According to research by the Corporate Research Forum, 69% of organisations with 10,000 employees or more now have a People Analytics team. The reality is perhaps not so rosy, as in my experience, many of these teams are still essentially restricted to reporting, and not really doing analytics. At least it shows the ambition is there.

One organisation that is definitely doing people analytics is Nestlé. Since the arrival in June 2016 of Jordan Pettman, our guest on the show this week, as Global Head of People Data Analytics and Planning, the progress has been remarkable.

You can listen below or by visiting the podcast website here.

In this episode, Jordan and I discuss:

• Key milestones in Nestlé's People Analytics journey

• How he grew capability in the team, both centrally and regionally, in line with Nestlé's decentralised business model

• Some examples of projects undertaken including one that helps address the gender pay gap

• What excites and concerns Jordan about the continual growth of people analytics

• Like with all our guests on the show, we also look into the crystal ball and ponder what the role of HR will be in 2025

This episode is a must-listen for anyone in a People Analytics role, as well as HR and business professionals interested in how people data can drive business outcomes and support initiatives in areas like diversity and inclusion.

Support for this podcast is brought to you by ClickIQ - find out more at www.clickiq.co.uk.

Interview Transcript

David Green: Today I'm delighted to welcome Jordan Pettman to the Digital HR Leaders podcast and video series. Jordan is the Global Head of People Analytics at Nestlé. Jordan, welcome to the show.

Jordan Pettman: Thank you, David.

David Green: It's great to have you here. Can you give listeners a quick introduction to your background and your role at Nestlé and also, your vision for People Analytics, as well?

Jordan Pettman: Certainly. Hello, listeners. I'm Jordan Pettman. As David says, I lead People Analytics at Nestlé. I guess that means that my team has responsibility for managing everything from data standards through standard reporting, all of the fun stuff we do in analytics, whether it's diagnostic and descriptive, through to some of the more predictive stuff, and then into strategic workforce planning. Then we get to play in some of the more interesting parts of the world, like machine learning, and AI's, and robots, which is cool.

I guess my background that got me there is kind of 15 years-ish, before that, consulting in the same space. I worked at IBM, and at SAP, Success Factors, little company called Inform, and all kind of specialising in, more the business end of that analytics consulting. Don't ask me about building cubes, or writing code, or any of that stuff, because I would lie, but certainly in terms of engaging with the business and helping them to understand and quantify their problems, so they're a bit more solvable is what I do. I guess that then is kind of related to what I see as what the role of People Analytics is.

I think it is the partnering with business leaders to help them better articulate their problems so that they can be quantified so that you can pull more insight into the decision-making process around how you could solve for them.

David Green:  Well don't worry. We're not going to ask you about code or cubes.

Jordan Pettman:  Excellent.

David Green: We would be also stumbling onto ground that I don't fully understand. You're Global Head of People Analytics. Nestlé has obviously got over 300,000 employees-

Jordan Pettman: We do.

David Green: What's actually involved in being a Global Head of People Analytics?

Jordan Pettman: I think for my role in particular, there's quite a lot of consultancy, definitely, in terms of aligning all of our different businesses and different geographies, and our very different agendas in the people space around being able to do things in a consolidated way. It's a real integration role, as well.

We are big, and a function of being big means that we are everywhere. There are a lot of different businesses that our geographies manage. What that means is that there's very rarely a global initiative that everyone is getting around and doing in the same way analytically, at any given point in time. What it does mean is that when problems are happening in our businesses, it's unlikely that it's a truly unique problem, and so a big role that I play, and that my team in our center plays, is really being well connected to each of our regional People Analytics teams to make sure that we're never reinventing the wheel, that when we've developed a solution for our business in Latin America, that we can pick up that solution and redeploy it in Asia, or redeploy it in Europe, and really push a move in our maturity in the way that we use analytics solutions by continually reusing and revamping and improving the things that we've done across time, which is exciting.

