How People Analytics Help Solve HR and Talent Management Challenges

Speaker A: Welcome to the Work Trends podcast brought to you by Talent Culture. I'm your host, Megan Mbiro. Each episode I interview really smart people who are reimagining the world of work. Be sure to stay current with all of our insightful podcasts by visiting our page at Ah, Talent Culture, Work Trends, M on Apple Podcast or Spotify. And of course, you can listen to talentculture.com on the podcast page. Hello, and welcome to an encore episode of Work Trends. From time to time, we bring back standout conversations that sparked meaningful insight and connection. If you missed this one the first time, now's your chance to dive in. Hello, welcome to the Talent Culture Work Trends podcast sponsored by SAP SuccessFactors. I'm your host, Megan Mbiro. In this episode of Work Trends, we explore how people analytics is literally reshaping the world of HR and talent management. From transforming workforce data into powerful insights to using AI agents for smarter, faster decisions, we're looking at how leaders are leveraging analytics to drive engagement, retention and performance. But before we begin today's podcast, I have a couple of burning questions before we dive into this podcast. For you out there, my important people in the audience, what excites you about how people analytics can shape the employee experience? And number two, does your organization effectively use people centric data to make these kinds of strategic HR decisions? I'm hoping, but it's okay if the answer is no. Today we are joined by Soren Hoiby and Mick Collins with SAP SuccessFactors. Soren serves as the Senior Director of Product Management for People Intelligence at SAP SuccessFactors. He has product responsibility for strategic workforce planning, operational headcount planning, dashboards, embedded analytics. I don't know what you're thinking out there in the audience, but that's a lot as it is.

Speaker B: Wow.

Speaker A: His specialties include product strategy, building new innovative products and growing business startups. Mick is Global VP GTM for SAP SuccessFactors. He is responsible for go to market messaging, commercialization strategy, internal sales training, prospect and customer engagement, partner management, and guess what, there's more. Product thought leadership. We love that. Mick's passionate about teaching strategies for the effective deployment, utilization and communication of workforce data and sharing case studies which we adore of company successes and struggles. Because we're going to get real Today. Mick and Soren are helping organizations turn complex data into actionable workforce insights that truly move the needle. And we are absolutely honored to have them here today. So welcome. We are thrilled to have you both with us.

Speaker B: Thank you.

Speaker C: Thank you. Great to be here.

Speaker A: All right, so I'M just going to dive right in. Mick, you're on the hot seat first. You ready?

Speaker B: I am indeed.

Speaker A: All right. What talent management challenges today are most in need of getting better data and insights.

Speaker B: So I'm going to say three things, three major themes that we tend to hear. The first is around capability. Now, the headlines talk about the need to develop more AI skills and employees, but it's really much broader than that in terms of helping employees across all walks of life develop the skills and the aptitudes they need to be successful in the coming years. And this really then factors into how organizations set up their skill development programs, how they change their hiring efforts, and so on and so forth. So I think capability is probably one of the biggest areas of need for better data. Second is capacity, uh, employees capacity to fulfill the work, uh, that they're engaged in, whether that's due to mental health and stress and burnout or responsibilities at home with childcare or elder care as well. So better understanding. Not only are employees able to work, um, but do they have the capacity to do so? And then probably the third big theme is this idea of fairness. And we'll touch upon this a little bit later. But younger employees expect organizations to be good corporate citizens and be transparent and fair in their work processes. And I think it's an area that's really untouched by data.

Speaker A: Is so well stated. And I have to tell you, this is an important foundation to our conversation today. I know many of you out there in our work trends and talent culture communities, you have similar challenges and are seeking advice from experts just like this. So, Soren, we're going into people analytics. So I gotta tell you, People analytics has come a long way in a short amount of time. Let's talk AI, agents and other tools leading this new era of HR intelligence for our listeners out there. I know you're at different levels of adoption, so would you do us a favor, Soren, and break it down? What are the complex problems you're solving?

