With a growing number of use cases, people analytics continues to develop both in sophistication and the amount of value it drives for employers. However, despite the quantum leap in recruiting technology we’ve seen in the last few years, I still feel that talent acquisition is significantly lagging behind where it should be in terms of data and analytics.
My guest this week is Vic Akosile, an HR Strategy Consultant at Humananalytics. Vic is a highly experienced people analytics specialist. He gives us an excellent overview of what is going on in the space and what talent acquisition leaders need to consider if they want to develop their data and analytics capability.
In the interview, we discuss:
• The evolution of People Analytics
• Cutting edge use cases
• Increasing digital interactions mean increasing amounts of data.
• People Analytics in talent acquisition
• How to develop more sophistication in People Analytics
• What trends is technology driving
• Using sentiment and network analysis to help with retention
• Where is People Analytics going in the future
Support for this podcast comes from Eightfold.ai. Eightfold.ai delivers the talent intelligence platform, the most effective way for companies to retain top performers, upscale and rescale the workforce recruit top talent efficiently, and reach diversity goals. Eightfold.ai’s deep learning artificial intelligence platform empowers enterprises to turn talent management into a competitive advantage.
Matt Alder (47s):
Hi there, this is Matt Alder. Welcome to Episode 430 of the Recruiting Future Podcast. With the growing number of use cases, people analytics continues to develop both in sophistication and the amount of value it drives for employers. However, despite the quantum leap in recruiting technology that we’ve seen in the last few years, I still feel that talent acquisition is significantly lagging behind where it should be in terms of data and analytics. My guest this week is Vic Akosile, an HR Strategy Consultant at Humananalytics.
Matt Alder (1m 29s):
Vic is a highly experienced people analytics specialist. He gives us an excellent overview of what’s going on in the space and what talent acquisition leaders need to consider if they want to develop their data and analytics capability. Hi, Vic, and welcome to the podcast.
Vic Akosile (1m 48s):
Hey there, Matt, how are you? Thanks so much for having me.
Matt Alder (1m 50s):
I’m very well, thanks. And it’s an absolute pleasure to have you on the show. Please, could you introduce yourself and tell everyone what you do?
Vic Akosile (1m 57s):
Sure, sure, sure. Hello there everyone. I’m Vic, Vic Akosile. I’m in the Washington DC area here in the US and I work as an HR consultant, people analytics consultant, HR technology, all of the above, and been doing so for close to about 15 years now, all under HR strategy. So I’ve had a chance to work with a lot of different clients in multiple industries, both large and small. And I think I’ve had a really interesting perspective and how things have changed here. I also host my own podcast, Humanalytics, so a shameless plug, check it out, where we talk to HR tech founders, senior people leaders about the future of HR technology and analytics, behavioral science, all the fun stuff there.
Vic Akosile (2m 50s):
So check it out.
Matt Alder (2m 53s):
And I’d recommend everyone to check out your podcasts because it’s such a great topic. I suppose, zooming in on that topic, lots of people listening may not have an in-depth understanding of everything that’s going on in people analytics. So just by way of background, talk us through how people analytics has evolved over the last few decades.
Vic Akosile (3m 16s):
Sure, sure. You know, I think there’s a misconception that people analytics is a kind of a newer function where really, I think it’s an evolution of something that HR professionals have been doing since the dawn of time. If you start from your basic headcount, right, how do you make sure that’s accurate? Can you predict what that looks like? You know, those are in my mind, the foundations of people analytics, and I think because of the proliferation of computing technology and what I consider the accessibility of how machine learning and statistics, you know, how it’s done, there’s been this growth and explosion in how can we get more sophisticated, more precise, more accurate when it comes to our workforce and our business.
Vic Akosile (4m 11s):
And then, therefore, people analytics has really grown from either the person in HR who knows excels, the best, full-fledge people, massive actually, people analytics functions, especially at a lot of the tech firms where the challenge and quest for talent is at its all-time high. So I think that’s how it’s evolved over the decades, but I think there’s there’s space for everyone to participate. You know, if you’re just getting in or if you’re an expert who’s moving in to the field, it really is a wide-open ocean for people to bring their best to the space.
Matt Alder (4m 57s):
Absolutely. And it’s something that’s very much evolving in sophistication all the time. And I suppose what would be interesting is to get your thoughts on what is the cutting edge in people analytics look like, what really interesting things are companies doing and what are some of the use cases you’re seeing for?