Then I guess there's the less exciting stuff as well, right? Like having arguments around what is FTE and what is head count and who do we count in and who do we count out, and making sure that everyone does do that consistently. I think operating in that corporate space, as distinct from the global space, it is a real drive and a real need to make sure that when we talk about numbers at a corporate level, that we are consistently and very deliberately speaking about numbers in the same way everywhere.

David Green: Nestlé is quite... I mean, certainly in comparison to IBM, Nestlé is quite a decentralised organisation.

Jordan Pettman: We sure are.

David Green: So what extra challenges does that bring to your role, operating from the corporate centre?

Jordan Pettman: I think that challenge really highlighted itself for me maybe a year into working at Nestlé. I joined knowing that Nestlé was this global brand and I was joining a corporate centre, and this was going to be great because I was going to get in and make decisions, and push an agenda forward. We spent kind of a year developing solutions and showcasing how you could connect engagement data to business data and connect that to how we might develop leaders differently and whilst our senior leadership in the centre were really engaged with it, and interested, and convinced that these were great things that we could do, it wasn't at the coal face of the business.

Those things that we were developing weren't actually changing the way that business leaders who were driving our businesses were making those decisions differently. It was at about the year in that we'd started moving my team out into regions where we were having that direct relationship at the coal face, so to speak, where we fundamentally shifted the approach that we were taking. Rather than being, kind of more of a traditional hub and spoke, where we build in the center and we deploy in the regions, we really took on that co-creation, very collaborative approach to developing things for our businesses in the regions, and making sure that everyone had access to them.

I think that's actually probably the turning point that helped us to accelerate a little bit faster because the things that we were focusing on in our teams in the regions were directly helping businesses to answer questions. They just happened to be able to be picked up and reused for other business leaders to answer those questions. Then thinking about the way that rolls up, instead of then saying, "Here is an interesting piece of analytics that's been done, and here are all those linkages and things that you could do," the discussions we now have are, "Here are all of these interesting pieces of analytics and the linkages that we've done, and things that businesses have done as a result." It really drives a different dialogue at the centre.

David Green: Great. So you've been in the role for three years. Obviously that was a key milestone, after the first year, that kind of realisation and maybe shift in direction. What have been some of the other key milestones along the journey?

Jordan Pettman: I think our first one, and it happened relatively early in my tenure, was creating and rolling out our global set of HR dashboards and reports. We just hadn't done it previously. There were certainly pockets of Nestlé that had used the technology available to us, whether it was Microsoft or SAP or whatever, to create very localised things. But that had created a bit of a monster because it meant that in country A, headcount was counted one way, and in country B, it was counted differently. In terms of rolling things up at the corporate centre, what that meant was that, to do any kind of quarterly reporting, it would take one of my team as least three weeks a quarter to go around to everyone and find out what their numbers were and push them together and try to get some kind of sense around what we were reporting.

We finally stopped doing that recently, but it had been about an 18 month process from starting to push out, you know, these are the rules around measurement. These are the numbers that we look at, at the centre. If your numbers are different, the onus of explanation really fell to the market to be able to explain why they were choosing to differ from corporate numbers. We've kind of got to the point now where they're not, which is awesome. Actually, at the end of Q1 this year, so it's about an 18 month difference from rolling out these global dashboards to the end of Q1 this year, but we finally agreed with our HR leadership team, that we will no longer spend three weeks a quarter manually smushing numbers together to create a PowerPoint presentation of KPI's.

We now have our leadership dashboards. They access their leadership dashboards, and the support that my team now gives to them is not about creating PowerPoint presentations. It's about going and spending an hour with each member of our leadership team and saying, "Here's what's happening if we navigate through these dashboards for your population. Let's talk about what the priorities are that we should talk about collectively because everyone is facing the same spike in attrition, or a change in recruiting, or we look like we're a distance from this target." So it's a huge milestone in my mind because it means that the people that are in my team that... What excites them is not producing PowerPoint presentations. What excites them is supporting the business to drive change and make better decisions. We're now doing that.

I think the other big milestone that we've got is around having enabled all of our markets to start approaching things like gender pay equity in a standard and statistically sound way, in approaching attrition risk in a statistically sound way, and standard way, as well. So kind of using all of that stuff together, in moving our agenda, both around data and standard reporting, and then doing things that are business impacting all at the same time.

