Nick Haap: ‘We Want to Become a Culture of Continuous Development’

Nick Haap:

If you think about an individual’s perspective, that’s how they feel. That’s their reality, and so we’ve got to make sure that we understand how we’re feeling instead of just looking at the cold, hard numbers, because they don’t tell the full story. You’re still hearing things as a leader on the floor when you talk to your employees, you have informal conversations. They want to make sure that you are taking note of that and taking stock of what you could potentially change, and what you could potentially impact, to make the employee’s overall experience even better.

Ashley Litzenberger:

Hi, and welcome to Betterworks People Fundamentals Podcast. I’m your host, Ashley Litzenberger, senior director of product marketing. Betterworks’ core belief in people fundamentals revolves around helping HR lead through constant change by focusing on core values like fairness, support, balance, and enabling growth for employees. These tenets empower everyone in the workforce to strive for excellence, to foster creativity, and to acknowledge each other’s contributions. Betterworks believes that strategic HR leaders can translate these principles into action, shaping their workforce for the better, and helping drive meaningful business outcomes. 

And in this show, we’re diving even deeper into these principles by listening to experts share how you can make them come alive at your organization. In this episode, I’m joined by Nick Haap, director of talent management and employee listening at KeHE Distributors. Nick has led the charge in integrating continuous listening, performance enablement, and data-driven insights into KeHE’s talent strategy.

In our conversation, Nick shares how his team has shifted from traditional performance management to a model that helps employees unlock their potential through regular, structured conversations. We’ll explore how KeHE uses centralized people analytics dashboards to connect engagement, performance, and retention. And we’ll talk about the role AI is starting to play in making these insights easier for leaders to act on. If you’ve been looking for practical ways to connect to your performance, engagements, and analytics strategies, this episode is full of ideas you can bring back to your own organization. Let’s dig in. 

Hi Nick. It’s so nice to have you on our podcast today.

Nick Haap:

Thanks for having me, Ashley.

Ashley Litzenberger:

Before we dive in, I just want to note, you are the director of talent management and continuous listening at KeHE. And I’m curious, where did the part of the “continuous listening” in your title come from? I’ve never seen it before.

Nick Haap:

Yeah, I inherited early on, and some former colleagues of mine had actually started venturing down the path of how we could do employee engagement even better. And it was set off by COVID, as many things were, where they had just finished an entire annual engagement survey. And by the time that they were going to start acting upon the results, all of a sudden, COVID hit, and the company went into survival mode, and nothing was done with the results. So, the thought was, we need to do something that is a little bit more frequent. In fact, they were pushing for weekly, and so hence this, as you can see on my shirt, “the KeHE vibe” was born. And it would basically ask each team member how their week last week was at the end of the week, and give them, on a scale of pure goodness to not so good, a reading, and then they would have an opportunity to provide a little bit more detail around it.

It’s since evolved, but I’ve inherited this program, which I thought was very innovative, and it’s been really exciting. And the reason that we’ve titled it “continuous listening” more broadly is because we want to encourage our leadership team to listen to their team members, and the vibe is just a supplemental portion of that, right? It’s great because we can get some analytics, which we’ll of course talk about, and confidential insights that people might not be willing to share in person. But you’re still hearing things as a leader on the floor when you talk to your employees, you have informal conversations. We want to make sure that you are taking note of that, and taking stock of what you could potentially change, and what you could potentially impact, to make the employees’ overall experience even better.

Ashley Litzenberger:

That is really cool. As a marketer, I firmly believe that words matter, and so I get really curious when I start to see new terms emerge or new titles getting created. And I think continuous listening really reflects the role that HR has, which is to have a pulse on what’s going on with your employees, especially at large companies. And so finding that way to be that feedback loop, that’s one of the places where you can add the most value, and have the most influence in the way that your employees experience their day-to-day work.

Nick Haap:

Absolutely.

Ashley Litzenberger:

Well, let’s dive into a couple of questions around data and analytics, which is the theme of the season. So, I know that you recently took ownership of the people analytics function. Tell me what that handoff looked like, and what were your first steps in getting started?

