Data-driven HR: What Forward-Looking Companies Are Doing
Welcome to another exciting episode of All About HR! This is the series for HR Professionals and business leaders who want to future-proof their organization and learn about the latest trends & insights from industry experts, CHROs, and thought leaders.
How can you use people analytics to drive business success? In this episode of All About HR season 2, we talk with Victor Akosile — Podcast Host & Analytics Consultant at Humananalytics Hub — about data-driven HR and building a People Analytics function.
Victor is a People Analytics consultant and the host of Humanalytics, a podcast where he discusses how HR tech is solving problems and making the world a better place.
In this episode, we’ll discuss:
- The most exciting HR tech developments happening right now
- How companies are using data-driven HR to succeed
- Essential skills for People Analytics teams
Watch the full episode to discover how you can help build a data-driven culture and contribute to your organization’s success.
Related (free) resource ahead! Continue reading below ↓
51 HR Metrics cheat sheet
Data-driven HR starts by implementing relevant HR metrics. Download the FREE cheat sheet with 51 HR Metrics
Victor Akosile: You know, this can work where if you really look at your people data and if you really drive people strategy, that can really drive your business strategy. So HR was in that shift there, you know. It’s an interesting shift to make because people have to believe that this is the new HR – the same way that people had to believe that marketing is not a bunch of artists creating stuff. There are like analysts to measure so many things now, it takes some time for that shift to happen.
Neelie Verlinden: Hi, everyone, and welcome to a brand new episode of All About HR. My name is Neelie. I’m your host. And on today’s episode, I’m speaking with Vic Akosile. Vic is a People Analytics Consultant. He also hosts his own podcast that’s called Humour Analytics. And I suggest you check it out if you don’t know it yet. And he also is a very well-known member of our very own AIHR community. We are going to talk about people analytics, which, interestingly enough, we haven’t done so yet on the show. So I’m super excited to get started with that. But first of all, let me welcome Vic.
Neelie Verlinden: Hey, Vic, welcome on the show.
Victor Akosile: Hey, there. Thanks so much for having me.
Neelie Verlinden: Yeah, I mean, I’m very happy to have you. How are you doing?
Victor Akosile: Well, doing good. You know, I’m very busy these days, as you may expect folks inside of my space to be but you know, very exciting times, though, to be in the sphere.
Neelie Verlinden: Yeah, yeah, no, definitely. And I mean, that’s also one of the reasons why we are going to have this conversation today, aren’t we? Before we dive in Victor, is there anything that you’d perhaps like to say to our audience about yourself?
Victor Akosile: Hey, there, everyone out there who’s listening. I’m Victor Akosile. I am based here in the Washington DC area in the United States. I’ve been involved with HR tech, People Analytics, and HR strategy for close to about 15 years now in different kinds of capacities – from small organizations to large ones on the corporate side to consulting on people analytics teams and technology strategy. So I see that a lot. And it’s been a really rewarding time and a rewarding career. So happy to share anything that may be of value to folks here today.
Neelie Verlinden: Absolutely. I’m also very happy that you are willing to share about that, Vic, because as I said, this is pretty funny actually. We haven’t done an episode yet about people analytics. And this is a really big part of the field of HR, of course. But before we start talking about that, just one other thing that I really want to ask you, because you do also talk a lot about developments in the HR tech field. So what development in HR tech are you currently most excited about?
Victor Akosile: Um, great question. You know, on the show, we do talk to a lot of HR tech startup founders. And I think that’s something that I find really exciting. So I think I’ll touch on two things. One, is that there is just so much energy, investment, and excitement, into HR technologies, you know. I think, coming out of the pandemic, you know, a lot of venture capital saw that this is an area in business that hasn’t had the same kind of digital transformation that let’s say finance or marketing has had, right. There are a few big players, but there are a lot of big shakers. And I think that that’s what’s exciting to me, that there was a lot of energy and a lot of investment inside of HR tech startups, even up to this day, around shakers and movers who are open and ready to disrupt the norms of the big players. And I think that’s because they can innovate a lot quicker and faster than let’s say your standard, you know, let’s call it HRIS system, or something like that. So I think that’s one. Another one that comes to mind is really how much AI is driving a lot of the innovation. And I know for some people that may seem a little bit like, Whoa, are the robots telling us what to do or who to hire, but I think it’s more aligned with a lot of AI is assisting people to help them make consistent and better decisions. That’s how I like to put it. It’s not that HR is perfect, but overall, you can consistently make a better decision than maybe doing it on your own because you have access to that data that’s there. So I think those are, you know, two things around the HR tech space that really get me energized to see so I love it there. So I’ll offer those two.