Vic Akosile (5m 18s):
I’ll share two. The first one that comes to mind is a bit of a classical use case, but it’s still cutting edge because it’s not everywhere that I can do this as easily or as well. And if you do it, it has a lot of impact. My mind goes back to, I think it was in the Wall Street Journal in 2015, the article or case example of Credit Suisse, where they were able to, you know, look at a lot of factors within their HR data and their business data, and be able to predict to a reliable standpoint of who would be leaving within the next upcoming year. Now that’s pretty cool on itself.
Vic Akosile (5m 59s):
But I think what made that example so impactful was not that they calculated who was prone to leave, which was helpful, but they were able to calculate the cost of turnover in a very, you know, hard financial numbers so that they were able to say, well, through our efforts and through these interventions, this is how much money we’re saving the business. And a 1 percent reduction in turnover trancends many millions of dollars. So their impact was not just colloquial. It was really on bottom-line impact.
Vic Akosile (6m 40s):
And I think that was, that’s a great example of using people analytics. It’s a classic one, but I think it just shows you how it can really translate to business. And I think the other one that I think is becoming more popular and it’s still, and it is pretty cutting edge is really trying to use network analysis, which is trying to understand the networks within your organization. And this kind of analysis wasn’t so mainstream let’s say prior to the pandemic. However, since a lot of our interactions have gone online, there’s a lot more data around how we connect or disconnect.
Vic Akosile (7m 21s):
And I think that kind of analysis there of, you know, what are the networks are certain people being promoted more in certain networks, you know, is a really interesting use case of really people analytics on the edge there. And it’s always fun to look at that data.
Matt Alder (7m 38s):
That’s really interesting now, particularly around all our interactions became more digital, obviously, there’s more data to analyze, which is fascinating stuff. What about recruiting? What are you seeing happening with analytics in recruiting? What’s good, what’s not so good?
Vic Akosile (7m 57s):
Yeah, sure. I think recruiting a talent acquisition has always been really, in my mind, one of the first places where things like machine learning and AI came to bear, just because there’s just huge disparities between recruiting teams and the number of applications they get and have to screen through. You know, I’ve talked to recruiters before and they say that sometimes up to 75 percent of their job is trying to screen through resumes. And that’s just what happens if you don’t have the technology to be able to make your process more efficient. So a common use case is really, you know, this intelligent screening or, you know, you’re using AI tools to try to help the recruiter get to that best candidate as quickly as possible.
Vic Akosile (8m 50s):
Obviously, with every innovation, there are downsides because, you know, in more advanced kind of applications, the AI is trying to say or trying to guess out which candidates may be the best and it’s using past human decisions to therefore drive future decisions. And I think it’s very commonplace knowledge now that there could be biases within certain decisions we’re trying to make. So therefore those biases don’t get evened out because of AI. At times they can get exacerbated.
Vic Akosile (9m 30s):
So really being able to monitor to check, you know, how one group of people are flowing towards like another, if there are inherent biases within that technology is a big thing that I’m seeing in recruiting. And I think one other thing that I’ll point out is it’s really an application of something that’s used kind of elsewhere in the customer service, and that’s recruiting chatbots. You know, if you’ve ever gone on our website and they had that little bot feature in the right where you can talk to somebody, but everyone knows it’s a computer. That’s something that I think recruiting is slowly adopting because I think we’ve all had that experience of sending off your resume, not hearing anything back at all or recruiting bots, especially for those high volume workforces, it’s a great way to have that interaction when you don’t have to hire, you know, a hundred more recruiters, but you can use technology to have that conversation, to get that information, and then take on the experience from there and for those people you would like to move forward to.
Matt Alder (10m 42s):
And I suppose, just to dig a bit deeper into that maybe, when the clients that you’re working with, and indeed anyone who’s listening who wants to use data in a more sophisticated way in their business, what’s your advice to them in terms of getting started? Or what should people do or what should people be thinking about if they want to get more analytical with the data that they have?
Vic Akosile (11m 6s):
I think you need to have a clear idea of what’s possible. And you know, that there’s obviously, you know, lots of white papers from lots of consulting companies that will tell you what’s possible like with data. But I think that’s one, but then I think too, you really have to understand the business drivers and what HR can bring to the table. For example, if you work at a consulting firm and where you bill out, you know, people then, you know, retention is a direct input of revenue versus, maybe let’s say a software engineering a company where, you know, you are hiring people to maybe do R&D software like development and grow.