Nick Haap:

Well, I’ll admit that people analytics was something I was very interested in and taking under my umbrella. Being over talent management. I feel like we’ve got a lot of core people data. You think about performance management, which we call performance-enabled ML, since we’ve both rebranded and evolved our approach. Performance ratings, you’ve got trajectory ratings, or potential ratings, as most people refer to it, and nine-box placements, and in succession planning data. And then we’ve also got the continuous listening data. So, that just made sense to, let’s keep the people analytics housed underneath talent management because it all fits together, and we’re keeping it close to the data sources. 

It was originally kind of its own group nested under compensation, of all places, but after the original owner had left KeHE, we ended up absorbing that back in. So, I think it’s where it belongs, and we’re kind of reconsidering. How do we adjust the strategy to make sure that we are giving the organization the insights that are going to drive our business forward, and really help our leaders make better people decisions?

Ashley Litzenberger:

I think that makes a ton of sense. If you are owning performance management data, or you’ve got one-on-ones, check-ins, reviews, and then you’re also doing the continuous listening part, where you’re getting those annual and more frequent surveys from your employees, you are the source of all the data that the analytics team is then digging into. So, bringing those teams closer together, to make sure you’re getting consistent data points time over time, so you can measure progress so that you can actually work together when you’re building out whatever frameworks, or whatever surveys, or whatever templates you’re creating, creates a much tighter connection between those two, and ultimately can make the data so much more valuable. So, that’s really exciting. 

I’m curious, you mentioned that you’ve been shifting your mindset from talking about performance management to performance enablement. I know a lot of other HR leaders out there are having the same conversation. Can you tell me a little bit about what the shift in terms from performance management to performance enablement really signals to you and to your organization?

Nick Haap:

This is a bit of a longer story, because it’s part of my own personal evolution as I’ve been leading performance management for quite a while in my career. And I, of course, was introduced to it as a very traditional approach where you goal set, you have a midyear, perhaps, with an on-track/off-track rating, and you have the year-end rating. As I was starting to dig into this a little bit more, and conduct retrospectives and focus groups with internal team members to really understand what their perspective was around the performance management process. Was it accomplishing anything more than giving compensation, a rating that they could use to anchor their merit and bonus to? Or were people really getting a lot of value out of it? And the answer is probably what you would expect: People didn’t look forward to it. They felt like it took up a lot of their time to complete the tasks throughout the year, and then they didn’t get a lot out of it.

And so as I was researching some other approaches, or maybe what the latest thinking was around performance, I came across several influential thought leaders on this. But one that stood out to me was Marcus Buckingham and his experience, of course, with Gallup, and just thinking about strengths that people had and how to encourage folks to do better within their walls. Eventually produced this notion of what he referred to as this kind of StandOut program. And as you look at StandOut, he tried to explain that as we were trying to do with traditional performance management, we’re attempting to both measure performance and then activate talent, and we’re doing neither of those very well. 

And that was a light bulb moment for me, because I thought, “How am I really contributing value to the organization beyond giving ratings from my group over to compensation, when I could instead be figuring out ways to drive behaviors among leaders, and team members that would ultimately unlock their own potential and make them more effective at what they do.”

And so that’s what really set me down this path of transitioning from traditional performance bandwidth to what we call performance enablement, which again, is really geared towards unleashing individual potential. And how you do that is through regular conversations on the topics that matter most, the things that matter most, and making sure you and your leader are aligned on what the go-forward tasks are. So, that’s critical. And so what we ultimately want our team members to see these practices as being more of tools and habits that are going to help them succeed, things as they actually implement them and follow through on them, is going to improve their overall chances of success by the end of the year. Instead of an HR mandate that they have to go on and do this within this particular timeframe.