Neelie Verlinden: Thanks for that, Vic. And yeah, again to the audience you know, check out his podcast because you do speak to a lot of founders and CEOs of HR tech startups. So, yeah. If you want to hear more about that, do you have a listen. But yeah, so today, it’s gonna be about analytics, people analytics. And since this is the first time that we are going to be doing an episode on All About HR about this topic, I think, first of all, here, Victor is let’s talk about data-driven HR. And to you, you know, as an expert in this field, what does data-driven HR mean to you?
Victor Akosile: First of all, what took you so long to have a show on people analytics? I’m excited to, you know, be on it. Right, taking me back to my days and the AIHR Academy, which I will put a plugin for excellent Academy, if you’re not in there, check it out. What are you waiting for? That won’t be my only plug for that. But second of all, what does data-driven HR mean to me? That’s, I think that’s a really good question. Because I think it looks different in different places. You know, I’ve worked with companies, large and small. Not all the big companies are doing your most predictive analytics. And sometimes you see small companies do it. But I think, how I would describe it is finding ways. And I think this is it, it’s the active, intentional way to find ways to incorporate people-centered data into the decisions that you make. Mostly, a lot of times, it’s about your people, but when it’s done well, and when it’s really put at the forefront, that people strategy based upon analytics is really driving your business strategy, you know, like a lot. And I think that is where you really can see data-driven HR really come to the forefront. So I think an example of that is, overall people are having a struggle trying to find people to hire qualified candidates and things like that. Right? Well, let’s say if you are a consulting company, right, and you build out your talent, well, that is a direct impact on your bottom line if you don’t have people, right? So how can you use data on maybe the labor market, graduation rates, right? Talent, migration, internal, like retention. These data now drive the business strategies you have. This is where we’re gonna let this, this is how we’re going to hire, this is how we’re going to look like in the next two or three years. That’s really, really driving that business strategy. So I think that that’s what I like to call it in the most advanced places. But to me, it even comes with something as simple as: Do you have access to your basic HR data to drive reports? And for some, that may seem really basic, but I’ve been in places where that’s really hard. But even having something like that I think encapsulates data-driven HR. So I think that that shows a little bit of the spectrum, about what that means to me.
Neelie Verlinden: It is a spectrum. And there’s basically one side of it. And then, of course, there’s the other side, and then there’s everything in between. And for that, we do not have enough time in one episode to talk about it. I think we could probably launch an entire series to cover all of that. But now, as a consultant, I imagine you see so many different types of companies as well. I’m curious to know, what ways are you seeing forward-looking companies use data-driven HR?