I think the milestones that we're now going to start seeing is markets being less reactive to what my team can propose to them as a solution and start to think about what their new problems are because we have kind of moved ourselves through standardising our rules, standardising our dashboards, getting leadership buy-in that we don't want PowerPoints any more-

David Green: Yeah.

Jordan Pettman: To we've got the information, now we can self-serve. Now let's start identifying these new solutions that we could be working on together.

David Green: So what you can actually do with the analytics, rather than what it looks like?

Jordan Pettman:  Exactly. Exactly.

David Green:  Three years, it's proving quite a journey-

Jordan Pettman:  Mm-hmm -

David Green: Probably flown by in many respects, as well. So what does the team look like today in comparison to three years ago. You kindly invited me in to meet the team-

Jordan Pettman: Yeah.

David Green:  Back in London, I think, in January, and I was struck by very large team-

Jordan Pettman:  Mm-hmm.

David Green: But also, they come from many different countries. But also, a very cohesive unit, as well.

Jordan Pettman: Yeah. When I joined, I had a team that basically did reporting at the centre. We were building a strategic workforce planning capability, and that was kind of it from a global point of view. We had a team here in the UK that had existed for some time, couple of teams in the US that had also existed for some time, but really focused on sort of single country, single market, and really being very reactive to those very specific business needs. We had lots of US and UK-centric business intelligence happening, lots of very US and UK-centric research and survey and that sort of stuff.

At that point, the skillset was kind of more heavily in the BI space, so how could we pull data together and push it out in a way that was meaningful to HR business partners, had some IO psychology, predominantly in our US businesses, really focused on some of the research-y type stuff that we do. Then yeah, one person that was doing strategic planning.

Today, we've got about 36 in the network that report in to me, approaching about 50 in a broader network of people who only do People Analytics work that might report to a market-based HR Director, rather than in the People Analytics structure. The skillset is actually pretty wide now. We have people whose real focus is on supporting businesses to adhere to data rules, and so understanding what our standards are, understanding how we create not those kind of, technical documents that we're all familiar with in a data standard sense, and more the guidelines around how we can teach from a data specialism, HR business partners, or talent people that when you're transacting in these self-service platforms that we've got, it's really important that you use this value when you mean this thing-

David Green:  Yeah.

Jordan Pettman: Or you use that value when you mean that thing, and you never mix those up because the downstream impacts are these things.

It's kind of a very consultative role, but really about enhancing HR's knowledge and capability in using data quite operationally. We still have quite a focus on the BI piece. There's a lot of work that they're doing in the moment, in terms of trying to streamline what our centre pushes down in terms of what the really important things are to measure, but also how we enable our local businesses to do their reporting in that same framework. Obviously recognising that as an analytics team, we do not want to be involved in doing regulatory reporting to governments, to claim funding for learning, but we need to make sure that we're not creating cottage industry in markets where they create a whole reporting platform that is contrary to what we're doing. There's a lot of support we do there.

We've hired for quite a lot of... I guess it's kind of a consulting skillset, so really working with HR Directors and their man-com's in our businesses to help them to better articulate the challenges that they've got in business problems driven out of people, to then help what our next skillset, which is then in the real doing of analytics. We have some data scientists, we have some IO psychologists, some statisticians, who are then kind of the engine behind how do we decide what model we want to use to tackle answering that problem, how do we push that into a tool that enables compensation people, or HR business partners to approach these problems themselves, then obviously our HR strategy stuff around the strategic people planning.

So it is a really interesting blend of skills. I think we have really set ourselves up as a generalist team.

David Green:  Yeah.

Jordan Pettman: There isn't a specific stream for workforce planning alone. That is really deliberate because I know we do have quite a few people, but inside of our HR population, we're pretty small. Inside our line manager population, we're even smaller. In order to serve the needs of the populations that we need to serve, all of the team are broadly generalists, but they have a strength in one area or the other. Then the way that we've structured ourselves, we're really trying to operate as a globally networked team, rather than individual teams. Where we have a shallow depth of experience in one region in data science, we'll be experience-rich in another part of the world, and so we can kind of support each other globally to do those things.