Speaker C: Yeah, thanks. Yeah, I think AI is incredibly exciting for everyone, right. And particularly for analytics. Like, if you think about analytics was just a couple of years ago, any insight you needed, you had to run a report, find a dashboard where that insight was surfaced, and you had to kind of decipher a chart and figure out if there even was a problem to be solved. Right. So that is now, um, kind of a thing of the past. Like with AI, we can do so many things and it's incredible. Just think about democratizing analytics. The easy access. You can just ask a question and get an answer rather than having to know which dashboard to navigate to to find a particular metric. Second of all, of course, now you get the insight. Do you actually understand what the chart is showing? Well, AI can help you generate a narrative to explain to you what you are even looking at. And that's just the kind of tip of the iceberg because of course from there you typically go on a bit of a treasure hunt to find the root cause. If you see a trend in a KPI trending the wrong way. Right. Where's the problem? Like, how do you, how do you find the root cause? You may see some charts indicating that certain segments have a, um, problem. But is that the true root cause? Like, it's always a bit of a treasure hunt and that really leads to the final problem, right? How do you then know what to do about it? How do you turn the insight you got into action? If you're still unsure what the real root cause is, that's incredibly difficult. So I think that's the areas where AI can help. I guess for many organizations that are still at the, at the beginning of that journey, it's all about that easy access and democratization. But as you mature through your AI journey, I think that kind of easier access to root cause and even specific actions you can take without having to be an analytics expert already, that will really, uh, help a lot of customers well.

Speaker A: And I have to say, Soren, I appreciate that you acknowledge that HR leaders are literally all over the map around the world right now and how much access they have to HR intelligence. I don't care if you've got, if you're out there and you've got a small budget and a team or you're a multinational company, please understand something. There are solutions within reach that I believe are guaranteed to change how we all look at data. So, Mick, this one's for you. Leaders today must be able to be more savvy with how to gather and utilize people data, using it to spot trends to boost engagement. Fingers crossed. And improve retention. Can you share a few examples of how you're seeing that play out?

Speaker B: I, uh, can, yes. I think we're in a cycle now where HR is being much more proactive about engaging leaders and helping them understand what the right questions might be to ask. I think for many leaders, they come through a Masters of Business administrat registration program that probably touches on HR topics for all of about five minutes across the course of two years. So we have to be more proactive about what are the Right. Questions to be asking, uh, based on often our leaders limited experience with HR data, beyond some of the examples you mentioned a moment ago. I mean, retention, turnover, two of the biggest topics. But leaders who are more informed now are not just saying, what is my turnover, turnover rate or my retention rate, for example, but what does it mean for critical parts of the business? How do I take that and apply it to operational capacity? Or how do I apply that to work workforce planning and thinking about the future kind of workforce. So, you know those HR organizations that are improving their maturity, positioning data as a set of questions versus a set of traditional metrics, they're also trying to be more proactive in terms of providing alerts to leaders to spot trends ahead of time or as these trends, uh, exacerbate a certain problem or an opportunity, for example. And, uh, probably for me, the two most important elements as to how leaders are becoming more effective. One is they're thinking about this in terms of stories. You know, data is just data. You have to bring it to life by telling a story story that connects the investment in people to the outcomes that an organization is trying to achieve. And it's that storytelling that helps leaders really connect with the data much better than they have been able to in the past. And probably the second piece is we have now the data and the tools to be more rigorous, to be more scientific, to be able to challenge conventional wisdom. The leaders have about, you know, you can't train sales employees. You know, you have to, you have to buy sales employees. You don't make them. Let's use data now and science to test those assumptions and maybe in some cases prove people wrong.

Speaker A: You know what, I love that you just said that. We don't always have to be right. We really don't. Everybody take that in for a minute, okay? We don't have to have all the answers. We have to ask smart, uh, questions. Right? These are great insights. This question really is for you both. SAP has really led the way with people intelligence insights that go well beyond traditional HR reports. What's the philosophy between the investment and creation of your people intelligence platforms and what's exciting each of you most?

Speaker C: I'm, um, happy to go first, Mick. What really excites me about our new people intelligence offering is that it's an AI, sorry, an SAP wide initiative, which means that we can really leverage all the broad analytics and AI innovations from all of SAP. So that's incredibly important when we have to think about what Mick just touched upon, like what is the impact of the HR Uh, initiatives you set in motion. How does that impact your business metric? Are you in fact helping provide the talent that the business needs and improve the business metrics or of your organization? So the fact that hr, ah, only system, but really for all types of business data allows you to have that impact analysis from the initiatives you make in hr, uh, to the business metrics in other areas.