Victor Akosile: A few things come to mind. And I’ll share an example or two. One way that I think people are really using data-driven HR is really a combination of maybe statistics and analytics to help tackle or provide, like drivers or levers for executives around the thorniest and trickiest of issues around DEI. Right, like, that’s a big area. So there is a body of work called organizational network analysis or social analytics, which is essentially trying to understand what are the networks that are formed inside your company, right? Who knows here, right? If you were to draw a LinkedIn map of your organization, and you were to look at it, you know, what does that look like? Right? And for DEI, we know a lot of research surfaces around that. A lot of times the connections that you make, and the people that you are able to connect to have a direct influence on promotional rates. Um, I talk with a lot of executives saying I don’t know what to do to help him you know, improve the DEI challenges and I feel for them. Because let’s say if you’re a tech company and you hire people with computer science degrees, well, in America, at least, the last time I saw it, only 5% of African Americans graduate with a computer science degree. So already, before they even come to you, your talent pool is smaller, right? So you may not be able to impact the labor market, but you may be able to impact what happens when they come to you. And that’s how they are progressing? So that’s something that one organization I know is doing, and they’re looking at whether there is an overlay or a correlation between the networks that are within our organization, and the progression that people are experiencing? And when we take that and overlaid that with DEI data, are we seeing that there are disparate networks in our diversity that may not be interacting with the right groups with the right connections with the right people, that may be influencing promotion rates? Because now as an executive, you have the ability to say, Okay, well, I want to make sure that these people get connected with these other people to help foster promotion. And this is a massive company with over 50,000 people, right? So they have enough people and data to make this happen. But to me, that’s like, super forward-looking, you know, what those kinds of companies like you’re doing. Um, so that’s one and but I think something that I think is really practical, and that a lot of places like are doing is actually looking at their, you know, what I call your HR employee lifecycle data strategy. So when they come in, are you asking the same questions when they come in, during engagement or during performance check-ins as you’re leaving, to help to see, okay, well, where do we lose people in engagement or things like that? So that’s something a lot of organizations can do – just kind of looking at that experience, and implementing checkpoints or surveys to say, Okay, are we checking these key performance indicators at each point of the employee lifecycle to see maybe where we’re losing him, that can be a really good indicator for something that a lot of companies are looking at, which is how do we retain more people? So I think that those are really, as I say, forward-looking companies kind of using HR in a data-driven way.
Neelie Verlinden: It’s very, very interesting that you mentioned that Victor, because, especially around the employee lifecycle and the data collection around that, do you have the impression that that is something that has increased with the great resignation? And a lot of people looking to change jobs or are already resigning?
Victor Akosile: Yeah, I think so. I think I can think about two indicators. One is a macro indicator of the fact that investments in HR technology skyrocket if you look at like the difference between 2019 and 2020. A lot of it is, you know, obviously, those businesses who are in the space of HR data collection, and people analytics are doing well. I mean, these companies are investing in that more. Right. So I think that’s one indicator. And I think to colloquially just, you know, from the conversations I’m having, I think that be pandemic expose a lot of maybe inefficiencies in their in data, or unpreparedness, that the organization have, you know, and just in how they collect their data and what they know about their people. And I think another indicator is that, in America, the Security Exchange Commission, the SEC, put out guidelines that organizations have to report on their people data, right, so they have to put that in their corporate filings. Now, all of a sudden, you see this alignment, which is something that I love, of business outcomes and people outcomes that I think was not there before, or that part of the story was at least missing. And now, Wall Street, and you know, financial investors are now taking a very closer look at how you are treating your people. Are your people staying or are people flourishing? Are they engaged? Are you diverse, within their financial filings? So there is an incentive to try to improve those numbers before they’d like to go out. So naturally, there is some investment because they’d like to spotlight there. So I would say yes like we are seeing some great investments there.
Neelie Verlinden: Oh, wow. That is super interesting. By the way, I didn’t know that. That’s the first thing I hear about it. Is this something that’s relatively recent, the fact that they now also have to basically publish these kinds of data?
Victor Akosile: That has been the official guidelines. They’ve been talking about it for quite some time. But I think last year was when they started to say, All right, we want to see something right.
Neelie Verlinden: Nice. I mean, let’s hope that this is going to have a huge positive impact on the way companies treat their people. Just coming back to data-driven companies and data-driven cultures and organisations, I’d like to touch on the leadership part in that for a bit. In your experience, what role should leadership play in creating a data-driven culture in HR, and in the wider organisation?
