roles.  And as my EEO says, "Remove the drudgery from work".  My biggest concern is also about AI.  It's about the responsible use of AI, it's about data privacy, data confidentiality, and ensuring that everything that we build keeps those principles front and centre.

David Green: One of the other practitioners we spoke to at Wharton was Ayanna Matlock, Deputy Chief Transformation Officer at the Southeastern Pennsylvania Transportation Authority.  We also asked Ayanna what excited her about the future of people analytics, and what she says about how insights from people data can support an empathetic culture is very interesting. 

Ayanna Matlock: So, what's really exciting to me is using the data to show empathy, to show that you care.  What I find in my role is that people will show up for you if they feel like they are being supported and appreciated and recognised for the hard work that they're doing.  It doesn't matter what the job is, but every position that we have where I work is needed, it's necessary.  We're a very lean ship and when someone is not able to do the things that they were thinking that we need them to do, you can tell, you can feel it, you can see it, and then someone else has to take on that role or that structure, and then that causes folks to be burnt out.  We don't really understand roles and responsibilities sometimes, so then that causes confusion. 

But if you could care about your workforce in a way that takes all these different things into consideration, I feel like people are going to show up for you when you're making great change, when you're trying to do things differently.

David Green: The final person we'll hear from of the practitioners we interviewed at Wharton is Jessica Smith, People Analytics Principal at Intuit.  In her answers, Jessica highlights the importance of scaling people analytics and using technology to democratise data across the enterprise.  She also provides a word of caution on algorithmic bias, as one of many attendees at the conference who were inspired by the presentation of Cathy O'Neil, author of the seminal Weapons of Math Destruction.  Here's what Jessica told us.

Jessica Smith: What excites me most about the future of people analytics are all the new tools at our disposal, as well as the interest in our space.  I talked a little bit about how there is this huge demand, which is great, and we need to learn to scale to that demand.  So bringing in all of these data visualisation tools, algorithms used responsibly, as we were just hearing about, there's just so much to play with right now.  And so, it's exciting to have an increased demand and then have so many new tools, products, and opportunities in order to deliver and experiment with that demand. 

My biggest about the future is responsible use of algorithms, and how today there are no audits or regulations in place to make sure these algorithms are used responsibly.  Oftentimes at companies, somebody creates an algorithm, they think they're being responsible, they're using data, they're driving the outcome expected, and then often others don't get in the weeds as much; it sounds right, the principles are fine, but there can be something in there that is driving and threading bias and issues across the company.  These algorithms can have outsized effects, and if they aren't audited properly, yeah, that's concerning. 

So, I think there's lots of talk about AI and what it means, but I think even at a fundamental level, before we get to AI, just these algorithms we're using, poke holes in them, audit them and understand the pros and cons.

David Green: Some wise and important words there from Jessica on the need to ensure that the algorithms we use in people analytics and the AI that is coming are tested, audited, fair and explainable.  So to conclude, the 10th anniversary edition of the Wharton People Analytics Conference confirmed that people analytics has come a long way in the last decade.  It has moved, in many senses, from the periphery of HR and how we manage people in the organisation to the core.  We've seen tremendous growth in the size of people analytics teams, the scope of their responsibilities and the extent of the impact they are having.  People analytics is more important and its influence continues to grow. 

The programme at the conference and the practitioners we spoke to, and that you've heard in this episode, also highlight that people analytics has considerable room to grow in the future.  Generative AI and large language models will undoubtedly be a part of that, and speed efforts to personalise, productise, and scale people analytics so that employees, people managers, leaders, and the entire enterprise benefit from people data.  As HR and people analytics professionals, we have the opportunity to use people data to create happier, healthier, more inclusive workplaces, while in parallel driving business productivity and growth. 

Thank you so much for listening to this special episode of the Digital HR Leaders podcast.  I do hope you enjoyed it.  My thanks to Laura Zarrow, Matthew Bidwell, and the whole Wharton People Analytics Conference team, as well as Prasad Setty, Dawn Klinghoffer, Tano Dixit, Matthew Cohen, Sandy Zou, Ayanna Matlock, Jessica Smith, and Garima Khator for sharing their thoughts on the state and future direction of people analytics. 

If you liked this episode, please don't forget to hit the subscribe button and leave us a five-star rating on your preferred podcast streaming channel so that we can keep producing the show.  And if you want to stay up to date on the latest industry trends and best practices and learn more for about us at Insight222, sign up for our weekly newsletter at myHRfuture.com.  Bye for now and we hope you'll join us next time for another episode of the Digital HR Leaders podcast.  Take care and stay healthy.