Speaker A: Well, I have to say your enthusiasm is contagious. I think it is a very exciting time in our industry and this is really illustrating the value in this investment. Right. So, Mick, finding and then effectively applying workforce data used to be a challenge, right? Let's get real. But now we have so much more at our fingertips. So tell me, how are people analytics changing overall HR strategy? What's cooking there?

Speaker B: Yeah, I think for me twofold. One is it helps HR become more agile. You know, without data, we're essentially, we're flying blind. We don't quite know how the millions and millions of dollars we invest in our people are actually turning into the outcomes we're trying to seek. And having access to the data, the alerts, the artificial intelligence helps us become more agile. We can start to change and pivot away perhaps from programs that are not working as well as they were intended and invest more in new programs that will have a greater impact. I think secondly as well, it's helping HR organizations create more personalized offerings. Now we've been touching upon this for 20, 25 years or so that not every employee wants the same things from their employer. Uh, you can use things like conjoint analysis to determine what kind of benefits might Soren want from his company versus what I want from my company. Maybe Soren wants more time off. Maybe I want more investments in my retirement programs. We can data to start to create more personalized packages for employees. So we're not necessarily, uh, employing this peanut butter approach where everybody roughly gets the same, but we can, we can invest more in hyper personalization. So the agility, the ability to pivot quite quickly based on the data and then create more personalized offerings, I think are two ways in which analytics itself is really shaping the future of, ah, HR strategy.

Speaker A: Did I just hear you correctly? Did I hear the words peanut butter butter approach?

Speaker B: You did.

Speaker A: You know what I've done now over a thousand podcasts in my career and no one has ever said those words to me. Congratulations. That's really interesting.

Speaker B: We are breaking new ground here with

Speaker A: the, you know, we're doing big things over here at talent Culture, I tell you. So listen, this is an Important point. The peanut butter is important too, by the way. But this other thing that we're talking about isn't just about technology. This is a true shift in vision and execution from top down. I think that's why we're collectively so intrigued by the impact of today's HR tech, even more than we have been in the past. So this one is for both of you. Can you give us some real examples of how your customers are using analytics to make better, faster decisions across their organizations?

Speaker B: Yes. I'll take this one first. M first example is in a call center. It's hard to spot a better use case for real time analytics than in a call center where employees are answering calls, often from, uh, disappointed or frustrated custom. But there was an organization we worked with who was experiencing high rates of turnover at a call center, naturally. So there are many cases you're looking at 25 to 35% termination rates from year to year. They were above that number, and therefore there was some concern that they weren't paying their call center representatives enough money. So a proposal on the table to increase compensation for all of their call center employees instead, with some analysis, they found it was less tied to compensation. But the root cause of terminations were that employees were not given a good preview of the role. They were not told exactly how challenging it would be and hopefully rewarding, but how challenging it would be to work in a call center. So they changed their preview. They would give candidates a chance to tour the call center to meet with representatives, to shadow calls, give them a much better understanding of what it means to be a successful call center representative. And that was the policy change they put in place instead of just handing out more cash, which may have solved some termination issues, but certainly wasn't the problem or the solution to the problem they had in mind. So you see examples like that with call centers with sales training. Again, this idea that you can't train salespeople. Right. Salespeople are made. Well, no. We've had customers that have used the analytics to reinforce the need to train employees, regardless of tenure, regardless of experience in a sales role. And by doing so, they see a sizable impact, uh, in the customer acquisition and the revenue numbers of these fully trained sales reps. So more and more you see examples of people actually taking decisions based on data, in some cases challenging those myths about how the workforce operates rates, but ultimately doing something with the data, which really is the holy grail.

Speaker A: Oh, for sure. And let's not forget managers out there. Okay, I'm getting a little tired of HR managers, talent acquisition managers, you name it. Us here at the Future of Work, not getting heard. Uh, you said it doesn't matter what your tenure is, what your role is. You know, you can be anywhere in that life cycle, right?

Speaker B: Yep.

Speaker A: What else? Other stories. Because that's what we're talking about. Teams, creativity, narratives, putting a story, humanizing data. And these are great examples. Right.