David Green: I was really struck when I came to meet the team, how cohesive it was. That's not always the case when you see global People Analytics teams come together.

Jordan Pettman: No, and I mean, I think that's partially due to design because we needed to operate that way and we built this generalist, if you will, team. I think something else that drives that a little bit, I think, is potentially the cultures and languages that we all work in. Nestlé's business language is English, which is great for the Australian based in Switzerland whose French is abysmal. We do all work in English, which is super, but many of the populations that we serve are not. If we have one of our experts dialling in from the UK to support a project in Ecuador, it's absolutely likely that the people that we're working with on the other end don't speak English as well as the analytics team will. The need to operate really pretty seamlessly as a team, regardless of where we happen to be, has just been so important for serving the clients that we serve.

There's been quite a lot of work that some of the teams have done in terms of measuring cultural preferences for the way that people work, as well, and really trying to line up their client relationship between some of our markets and the natural preferences that we have in our team versus the way that we work within our team, which is then far more cohesive, and far more, kind of, fluid at any given time.

It's been a fun experience to build it out. It continues to be a fun experience.

David Green: And of course, you work on a number of global initiatives as a team, as well?

Jordan Pettman:  Indeed.

David Green:  I've seen you and Andre as well, present the really good work that you've done around gender pay analysis.

It'd be great, I think, for the listeners who haven't been to some of those conferences really to just hear a little bit about what you've achieved there.

Jordan Pettman: Sure. I think this project is probably one of the more exciting things that we've worked on, purely because it's not analytics for analytics' sake, and it's not analytics for creating a justification for something or a dashboard. It's responding to a really key business initiative that our CEO made statements at the United Nations and the International Labor Organization saying that at Nestlé, we're taking diversity and inclusion really seriously. It's something that we really want to focus on is understanding and improving the way that we remunerate our employees, men and women, which I think, is a huge statement for Nestlé to make.

We're a big production company, right? We create food and then beverages and that means that we have lots of factories and distribution centers, and traditionally, that's a male-oriented workforce. I think it's a really exciting thing that we've been able to support analytically, is making those statements externally that we will understand the way we remunerate people and seek to improve that, means that everywhere in the world has to be able to measure pay gap and measure pay equity.

Yeah, it fell to us to enable the business to do this. We built a pretty slick tool. One of our IO psychologists built pretty simple step-wise regression in R, is the statistical package we use, and then built a front end in Shiny that is basically built to enable someone that isn't an analytics bod to measure something statistically and present it back to their leadership team in a way that helps the leadership team make decisions. It's kind of very step-by-step, you know, look for these elements of data in your local HR system, download them, put them into this Excel structure, make sure that there are no gaps, make sure that there are no blanks, make sure that the date format is this, load it up, and then it steps through the regression model. Then at the end, it shows you how strong your relationship is, whether the gap is systemic or not, whether the gap is just in particular pockets, and then kind of guides you through what the interpretation of all of the charts that the tool spits out are, as well.

So when an HR business partner or a reward manager who isn't necessarily statistically trained is having these discussions with the head of HR and with their man-com, they can really confidently be saying here is the way that our pay looks in terms of men and women, and that gap or that lack of gap is either across the board or it's not. That means the strategies that we need to be thinking about to correct these things is either systemic or point. Then when we cost these things out, we can then start to talk about the impact of executing strategy X to level out our pay equity lines.

I think it's a really powerful demonstration of the fact that approaching these problems in an analytical way enables non-analytics people to really have genuine impact, both on the business, given that this is a real business initiative, but on people. I think particularly in the People Analytics world where many of us employ psychologists, having a real impact on people's lives is absolutely something that is intrinsic to what we want to do, not just within HR but because a lot of us are psychologists. I think it's been a really great project, both for Nestlé, but my team as well. Lots of hard work-

David Green: I bet.

Jordan Pettman: And lots of heavy lifting, and lots of horrible data cleansing, and all of that sort of stuff, but fundamentally, the sort of project that we want to be involved in.