Ashley Litzenberger:

So, it sounds like performance management really kind of can boil down to just performance measurement or giving someone a grade, whereas what you’re looking at is how do I actually find out where someone is, and then use that information to benefit the employee and our organization by putting them into the right place, giving them the right guidance, and giving them the right information, and tools that they can use to grow in their career, and then provide increased value back into the organization as a result?

Nick Haap:

Yeah, I mean you’re ultimately, in these regular conversations, letting the employee know where they stand, and then determine, get alignment on what they need to do going forward, and just creating that action. It’s those actions around it. So, it’s pretty straightforward. There are four topics that we have consistently across each of what we call check-ins, and that’s just around the results so far, their objectives and key results for the upcoming quarter, and their development progress. We want to become a culture of continuous development, as well. And then any needs of that team member on behalf of the manager. So it creates an opening for team members to ask for things that they may not totally feel comfortable with, if they happen to need something from their manager.

Ashley Litzenberger:

That’s really interesting, creating that culture where you have this clear set of expectations about what the performance conversation or what the continuous conversation is going to be about. It does a lot of things for employees. It gives clarity about what the conversation is going to be, which relieves anxiety. It gives managers a clear template for what to follow and where to have a conversation, so they’re not making it up on the fly or having different conversations. And it creates this sense of psychological safety, because you know it’s OK to talk about those things in that conversation. It’s OK to share something with your manager, or it’s OK to provide growth and feedback to your employee if it’s positive, or if there’s also a little bit of where they need to work on things, as well. That, I think, is a really strong place of culture building where HR really gets to be in the leadership role. And when you’re able to do that, you’re actually able to create so much clarity, and just lightening the mental load for employees and for managers. So, I think that’s really great. 

I’m curious because what you’ve talked about here is, what are you doing to create consistent expectations and conversations for employees and managers? Flipping it back over to the HR team, when you’re working on supporting the HR team, based on these performance conversations, what kinds of key metrics are you focused on tracking, and how are they tied back to the business? What are you seeing in terms of, what are you looking for in terms of what’s happening at the performance level, and how does that tie to employee trends and business outcomes?

Nick Haap:

Yeah, great question. So, we’ve just started moving into these quarterly check-ins. So we’re on our second quarterly check-in that we’re just wrapping up now. A couple of metrics that we’re looking at is, of course, overall participation, meeting the team members going in there, providing some of the answers to those questions that I just mentioned, and then the managers going in and providing any supplementary details that they might want to talk about as part of the conversation. The way that we leverage those answers is more of an outline or a form or agenda for the conversation between their manager and a team member. 

And we have a way of tracking that within our performance system, those conversations taking place, but we also wonder how the quality of the conversations have been. And so within our current quarterly vibe, so the continuous listening survey that we send out, we’ve incorporated a question around, how valuable was that check-in conversation? And so far, it’s looking quite positive, with upwards of 90-plus percent of people finding it, or agreeing with the statement that it was valuable for them. We wanted to make sure that not only having the check-in conversation, but they understand the value of it, and they’re more willing to have it. And so that’s a way of us confirming that we’re on the right track with the way that we’ve trained our leaders to have the conversations, the guidance that we’re giving them, and then that the team members feel like they’re leaving with something of note that they can use going forward. 

Now, we’re going to layer onto that, of course, some correlations between their quarterly check-in participation and their overall performance at the end of the year. So, this’ll be more of a longitudinal thing, but we also want to look at how their favorability is overall in engagement. So, the favorability, if we think about the question that we ask, which is now that we’re doing this quarterly, how is your last 90 days? And they can rate it on a scale. And so for those people who are selecting either good, or pure goodness, and that’s more of our branding, that they are considered having more favorable perspective of their last 90 days. And so we would anticipate the individuals who are having those checking conversations, having a positive experience, are going to be more favorable overall. And so we can start to tease out a lot of these correlations and these relationships to show the importance of one thing on the other. 

So, the importance of having a check-in conversation on overall favorability, the quality of the conversation on overall favorability. And then longer term, I think the hypothesis, of course, would be that those people who are having regular check-in conversations, having quality check-in conversations, are going to be on average performing better than those that are not.