Victor Akosile: This is something I’m really passionate about where you know, leadership, and most especially leadership expectations, drives a lot of culture out of business, right? If your CEO wants to see something, everyone can change how they work to satisfy those needs. So for example, if your CEO is constantly asking, do we know how people feel about this? Or what do our people data have to say about this? Well, if you’re a VP of HR, or CHRO, you take that as cues of like, I really need to get in line to be able to provide this insight that my leader is looking for. So that’s what it means at the CEO level. But I mean, even at the VP and CHRO level, right? I’ve seen a lot of executives in those spaces come to learn new roles to help revitalize and bring that data-driven mindset to their roles. So it’s changing the expectation. And I think that’s one thing related to the role that leadership plays because when you change the expectation, you start to change the conversation that people are having. Hey, you know, Jane and the CHRO, you know, want to know, you know, how many people left between this time and this time and why? Well, we don’t know why? Oh, well, looks like we have to figure out why. Right. So now that sparks the expectation that has sparked greater conversations of how can we do this better. And I can’t speak enough about leadership’s role in driving that expectation of we will look at data, we will base our decisions on data, and if it’s not there, well, we have to be able to produce it. So a leader’s role is I think, vital in driving that data-driven culture because they set the norms, they set the expectations, they drive like the conversations, which ultimately comes down to what, what gets done, you know.
Neelie Verlinden: Now when we look at the potential impact of people analytics on not just the HR function, but also the business as a whole. You mentioned it briefly already. But perhaps there’s another example that you can share of a business problem that you’ve been working on with one of the companies that you have been consulting with, and that you have successfully addressed. Is there anything that maybe comes to mind?
Victor Akosile: Yeah, I think that one common one, actually, especially coming out of the pandemic that is very common now. It’s this challenge of pay equity. Okay, pay equity, especially between women and men in the workforce, you know, the pandemic saw a lot of burden on women who left the workforce to take care of families. And, you know, as we’re either circling out of it, crossing fingers right now, a lot of women are re-entering the workforce, and companies are taking a closer look at Hey, are we paying people fairly when it comes to gender in those kinds of roles? So, you know, that what we do is that we take a lot of their people data, compensation data, and we try to normalize it based on the role or based on 10 years, you know, based on all the things that we know that could impact somebody’s compensation, and we have a look, you know, like we said, hey, you know, are this group of people within a certain level of expectation, let’s call it that? These other groups of people, when it comes to compensation, sometimes we see things are going wrong, but I think that when you really break it down to the specific roles and specific 10 years, you can start to see some differences and those differences start to spark questions of why. This person, you know, came in at a much lower rate, even though maybe their male counterparts came in at a much higher rate with not that much difference in the job description. Could have been that this person just negotiated higher? And that was it, right? Well, let’s try to fix that because we know there are some inequities across the board when it comes to those kinds of things and in those negotiation kinds of situations. But those are things that organizations are looking at. An example that I point to, it’s actually pretty common now. And I think more consulting firms are offering almost an easier way to access that kind of service. And they’re a lot of data and platforms now too, that is offering a capability to really explore this issue of pay equity. So that’s when I think it’s pretty common. And I think the only other one that comes to immediate mind is I think the challenge that everyone is trying to understand why are my people leaving? What can I do to help to reduce attrition and increase attention, you know, or increase retention, whichever we’re going to cut it? And that’s a big challenging problem, because there are so many factors that go into it, that you really do have to scope that kind of problem down to say, Okay, well, can we look at a group of people or a cohort of population and say, Well, do we have any clarity that we may be able to extrapolate from that? So those are, I think, examples of common business problems that we’re seeing that people analytics can definitely address. So it’s an exciting time to be in the field.
Neelie Verlinden: With regards to the second thing you mentioned, Victor. That’s also where the whole employee lifecycle analytics comes back into play again, if you’re going to think about why are people leaving? So that’s another one or another reason actually why that is a super interesting part within the field of analytics, I think. Now, let’s change tack a little bit in the sense that I’d like to touch on building the people analytics function. Still curious to hear from you, Vic, what are some of the things that people get wrong when it comes to building and people analytics functions?