David Green: I guess the great thing about it, because it's obviously quite high profile, it's a topic that's come right from the top within the organisation, it raises the profile of People Analytics, as well.

Jordan Pettman: Exactly. Exactly. I think it calls into relief that People Analytics isn't this mystery-shrouded in mystique. It's an approach to problem solving that we worked directly in partnership with our diversity and inclusion group, and with our reward group, and that together, we've made something that could have been a problem for one or the other of those groups to tackle much, much simpler, and much, much more straightforward because you're applying that science and rigour that an analytics group brings to a topic that... I mean, it's no particularly esoteric, but a topic that could have been very, very difficult for one or the other of those groups to solve.

I think in terms of raising the profile of People Analytics, it's not that People Analytics is delivered the... We're not the knight in shining armour saving women's salaries everywhere. It's that we're intrinsically a partner to other parts of HR and other parts of the business because we can help them do things better, faster, smarter.

David Green: Perfect. Well, as I said, it's very impressive always goes down well at conferences when I've seen you and Andre deliver the story. Any other projects that you've worked on over the last few years where you can share some of the experiences and some of the outcomes as well, with us?

Jordan Pettman: I think one of my favourites to talk about is the work that we've done across a bunch of different approaches to flight risk. We've talked to... A couple of my team have talked at conferences about this as well. I think the approach that we're now taking to talking about this with the business has really evolved across time. I think that's probably why it's my favourite.

We started out by looking at things like logistic regression to predict the list of people who are going to leave. That was interesting. It was... The different parts of the business we did that in, it was sometimes very accurate and sometimes not so accurate. We looked at some supervised machine learning and it then decided that clustering was the way that we were going to predict attrition. Again, that kind of gave us a list that sometimes was pretty accurate, and sometimes was less accurate. We then moved into doing survival analysis, which we thought was super cool. The analytics team were like, "Yes! This is super statistics! It's driven out of pharmaceutical! How smart are we? Not only do we get the list, we get the drivers of it, we get the timeframe. Gods of saving people, we are, in People Analytics!"

It was pretty accurate, but my Lord was it heavy. Across the way, we'd quantified the impact of using these models and sometimes adding some of the survival analysis stuff, we were really able to say by saving these particular people at this particular time, the impact on cost per hire and the impact of the cost of turnover was really exciting. Our HR population were then able to go and say by doing these things analytically, we've saved money, and we've been able to spend that money in better ways than hiring these people.

 But at the same time, what it's kind of highlighted to us is that what we were doing as the result of these things was taking the output of these models, and then going, "Well, who of these people leaving, do we wish wouldn't, and if we could identify who we wished wouldn't, what would we do to keep them?" We'd go and talk to them. We'd understand what might cause them to leave if they were someone that we wished would stay and then do something about that.

You know what? If you know who you wish would stay, you don't need a statistical model to tell you who we think is going to leave. Our whole approach to measuring flight risk, and our whole approach to working with businesses to better manage their flight risk still uses the statistics if we need to, but what we're far more likely to do is start to look at historical attrition, look at the pockets of places where attrition is happening, and then help people to work through how would you identify which of that population you wanted to stay, and then here's a framework and here's a toolkit for you to go and talk to those people. Encourage them to stay. Then you don't need to invest so heavily in these statistical models, unless we decide that actually, there's a return on investment in you doing these things.

As an analytics leader, I guess I should be trying to sell the statistically difficult stuff, but I think it's been a really interesting twist in events for us that actually, the real business benefit oftentimes is in keeping it simple, as we so often hear, which is cool.

David Green: Yeah, I think you don't necessarily need sophisticated analytics. It's about the business question you're trying to solve, really, isn't it-

Jordan Pettman: Exactly.