Ashley Litzenberger:

I think that’s really insightful that the answer is not that the numbers are correlating to negative responses, it’s that there’s an absence of data there. It’s the lack of participation that’s the bigger red flag. I almost even wonder if someone is responding to the vibe check-ins, and they’re negative, but the fact that they’re engaging is actually a healthier sign than someone who doesn’t even take the time to participate in the quarterly vibe or the engagement survey that you’re running. That’s really interesting. 

So, tell me a little bit more about the kinds of questions that leaders were asking that made you realize you needed better access to data or a better way to organize it. And I think one of the things you’re talking about is this quarterly vibe check-in, where you’re not just trying to get to quantity of performance reviews or conversations completed, but getting into quality.

Nick Haap:

So, I think it’s a matter of making it as easy as possible for leaders to find the information they’re looking for and alleviating the burden on our HR business partners. You can imagine, as an HR business partner, before we had a centralized home for people analytics, they were constantly getting questions about what’s my turnover rate, annualized turnover rate so far. And it really takes the HR business partner away from being a strategic partner to one of being administrative assistant, pulling data. 

Our intention was to help streamline this by getting the fanciest tool that we could find. And it is actually really fantastic because of how it integrates all of the data sources that we have, and we have several, to allow people to go in and look at kind of pre-populated dashboards, and then also modify those dashboards very easily to get some insights on short notice. So, a couple of things with that. As we use this platform, and we’re pulling in data sources from multiple places, now we have it all in one location where we can start looking at comparisons.

Ashley Litzenberger:

So, what are all the data sets that get pulled into there? I’m just very curious. It sounds like you’ve got engagement data, you’ve got conversations, what else is in there?

Nick Haap:

So, we have the engagement data. We have the performance data that’s coming across. We have a lot of the turnover data, promotion data. We have new-hire data, as well, in talent acquisition data coming from our—I always get this mixed up. I forget what they call the system that they use to track—

Ashley Litzenberger:

The ATS, applicant tracking system?

Nick Haap:

Applicant tracking system. Thank you for that. They utilize all this data together in one place, and then they can start making correlations and showing relationships between the different data sets. Let’s say, for instance, we could look at the team members that are joining for a specific location or a specific background, and we could start to see how their performance is trending. Maybe we start to see a particular profile top up around people with this background, from this college education, and this region tend to be performing higher. Or with engagement, of course, seeing the relationship between overall favorability, or maybe even the answers to specific engagement questions, and overall turnover. And so there’s some attrition models that are already built in that pull in a lot of these data points and can indicate the biggest drivers in overall turnover. That starts to get into the more advanced components.

But if we try to reverse-engineer this and ask a simple question, “What is it our leaders need?” Or maybe, “What do they need that they don’t know that they need?” We got to think about what’s driving the business. And so we have some scorecard metrics around people. Of course, it’s very standard. And then we want to keep the turnover low for our top talent. We want to keep turnover low for our warehouses, because we’ve got to make sure that we’re ready for our busy season. And then likewise, we want to make sure that our leaders are action planning against the results of their engagement data each quarter. 

So, those are going to be core elements to what they see in their dashboards. And then you start to think like, OK, what’s going to help supplement those, because they’re more lagging metrics. And so what are some of the leading indicators that we get to try and incorporate? So, if we talk about keeping the turnover rate low for our top talent, they want to show, OK, what is the favorability level coming out on our engagement survey for top talent? We want to make sure that, if it’s trending downward, we may need to address that before that group actually leaves. It’s just a key way of allowing our leaders to produce a self-service solution where they can go in and see these trends, and look at this data to make sure that they are aware of what might be coming down the road, and make valuable people decisions.

Ashley Litzenberger:

And have you ever had a moment where the data revealed something surprising, or counterintuitive, something you wouldn’t have spotted if you didn’t have the dashboards or you didn’t have all that data centralized?