Victor Akosile: A few things come to mind. I think I touched upon it earlier, which is that people analytics is a spectrum, right? There is the spectrum of just being able to, you know, automate and generate reports quicker and easier, you know, this element of being able to have your business leaders self-service with dashboards and things like that, right? So there’s that element of people analytics, which some people don’t like to hone in as people analytics, but it looks different as you mature within your function within your organization. So I counted, because a lot of times, it’s the same team of people during the same kind of work. So I think that’s what people tend to get wrong is that they think of people analytics as purely, you know, like the data science element and machine learning models and things like that. I mean, a lot of business problems can be solved by getting well-organized data. I think that people may focus on the analysis a lot, but not focus enough on the data engineering side of it. How do you get data that’s good, that’s clean, that’s accessible? Now is when you really start to do analysis. And I understand, if you’re building a people analytics function, you’re spending all this money on people, technology, and resources. You want to show, hey, this is the insight that this investment has made. So maybe the engineering piece feels like well, you can’t really see that. But it’s something that if you want to really go far. That’s the stuff for a strong foundation that I would say is needed. So I know the sexy machine learning models are cool, and that’s what people like to do. But you know, no one wants to be inside of a meeting where you’re presenting, and maybe you’re showing that headcount number and the business executive says: Well, that can’t be right. No, I know hiring more people. Everything from that standpoint is questionable, you know, so it really is the solid foundation. So it’s more about quality data engineering. I think a lot of times it is about the most advanced machine learning module that you can apply. So I think that’s what sometimes people have a misconception about that. If I could change that I would.
Neelie Verlinden: It sounds pretty obvious, but I can see how it’s something that gets looked over, perhaps because it is so obvious. So yeah, that foundation is the basis from where it should all start. Makes sense, but it’s really good that we actually emphasize the importance of that one, I think. So when we are talking about people analytics teams, Vic, what do you think, are important skills and mindsets needed?
Victor Akosile: I think I may share a few skills and mindsets that maybe are not so common, that I think are really important. And I think that allows people to really leverage their strengths and bring in different kinds of skills and expertise to the table. The first thing is the skill of storytelling, right? People need to be brought along, alright, you’re doing all this analysis, you’re crunching numbers, putting charts on the screen. It is not the end of the cycle here. Just because you have seen the insight, you have to bring people along in the journey that you went through. Now, there are some times and some places where some people just don’t want the answer. But in my experience, nine times out of 10, if you could give an answer of like, okay, well, why is this happening? Well, this is why the next common question is, well, how do we know that? Now you’re getting through the story, alright, well, this is what we looked at. And this led to this, and I know from this department, they tend to do this kind of work. So this is what I look at here – to bring people along on that journey. And being able to be a great storyteller, I think is a super important skill. The next important skill that people may overlook that I think is important is to really be a good teacher, a good educator, right? In a lot of my roles, I find myself helping people understand what’s important, what to look at, and why. And you’re really, you know, you’re teaching people the basics of analytics and how to be a smarter consumer of people data. And that’s not something that is naturally occurring, like for most people, so you do have to have a way about your skillset, to be that coach and to be that teacher to help them see things that they may not have seen before. And you know, that’s not an analytical skill. That’s a people skill, you know, what people call soft skills, right? So I think, and I say those two first, because I think it helps you to understand the role that different people can play on a team, right? Not everyone has to be the number cruncher because, at the end of the day, you have to share, communicate, teach, and expose what you’ve done at your computer for, you know, hours with others. And if that doesn’t come across well, the impact of your insights just gets diminished. So I think those are two things that I think are important, but I’ve seen, along with all of the other things that you would expect, you know, analysts, maybe data like engineering and things like that, but I think a lot of people know that now. So I wanted to put some emphasis on these other things.
Neelie Verlinden: Yeah. And I think it’s really important that you do so because it’s exactly like you put it, I mean, if you’re in all this number crunching, you’ve got all the data lined up. But if then you’re not able to explain all this data that you found, it’s gonna become a very difficult undertaking, I think, to get something done within the organization. So now, I think we get to one of my favorite parts of the episode, actually. And it’s the part where I get to ask my guests, first of all, what they believe is the biggest cliche out there about HR.