David Green: And the impact it has. That's an interesting story about how that's kind of evolved. What's kind of next? What's the direction of the team for maybe the next 12 to 18 months? Any specific projects that you're looking on? I know you've got workforce planning, for example-

Jordan Pettman: Yeah, so workforce planning is kind of a constant. It's one of the things that, I guess, is the thing that ties us to the rest of the HR function in terms of what we continually deliver on an annual basis, is support to our businesses to do their strategic planning. So that kind of continues to evolve. Again, we started with a pretty heavy approach to quantitatively forecasting the number of heads and bodies and what skills they needed and have moved in recent times, to a bit more of an a la carte menu approach where depending on where the business is, sometimes we'll do that heavy quantitative forecasting, particularly in heavy production environments. But where we're seeing far more of a focus on helping business leaders to think a little bit more agilely, and if they're planning every year, then we probably don't need to update a quantitative forecast for a five year period every year. But, we might want to look at the things that we could do in the light of retirement risk if you've got an aging population, or in light of having a weaker or stronger succession plan throughout key roles.

Some of that strategic planning is really about pulling in different analyses from a bit of a menu and saying well, what is it in HR that you're going to do to support the business differently this year? How can we bring analytics to bear in your decision-making around that, which I think will continue to evolve.

Then the other big thing that we're working on at the moment is shifting from our traditional way of doing engagement survey to being a little bit more continually collecting and supporting the business to react to insight. In January, we started to launch what we're calling our Nestlé and I Insights Strategy. It sounds very grand, but it's effectively a way of enabling people in our markets who aren't necessarily full-time analytics people, but are those point people in our HR teams, that partner with our HR Directors, that partner with our man-com's, to help them to think about what is it that we want to engage with people about this year because we want to talk to them about a strategy, and we want to talk to them about how they're feeling about senior leaders, or how engaged they are, or how change-ready they are in one of our transformations, and how do we ask those questions? How do we frame them in a way that business leaders can make decisions with it? How do we really rapidly go back to the people that have taken the time out to give us those insights and tell them that we understood them, that we've used them, that this is the impact that they're having on their decision-making?

It's a big evolutionary change that Nestlé is making in that space. So we've been on the journey for about a year, and I think in the next 18, 24 months, you'll see a real shift in the way that we're doing that from a top down, really moving to being a little bit more agile, a little bit more content and decision-making focused, and hearing a little bit more about the way that our businesses are maturing in that space, which I'm really excited about. It's not something that many of my previous roles had a lot of hands-on work in, so it's personally really rewarding because I'm getting to shape something new that's genuinely new for me, as well. It's cool.

David Green: Any plans to incorporate sort of machine learning, or network analysis into some of the work that you're doing?

Jordan Pettman: Certainly in some of our more experimental projects we're doing a bit of that. We've done some ONA in the US and in Australia. There's a rumour that we might be doing something in Europe, as well. We'll see. But I think we're really trying to be as focused as possible on driving business results with those sorts of analyses, rather than doing something cool.

David Green: Just for the sake of it, yeah. Yeah, makes sense.

Jordan Pettman: As cool as that is, in order to move away from doing things in an active, resource heavy way, to do something at scale across something as big as Nestlé, we really need to be able to say this was the problem, this was the investment, and if we started to invest more cleverly in some of the more passive ways of doing ONA, these are the sort of business results that we could be delivering as a result. There is definitely some stuff happening there.

We are actually working currently on a robot. I guess it's an AI, but it's in our reporting space at the moment. We've spent quite a lot of team in the People Analytics team so far, teaching that robot all of our weird and wonderful acronyms and all of our reporting measurement standards and what we're seeking to do in the next little while is to start getting that out into our businesses where we can further have it educated about local stuff-

David Green: Yeah.

Jordan Pettman: And then launch it in a way that removes that email from an HR Director to their HR services person asking for how many women there are in leadership and moving that to be the same effort from the HR Director, but asking a robot that question. The robot go... Knowing all of the acronyms, knowing the local content, knowing all of the things about that person asking the question because we know their job, we know where they're located, we know the country they're in, interrogating our business warehouse directly, and responding with that number. Instead of the response time on that sort of thing being completely reliant on how much time the HR services person has to go and run the report, and if they see the email in time to get it to the HR Director for their meeting, and that stuff becomes real time operationally, with a robot, which is pretty exciting, as well.