Nick Haap:

Yeah, I know I keep leaning on the engagement data quite a bit, but it is because it’s so telling. We looked at action planning. Again, action planning is what our more senior-level leaders do after they get their vibe, or engagement, results. And for those team members who recognize the actions were actually being taken, they had a 36-percentage-point-higher level of favorability than those that didn’t recognize any actions being taken. So, I think that was just a really big flag for us that we need to make sure that team members recognize the actions are being taken. And we need to be closing the feedback loop with them, because it’s clearly related to favorability, as we would’ve anticipated. And so being able to see that kind of all in one place made it very easy.

Ashley Litzenberger:

That’s interesting. And I think what I really love about this conversation is that for so long, there’s been a focus on performance management conversations, or on goals, and OKRs data to show you how individuals are performing, how the company is progressing in terms of meeting strategic goals. But there’s been a little bit of quietness around engagement data, which I think is something people are sleeping on because you’re right, you can have qualitative data that tells you numbers, but if you don’t have that qualitative data that tells you how are people feeling, what is the impression of what’s happening, you’re missing a huge element or a huge part of the puzzle. It’s almost like taking something from 2D and moving it into 3D to really understand what’s happening.

Nick Haap:

It’s very true. So, if you think about an individual’s perspective, that’s how they feel, that’s their reality. And so we’ve got to make sure that we understand how we’re feeling instead of just, again, like you said, looking at the cold, hard numbers, because they don’t tell the full story.

Ashley Litzenberger:

One of the things that’s starting to come up really often when it comes to data and analytics is the role of AI in that process. So, are you starting to explore AI in your data analytics, within your teams, within the tools that you use? And what potential or concerns do you see around AI when it comes to people analytics?

Nick Haap:

All great questions. Yes, AI is the burgeoning technology that I think has kind of unlimited potential. So, a couple places that we started utilizing it. One is with an engagement survey platform. So, when we ask our leaders to go in and action plan, now when they’re within their dashboard and to look at the results, we have comment summaries. They don’t have to read through all of the comments. Instead, it creates comment summaries around five of the most important topics based upon the sentiment. So, that really streamlines things. And they even have an AI assistant. So, if you’re trying to cut to the chase, for lack of a better expression, you can go in and just say, “OK, what are two actions I could take to address the most pressing topic based upon the data?” And it will provide you with actions. 

So that way it makes it a lot easier. You have to do a little less investigative work. Now, I would of course encourage our leaders to spend a little bit more time with the information that’s being provided, but it’s better than nothing. And I think that’s the risk, of course, with AI is like, are we cheating, in a way, by not spending more time with the information and just assuming everything to face value? But we’ve got to see the silver lining here, and just say, if we get them engaged with the data, and we make it easier for them to use it, then that would ultimately be an improvement upon doing what we’ve done in the past, which is very limited. 

And so on the people analytics side, a kind of more robust system that incorporates all of our data sources, they are introducing the new solution where it’s tied into the social working tool of Teams, and you can just go into it, and ask it a question. It’s like, “What was my turnover rate over the last quarter for my high-performing team members?” And it would provide you an answer. And so that way you don’t have a need to go in and look at the dashboards, it’ll shoot out an answer for you. And then it kind of takes the place of what they were asking the HR business partner in the past. It saves them time from having to go in or maybe tailor a few of the dashboards that they’re looking for, and building their own, and just getting them the information they need at the fingertips a lot faster.

Ashley Litzenberger:

I often, I’m not in analytics specifically, I do more work in marketing and in content creation. And I often think about AI as being a really highly qualified graduate intern, or first- or second-year employee, in some respects, where it can deliver really solid information really quickly. And at some level, you can start by taking it at face value and accepting it, but before you hit send and roll out something really big, it’s always good to double-check or take a look. So oftentimes, you can get really quick responses to a simple question: “What is my attrition rate over the last two quarters?”