Victor Akosile: The biggest cliche, and I think this cliche is rooted in some level of truth. I had one executive say that HR is a cost center, and you know, it should be handled as such. Sure, they can provide some value, but ultimately, they’re costing me money. And I came back to the executive and I said, Well, you spent a lot of money. I’m marketing, right? Is marketing a cost center? And he said, Well, you know, I don’t know, I mean, they can help like to drive sales. Oh, okay. Cool. Cool. So who was driving though? With a sales department, okay, who works? Well, you know, the employees work inside. Okay, cool. And what if your HR was not good and all your sales employees left? Now HR is losing me, man. Ah, so if they can lose money, then they can make money. Right? So that mindset of HR being a cost center is really cliche. And I say that going back to my first point of like, data-driven HR, where data is in the forefront can actually set a lot of your strategy, especially if your business is really heavily dependent on people, which, according to the latest stats, I have seen 70% of businesses expenditures comes from people. So for most businesses, you know, this can work where if you really look at your people data, and AI really drives your people strategy, that can really drive your business strategy. So, you know, and I think HR was in that shift there, you know, it’s an interesting shift to make because people have to believe that this is the new HR, the same way that people had to believe that, you know, marketing is not a bunch of artists creating stuff, there are like analysts to, you know, measure so many things. Now, it takes some time for that shift to happen. But I think that’s the shift that’s happened. So that’s my cliche, I don’t know if that’s a cliche answer, but I’m sticking to it.
Neelie Verlinden: Nice, nice. I love that you’re sticking to it. And no, that is definitely not a cliche answer, if you’re gonna have to say I find that a pretty tough one. So thanks for that. And then I have one other thing, or actually two. And this is when I ask our guests to share an epic win and an epic fail with us. And it’s up to you to decide which one that you’d like to start.
Victor Akosile: Yes, epic win and epic fail, I have a lot more of one than the other. I’ll have you guess which one is which. I think an epic win for me is, and this happens kind of sometimes ago, but, you know, going back to what I said around, you know, leadership matters and leadership expectations, drive conversations, I’ve been very fortunate to see that, you know, through or working with an organization, or around retention, pay equity. Having the CEO really changed the expectation that this is not a byproduct of something that, you know, we are going to look at people data or at each of our key strategic meetings, and we’re going to talk about it. And we’re going to base our strategy using this kind of data. Right. So, you know, we were helping them with some pay equity retention stuff, but I think what I liked about it was because I had the privilege of being inside a few of those meetings and the conversation truly did start to change, there were other VPs and executives who were reporting on their performance, based upon the KPIs of their people, not just revenue, right. And I think that to me was like really, really rewarding to know that kind of organization, they were trying to justify their profits or losses, based upon people data. A really rewarding experience. It may not be the biggest thing, but you can see and feel the impact that those things have on the organization.
Neelie Verlinden: Beautiful one. That’s a beautiful one.
Victor Akosile: So failures. Okay, now, where do I start? I think something that was a failure early in my career was that, and I think I mentioned this earlier, too. So maybe I was challenging. It was that I didn’t take note or understand the maturity of the organization was when it comes to people data. So you know, I thought I was hot stuff and said, Okay, well, I’m gonna show you this and draw these correlations and show the models and tell you how much impact this thing is having on the other. For an organization that was super ecstatic when they could get their headcount correct. You know, and I think sometimes you can go too far and not bring the organization – and really I say the organization but it’s really the people there – along and because of that huge gap, it’s hard for them to wrap their heads around. So again, it’s hard for them to believe it right? Like you’re changing hearts and minds. That’s essentially why you’re doing this and if you don’t bring people along, it doesn’t matter how fancy your analysis is, you know, the gap is just too far for them to jump or to say, well, I’m going to change my worldview and how I do work based on what this hotshot consultant just told us here. So I think that is a farrier that I’ve learned. And this is why I said that the teaching part is really, really important. You have to be able to bring people along. So I made that mistake quite a few times before I realise you should probably change that. So yeah.
Neelie Verlinden: Nice. That’s it. It’s a beautiful learning that you have there though, Victor. I mean, thank you very much for sharing as well. And I think that actually brings us as well to the end of our conversation, Vic. I mean, I really enjoyed it. I hope you did, too.
Victor Akosile: Oh, this was lots of lots and lots of fun. Thank you so much for having me.
Neelie Verlinden: You’re very welcome. And thanks, everybody for tuning in as well to today’s episode. If you haven’t done so yet, please don’t forget to subscribe to our channel, hits the notification bell, and like this episode. Thank you very much for watching, and see you again soon. Bye.