Not launched yet, but on the cusp, which is... it's cool. It's the sort of stuff that my team do get really excited about. I think particularly in that AI robot space-

David Green: Yep.

Jordan Pettman: I think there's so much scope to teach an AI about some of our process stuff. Imagine the sort of scale we could get on a robot that knew our performance management process, and instead of it being HR people asking it a question, it was a Line Manager asking for just some quick tips on what I should be doing at this time of year in my check-ins. The time that we stand to save HR business partners in that kind of hand-holding, operational work, and give back to them in supporting better strategy decisions being made, I think is huge. But small steps. We need to prove that we're actually solving for some of that time wastage before we roll it too far.

David Green: So obviously you're doing some great stuff at Nestlé, and lots of exciting things ahead as well. If we bring it back to the sort of People Analytics as a field, what excites you most about what's going on at the moment, or could happen in the future?

Jordan Pettman: I mean, I think for me, the things that I'm seeing that are exciting in this field is definitely in the space of business impact. I think if you look at any of the presentations that you start seeing in conferences today, the analytics content is so high and it's not being delivered by the likes of you and I. It's not analytics people talking about how we used this fancy dashboard to support business leaders making better decisions. It's not us talking about how we used a predictive model to predict attrition. It's about business leaders saying because we were able to do this stuff. The analytics stuff is almost by the by. It's becoming about the way that HR is quantifying its impact to changing business results.

I think that's the really exciting stuff. I think the challenge for People Analytics people is to see that that is the light at the end of the tunnel, when the tunnel that you're wading through, which might involve talking to people about the difference between FTE and headcount again, or wading through a data cleanse before you can pull it into the model that's going to support this stuff, that the light at the end of the tunnel is genuinely that HR is really starting to get it-

David Green: Yeah.

Jordan Pettman: So to speak.

I don't know that that's so true in the last sort of five, ten years. I really feel like there were battles to be fought to have people understand the value that People Analytics brought across that period. I really feel like that's changing.

David Green: Yeah, I think you're right. Like me, you've been going to conferences for a long time, and it seemed up until even 18 months ago, where everyone was talking about what People Analytics is and why people should do it, and that's really moved to the how and then the what, the what it delivers, as you said, the business outcomes it delivers, or the employee outcomes it delivers, and I think that's a good sign for the field's health moving forward.

So that's what excites you. What scares you or what is your biggest worry about the space?

Jordan Pettman: What's scary? What's scary and what continues to worry me is that the problems that were always there are still there, right? We still haven't really tackled that HR data quality, broadly, is really challenging. It's not necessarily something that's endemic in People Analytics. It's in HR. It's still something that we're having the same conversations about like how we educate the broader HR population to really get it? How do we help them to understand the impact and influence they have on your ability to do anything cool at the point of data entry?

As a result, it means that whilst technology is evolving, and whilst the application of analytics in business is becoming more and more exciting, there is still this danger that those of us who work in analytics roles, will continue to be sucked in why is Susie not in that number, and why is John in that number? That real deep data, horrible reporting black hole that we do still spend quite a lot of time in. I think for us to really accelerate on the cool stuff, and for us to really keep pace with the rest of business in using artificial intelligence in the right way, we really need to manage that rest of HR doing their bit in the People Analytics space to enable that to happen. It does continue to, maybe not keep me up at night, but it certainly keep me in a healthy supply of red wine.

David Green: Yeah, I think it's a challenge. I mean, hopefully, the more people see the business outcomes as to what analytics can deliver, the more that encourages everyone to actually, as you said, put the data in the right place and actually be HR business partners in the wider HR population, to actually be excited about people analytics because it supports them in their day-to-day work.

Jordan Pettman: Yeah.

David Green: It will be interesting as it unwinds.

Jordan Pettman: I think we're all working on it. You talk to any of my peers, it's something that we all talk about it. It's not that we're not addressing that worry. It's a long-term worry.

David Green: The space is evolving quickly.

Jordan Pettman: Mm-hmm.

David Green: How do you learn, yourself?