Speaker B: I'll give you one other example in an energy company where they were talking about workforce planning. Now, if you mention the words workforce planning to most leaders, their eyes tend to glaze over. It's somebody crunching numbers in a spreadsheet in a darkened room for 12 months of the year. And that data never sees the light of day. But they went to their senior executives and talked about this. Not in terms of, of retirement rates, but how many years of experience they were going to lose in the next five years. And they quantified this and they said, we think in the next five years we're going to lose 8,063 years of experience. And um, even if you think that 1,000 years of those experiences are, uh, no longer needed, that's outdated knowledge. That's still 7,000 years of experience that we might lose in the coming years. And armed with that kind of visual a talent cliff, if you will, they were able to get the resources that he needed to actually put in place a workforce planning approach that is so cool.

Speaker A: This is so important because us getting past the technology and the theoretical language and into the practical applications that frankly make HR leaders, everybody along the journey have those aha moments. Well, you know, time flies when we're having fun here because we've hit my last question today and I want to hear from you both. Both, let's flip the lens to the employee experience. How is this technology helping organizations better harness skills, enhance the day to day experience, and ultimately, this is my nirvana, ultimately retain great talent.

Speaker B: Soren, you want to go first?

Speaker C: Yeah. I mean really, the outcome of great analytics should be felt by every employee. Not every employee might use analytics. Like, if you're an individual contributor, there are certainly things you can analyze. You know, what is your, your uh, personalized career paths, what, uh, are great learning recommendations for you in your specific role. But all the interventions that an organization put in place, all the actions they take as an outcome of a great insight where they understand the root cause and know what actions they can put in place to improve the situation, that should be felt by every employee. So like, if you realize that having an onboarding body during the onboarding process will actually, you know, help lower the no show rate and also the low tenure termination rate. Then that investment in finding onboarding bodies for all new employees, well that will be felt by everyone that joins the organization. So I think there's lots of these examples where you don't know that it's analytics that helped improve something in your daily life, but it might have been. Mick?

Speaker B: Yes, to echo on your point there about the uh, almost the return on investment, I give my company my data, whether it's my demographic data, whether it's my employee engagement surveys, and now as an employee I expect something in return. And you mentioned this in terms of learning recommendations. We're going to hopefully go a step further and get into really better, uh, career pathing. So we as employees know based on data, what the right career path opportunities might be for us moving forward. But yes, expectations have increased that I will get some data in return for the data I'm giving to the company. And also you mentioned that point around leaders who are listening and taking action that they're communicating to employees that we are taking your data and we are doing something with it. And here at SAP, a few years ago the company implemented what they call call Focus Fridays, which the idea being that try to limit the number of calls you have on a Friday so you can finish your work off, you can attend to customer needs, you can get ready for the weekend. That was implemented as part of a, uh, result of a survey that they did. So employees get the sense that, yes, uh, my company's being transparent. My company is using the data to close the loop and take some action based on that data and hopefully that improves my connection to the company and my experience here as well.

Speaker A: Well, retention has been a hot term for the last couple of years and honestly it should always be important. It always has and it's always will be. I know that the workforce is changing when I say that I'm talking to all generations right now. Please understand this. When we can illustrate that the adoption of new technology will improve the employee experience and therefore compel people to stay, we are all winning. Thank you so much for stopping by. Mick and Soren, Thanks. Thanks again. Sren and Mick. We really covered a lot today and I'm super glad you shared your insights, predictions and applicable examples. So here are a few of my key takeaways. Number one, people analytics is no longer optional. It's essential. Organizations that leverage data driven insights are improving engagement, retention and performance faster than those relying on intuition and outdated processes. Number two, AI and analytics are transforming HR from reactive to proactive. With the right tools, leaders can predict trends, identify skill gaps, and make faster, smarter workforce decisions. Number three Better data creates better employee experiences. When organizations use people intelligence strategically, they empower people, elevate culture, and build workplaces where talent can thrive. This has been a special encore edition of the Work Trends Podcast. Uh, a reminder that the most meaningful conversations at work don't expire. We invite you to explore more episodes featuring the people shaping what's next in the world of work. Thanks for joining us for today's conversation. I hope you enjoyed it as much as I did. I love learning something new in each and every episode. Just a reminder that you can listen to all of the Work Trends Podcast on Spotify, Apple Podcasts, and the podcast page@talentculture.com or your favorite podcast platform. Be sure to subscribe so you can listen on M the Go and stay up to date on all the latest news you want to hear. I look forward to catching up with y' all next time. And I hope today's information made you wiser, happier, more informed, and most importantly, thinking of how you can use it to improve the quality of your career, your life, and your world of work.