But then, when you’re starting to ask, what are some of the root causes, or what are some actions I can take, that’s when you still need a human to come in and take a look, and be like, “Ooh, does this recommendation work for desk workers versus non-desk workers?” Or “Does this recommendation work for my night-shift team versus my day-shift team?” And so starting to understand where those recommendations come into the practice of your own organization, where that human level of assessment is very helpful still.

Nick Haap:

Yeah. And I will say that it always has been “Pass the gut check.” You need somebody with a certain level of experience with the business to be able to provide that gut check. So, again, I had said earlier, well, let’s not take everything at face value. You’ve got to really dig in. If you get a response back from AI that really kind of makes you scratch your head a little bit, then you’re going to have to spend a little bit more time on the data that really uncovers where that’s coming from, if it makes sense. 

And then there’s qualitative information you get from talking to your team members. So, maybe it did uncover something that you weren’t anticipating, and you could validate that by talking to your team members or looking more closely at the data. But yeah, there’s a lot to be said by just taking the time to validate what’s being provided to you.

Ashley Litzenberger:

And with just the growth of AI within the workforce, there’s a lot of conversation around AI replacing jobs or taking over and replacing whole roles. Do you ever think AI will completely replace a data analytics team?

Nick Haap:

No, precisely the reason that I was mentioning earlier. And you got to have a human to be able to double-check the responses that AI is producing. And you need somebody, again, with enough experience and familiarity with the business to be able to say, “Yes, that’s accurate,” or “No, that doesn’t make sense. We got to figure out why it’s saying that,” and just check the AI. 

Now, could it shrink the team? Absolutely, I think that’s possible. I’ve started seeing examples of AI agents being built into the org hierarchy, so doing a lot more of the—I think the term that’s being used now, and I’ve really only heard this in the last few weeks, so it must be relatively recent, but the agentic AI, so agents being added in to the work that’s being done that’s more routine. So, you could train it up to do a lot of that kind of more manual, repeatable tasks that I think people will be happy to take off of their plate. And maybe allow them to do more of the strategic work. So, that’s the intention. 

So, I think ultimately it will be better, because it’ll save us a lot more time and effort and heartache when it comes to those high-demand, low-productivity tasks that we have to spend our time on. Only to just make sure that the information they’re giving is accurate, and then kind of move on, start thinking about the big picture. How can we have more of an impact overall on your organization within our function?

Ashley Litzenberger:

I think this is a very natural follow-up question. What skills do you think will be most important to your people workers, your humans, in your analytics teams as AI becomes more embedded in their everyday tools or even as agents within their org chart?

Nick Haap:

So, I think they need to know how to best interact with the agents and be very proficient in the prompts, in understanding how to code them, how to make that agent more effective at what it does. So, continue to train them, and then test it out, of course. But with the people analytics role, so as a human, or with the people analytics side of the business, we’ve got to make sure that we’re just kind on top of, what are those data sources that you want to be pulling out? Where are some opportunities for us to identify relationships that we haven’t identified before? And the AI can help us out with that.

So, we still have a level of creativity that I think AI does not have and probably will never have, because all it is just really scraping the history and the knowledge of employee experience and knowledge. So we have that level of creativity to start thinking about, OK, what are these relationships between people, between people in the world in the overall impact on the business that we can continue to guide both the AI on in the business eye to make sure that we are providing the best insights going forward.

Ashley Litzenberger:

Over the last few months, I’ve been thinking a lot about a parallel between the invention of the computer, and the AI coming into the workforce. And I really have been thinking a lot about the movie Hidden Figures, where you had people who were the computers who would do all of the mathematical equations to help get us into space. And then at some point, they brought in a computer, someone had to learn a whole new set of skills on, how do you actually work with a computer? How do you actually make it do the thing you want to do? Especially when we were talking about supercomputers. But at the end of the day, they still needed to understand the foundations of what the math equations were, how those things worked, so they could gut-check what the responses were that were coming out. 