Jordan Pettman: I think I'm... I mean, I'm pretty fortunate in that I have a relatively good network of People Analytics people and so, any time I do have challenges, or that I don't know an answer, I can reach out pretty quickly to a bunch of very educated professional people in the space, and really leverage my peer network in the space. I would say that I do that a lot.

There's a bit of reading that I do. I think the same as many of us, David, I read your blogs religiously, of course.

David Green: I'm not paying you to say that, but I will write a cheque.

Jordan Pettman: There's so much out there that can be read at the moment, that I think that's really the way that I encourage my team to stay current, as well. I think I would confess to not having as much time to stay current as I would like to, and so shamelessly, we've actually set up what we're calling our Global People Analytics Connect, which is at minimum, once every second month. Depending on whether there's cool stuff going on more regularly, we're having our people across the team, whether that's a leader, or whether it's one of our very junior people that have just learned a new thing about managing data, or this cool new thing in Power BI that we can do, we're really encouraging the people in our teams to share what they're learning with all of us to learn.

I think at Nestlé, we're not going to teach people how to be statisticians or IO psychologists. We teach people about the process that takes a coffee bean from a tree to a cup. We teach people about how to make baby formula or what have you. The learning that I can do and the learning that my team can do is unlikely to be part of the Nestlé development stuff, so it is really about engaging with networks, picking a conference that actually has the content in it that you're interested in. There are a bunch today that really do deliver really slick, interesting, real-life presentations from real businesses who are really doing it.

I think I can... I'm one of those people that was a consultant for long enough that with love in my heart, I can say that consultants will tell you all kinds of things because it was our job to sell what our capabilities were to you. Pick a conference that consultants are at because they do do lots of research. They do bring the cool stuff. Pick a conference where some of your peers are presenting what they work on because if it's happened in a business, then you can make it happen, too.

David Green: Yeah. I would agree with that. So we'll now move to the last question, which is the question we ask every guest on the show. It's where do you see the role of HR in 2025?

Jordan Pettman: We've been talking about this recently, actually. I suspect that I have a controversial view in Nestlé. I don't know how controversial elsewhere, but I kind of think, particularly my role in People Analytics within HR, I kind of see us evolving towards being... it's almost that Jiminy Cricket conscience character for businesses. If you think about the speed with which we are evolving our technologies, our ability to use data from all over the place, whether it's social or personal or what have you, I don't think that HR is not going to start using AI's.

I don't think that we're not going to apply machine learning to loads of our processes that enable us to be faster, leaner, smarter, better. I think our role really needs to start moving into that space where we're applying the human element to all of the cool tools that we're able to use to make these things move faster. I think that the GDPR launching mid-last year, I think really called into relief our role in that space where a lot of the examples given are in financial, and it's about not making decisions algorithmically, because that could impact someone financially.

If you think about that in the context or an organisation, HR technologies and HR systems that design an employee experience are going to start doing that algorithmically. I think that HR really needs to embrace their role of being that conscience inside of all of that technology where we need to make sure that the technologies are providing these digital experiences to people that are kind of, across the board, not exclusionary, that we know AI's and machine learning algorithms have a penchant for doing. There's enough of them in media about the chatbot on Twitter that became racist in under 36 hours. We have a real responsibility to make sure that HR tech and HR practices don't do that.

David Green: Yeah, I'd agree. I think that the ethics part, the responsibility part is going to increasingly fall to People Analytics leaders. Well, we'll have you back in five years and find out.

Jordan Pettman: Yeah, let's see.

David Green: Thank you very much for being on the show, Jordan-

Jordan Pettman: Pleasure, pleasure.

David Green: It's been a pleasure, as ever. How can people stay in touch with you?

Jordan Pettman: All the usual ways, I guess. So LinkedIn, I think I'm just /JordanPettman. Twitter is ridiculously, all lower case, @j_lp because Twitter existed before I was someone that people would be interested in following, so @j_lp. That's kind of it. Follow me. There's lots of photos of Swiss sunsets and wines and then obviously, interesting People Analytics things.

David Green: Well, we're never going to complain about wine. Jordan, thank you very much for being on the show.

Jordan Pettman: Thank you.