Vic Akosile (11m 47s):
And then you have salespeople, you know, striving. That’s a different business model. So I think that’s one thing that you really do have to understand. And I think too, it really gets back to the quality of your data, right? We all know the adage of “garbage in, garbage out,” and sometimes having good clean data and maybe your basic level of analytics, it’s enough especially for those organizations that may just be starting out on their people analytics training. So don’t get so caught up in, you know, I want to do these like fancy models and things like that. Honestly, your basic analytics and sharing that, and then understanding the trends and cycles of your business, very, very insightful.
Vic Akosile (12m 28s):
So I think that’s something I encourage people to do. Now, if you’re, you know, progressing like a little bit further, I think my recommendation is definitely to build the right team. People who have context of HR, but then obviously, knowledge of the various methods you use to calculate, you know, certain parameters or use certain models. And that’s really when you start to build your people analytics function, but, you know, there’s a spectrum. So understand where you are, understand about the business drivers and then plan accordingly.
Matt Alder (13m 3s):
We’ve talked about technology, we talked about the larger amount of data that’s out there. What trends are you seeing from the increased use of technology in, you know, analytics across HR and recruiting?
Vic Akosile (13m 17s):
I think that one thing that immediately jumps out to mind is now there’s such a push to hire, especially with our service industries, and the need to have people on board is so great that businesses can’t afford long lead times between the moment a candidate applies for a job and the time that they are starting. You know, I think ideally, if you talk to some front-level managers and store managers, they would love to be able to interview some person that morning and that person is on the shift that evening, right? So in an environment like that, the technology has to be able to facilitate that.
Vic Akosile (13m 60s):
And I think a lot of our, let’s call it big-service providers in applicant tracking systems and HR systems, in my opinion, they’d been tuned too much for maybe knowledge workers and maybe how they apply versus, you know, somebody who works at a warehouse or a grocery store, which we’ve learned through the pandemic, those are our essential workers. So I think because of the pandemic, it’s really exacerbated this question of how can I go from a candidate sees my job application to they’re hired in the shortest amount of time. So that time to hire KPI, I think has a reason to front and center, I think more than ever for a lot of these service-based industries.
Vic Akosile (14m 48s):
And I think too, it’s more of an emphasis rather than innovation on finding ways to listen to our employees, to find ways to understand what they’re saying from a large population of people, to be able to pre-address things before they, you know, maybe grow into retention problem. And now you have retention issues in a talent market that’s so hard to hire in. So I think those are, I think, two things that are really driving technology and driving a lot of choices for businesses to choose the types of technology they’re going with faster hiring and better ways to listen, understand, and communicate with their employees.
Matt Alder (15m 38s):
Final question, obviously impossible to accurately predict the future as we’ve all learned in the last few years, but I’d be really interested in your opinion on where people analytics is going, where’s it going next? Where’s it going in the medium to long-term?
Vic Akosile (15m 52s):
I think about this question a lot, Matt, and, you know, a lot of times, we think that it would be something completely new, but I tend to think it’s an evolution of things we’re currently doing, currently looking at. So I think what you’ll see is that a lot of the business strategy will be driven by the people strategy where I think prior to it was the financial strategy that was driving a lot of the business strategy. I think even on Wall Street, they’ve come to the understanding of how you treat your people matters, right? So I think it was 2020 or maybe 2021, the SEC, the Security Exchange Commission here in the US announced that it was mandatory for companies to start reporting out on people-based metrics.
Vic Akosile (16m 47s):
Now, what does that mean? If I’m a CEO and I know that wall street and investors are going to be looking at this data, well, now I have a more incentivize energy to make those numbers look better now in reinvesting in my people. And as more really millennials kind of are more coming into the investing space with the democratization of investing, they’re looking at companies who are more sustainable, who treat their people well, and they will choose where to invest. So I think the incentives are aligning with the people strategy, and I think more than ever before, that’s where people analytics will be deployed to help create the people strategy that helps the business strategy here, Matt.
Matt Alder (17m 35s):
Vic, thank you very much for talking to me.
Vic Akosile (17m 37s):
Oh, Matt, this has been great. Thank you.
Matt Alder (17m 39s):
My thanks to Vic. You can subscribe to this podcast in Apple Podcasts, on Spotify, or via your podcasting app of choice. Please also follow the show on Instagram. You can find us by searching for Recruiting Future. You can search all the past episodes at RecruitingFuture.com. On that site, you can also subscribe to the mailing list to get the inside track about everything that’s coming up on the show. Thanks very much for listening. I’ll be back next time and I hope you’ll join me.