And even today we use calculators. I grew up on the TI-89 calculator, going to all of my math classes with that. And I know that I use that for doing all of my mathematical equations, but I can still gut-check, “That doesn’t sound like it’s right, or something looks like it’s missing,” and I still know the underlying theory behind it. But you’re right, we have to start developing new skills. How do we interact with these new tools? How do we direct these new tools? And then, how do we use these new tools to allow us to get more creative, or to get to the next stage where we’re trying to problem-solve what we couldn’t before?

Nick Haap:

Absolutely.

Ashley Litzenberger:

Last question for you today. For someone who’s stepping into a people analytics leadership role for the first time, especially without a technical background, what advice would you give them?

Nick Haap:

So, if you think about people analytics, it can sound like a very nerdy profession, kind of like a developer, where you’re going in, you’re developing code in order to build something. But at the same time, too, you’re building something that ultimately, people are going to use, and it’s going to make their life hopefully easier and faster. 

With people analytics, you’re building insights for your leadership team to make better decisions overall. And ideally, that’s going to drive business results. It’s going to make sure that the right people get into the right roles at the right time, and that we’re much more efficient at the things that we do. And you’re kind of the precipice of that. So, instead of wandering in the forest, now you’re creating a path for people to follow, and giving them the guiding posts to make sure they’re heading in the right direction or taking the routes they need to take.

Ashley Litzenberger:

Something that I learned early on in my career, not working necessarily with data analytics, but I use it now when I work with my data analytics team all the time. When I was working with the product team, I had to learn how to not ask for what I thought was the answer. So, not “I need a bridge to cross this river,” but to say, “I need to get across this river with five trucks that are really big. Figure out what the right approach is. Is it a ferry, is it a bridge?” And let the engineers actually look, or in this case, the people analytics teams look at the resources that are available, the data that they have to back into what is the best way to get to the answer that you’re looking for or the insight that you’re looking for.

And that has a lot to do with just getting better about asking for what you actually are looking for as opposed to the thing you think the expected outcome is. So, instead of saying, “I need to know what the attrition rate is by X, Y, Z metric,” you’re actually asking for, “I need to understand what’s causing different groups of people to leave at the highest rates.” And then you might actually find something new and different. So, learning how to ask those questions was something that I’ve learned from working with product teams that I find has made the insights I get back from my data analytics teams so much more valuable.

Nick Haap:

Yeah. In the way that we’re thinking about it here, and I appreciate you bringing that up, is from a lean perspective, because we’re trying to introduce lean concepts within KeHE, is like going back and asking the question, “What’s the problem we’re trying to solve?” And so that helps people understand, to your example, we need to cross the river, and we have to do it with this many things, and we’re limited in this respect. So, I think kind of painting the picture of what the situation is and being very clear on the root cause of the problem that we’re trying to address allows us to attack it more effectively.

Ashley Litzenberger:

I think that’s exactly it. So, that’s really interesting. Thank you, Nick. This was a really great conversation.

Nick Haap:

Thank you. I appreciate you having me.

Ashley Litzenberger:

As we wrap up today’s conversation with Nick, let’s think about a few ideas you can take with you today. First, shifting your mindset from performance management to performance enablement can change the way employees experience feedback. By creating consistent structured check-ins, you’re not just tracking performance, you’re giving people the clarity and support they need to grow. 

Second, centralizing your people analytics can make it easier for leaders to connect the dots between engagement, retention, and performance. Nick showed how putting that data in one place empowers leaders to make timely and informed decisions that directly influence culture and outcomes. 

Third, while AI is making analytics faster and more accessible, human judgment still matters. The best insights come when technology and experience work together to validate findings and to shape action. This ensures that data leads to meaningful, people-centered results. 

And finally, Nick’s commitment to creating and acting on feedback loops is a reminder that when HR brings together listening, enablement, and analytics, it doesn’t just create a better employee experience. It also equips leaders to build stronger, more resilient organizations. 

Be sure to stay tuned for our next episode of the People Fundamentals podcast. Subscribe to us on Apple Podcasts, Spotify, or YouTube Music. And if you like what you hear, share us with your friends and colleagues. We’ll see you again soon.