What's Fundamentally Broken about Employee Surveys and What to do About It, with Jake Mealy

In this podcast episode, Dr. Jonathan H. Westover talks with Jake Mealy about What's fundamentally broken about employee surveys and what to do about it. Jake Mealy is a data analyst and storyteller whose experience spans biotech, sales, marketing, HR tech and people analytics. He holds a PhD from Trinity College Dublin and previously led data teams at Indeed and Analytic Partners. As Welliba's Chief Data Solutions Officer he pioneers AI-powered people analytics solutions. The insights delivered by this technology reveal the influence that employee experience has on hard business performance metrics like revenue and shareholder return. See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

• 0:03Speaker 00

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• 0:35Speaker 00

  Jake Mealy, welcome to the conversation today.

• 0:37Speaker 01

  Thanks for having me, John. Yeah, excited to be here.

• 0:39Speaker 00

  It is a real pleasure to be with you. You're joining us from Dublin. I'm south of Salt Lake City in Utah. Today, we're going to be talking about employee surveys, employee feedback, and really what's broken with the model with that kind of a system, and how we can break it down, rethink it, and do it in a much more effective way. I think everyone's experienced it. Everyone's experienced, you know, the annual engagement survey or employee survey. I think people have experienced, you know, perhaps pulse surveys, or, you know, various approaches to doing these sorts of things, to varying degrees of effectiveness, often to low degrees of effectiveness. Yeah, so we're going to unpack this. We're going to

• 1:21Speaker 00

  explore this together. As we get started, I wanted to share Jake's bio with everybody. Jake Mealy is a data analyst and storyteller who's experienced bands, biotech, sales, marketing, HR tech, and people analytics. He holds a PhD from Trinity College Dublin, and previously led data teams at Indeed and Analytic Partners. As well of as Chief Data Solutions Officer, he pioneers AI-powered people analytics solutions. The insights delivered by his technology reveal the influence that employee experience has on hard business performance metrics like revenue and shareholder return, and really just such a tremendous background

• 2:01Speaker 00

  insights into analytics and how that applies to employee experience in the workplace. A pleasure to have you, Jake. Anything you'd like to add? By way of your own background or personal context before we dive on it.

• 2:12Speaker 01

  Yeah, I mean, I guess it's been a bit of a diverse sort of career journey for me so far as as your your generous intro kind of kind of highlighted there. But I suppose the arc of it has been bending more towards people analytics, particularly recently. And certainly, when I think back to my previous role in in Indeed, where we were really trying to, you know, help clients understand, you know, their hiring strategies and and who their talent competitors were. I I I think back to that now and and some of the insights that we're uncovering now at at Wellabah in terms of the the why behind talent movement or the the why behind employee sentiment. Why do employees feel the way they do? How are they responding to that feeling? And what impact does that have on businesses?

• 2:57Speaker 01

  And I think back and I'm like, if only I knew then what I knew, what I know now, you know, the the kind of of analytics and the kind of tactical recommendations we could have given to clients in Indeed would have been so much more powerful. And that's only sort of three, four years ago. And so just the the speed at which this field, like a lot of related analytics fields is is changing is just really kind of.

• 3:23Speaker 01

  Jaw dropping, it's blink and you miss it kind of. So, yeah, I was just kind of reflecting on that before before we jumped on the call. And yeah, I I I just think it's it's it's fascinating and something that that people probably really need to to to pay attention to to to to stay up to date.

• 3:38Speaker 00

  Yeah, well, that's super interesting, especially given, I think, the state of like employer surveys that are out there. Because I don't see them keeping any sort of pace with these shifts, right? Because like when you think about the the annual employer survey, like the engagement survey or the satisfaction survey, has that changed for most companies much in the last decade, do you think?

• 4:02Speaker 01

  No, yeah, it it. I mean, I I think I think people, you know, sort of gathering techniques and and analytic techniques might have changed. But fundamentally, you're asking employees what they think. And that probably.

• 4:16Speaker 01

  Will will for some time continue to be an important thing to do. Having a two-way dialogue between leadership and employees is important. But what I would say is that that it leaves a lot of stones unturned. It gives you a very incomplete picture of your, the human capital in your business as a whole. So what do I mean by that? Well, first of all, you know, you're engaging in a dialogue, right? You're asking questions, right? So that naturally creates an expectation, right? And so that's, that's why when in Wellaba, we would, we would term that type of employee analytics or people analytics as active listening. You know, you're, you're, you're sending a signal to the employees that you want their feedback.

• 4:59Speaker 01

  And so that creates an expectation that actions will happen based on that feedback, which may or may not be possible or, or useful for you as a business leader. And then, and then secondarily, and, and in my opinion, sort of even more importantly, you're only ever looking at your own organization's results in the context of your own organization. Okay, your survey provider might give you a benchmark or some sort of industry average number that, you know, that you can kind of like, you know, compare yourself against. But do you really know how you compare against your closest talent competitor? Do you even know who your closest talent competitor is? And if you do, what would be that? And this is why, you know, I was, I was saying that about, about my previous work in Indeed.

• 5:42Speaker 01

  You know, let's say I'm a, a, a business leader in a, in a care home, you know, in rural England. Is my biggest talent competitor the care home in the next county over? Or is it the Amazon warehouse that's just opened up down the road? And no matter which it is, and I, I think I'm losing talent to one of these places. How do I defend against that? Why is that happening? It's the why that's, that's, that's really, really important. And that's, that's, that's fundamentally where the survey system is going to let you down. Because you can survey your own employees all you want, but you'll never be able to survey the employees in that Amazon warehouse and find out what's going on over there and, and compare apples to apples. And that's really where, where this kind of work that we're doing now totally changes that game.

• 6:27Speaker 01

  You know, we're, we're, we're looking at totally different data sources, publicly accessible at vast, vast scale. And so now all of a sudden, it's possible to rack these organizations up side by side. And that's, that's why I say that the survey picture is incomplete, because it's, it's never going to give you that context of the wider ecosystem that you're, that you're operating in.

• 6:47Speaker 00

  Yeah, and so to just recap a little bit what I'm hearing. So always important to to understand how your employees are thinking, feeling, and to have kind of that dialogue piece where if they give you feedback, they feel like they're being heard and that that's going to have some sort of impact and that it might influence your decision making and that you have some some way to communicate back to them, like what how it's influencing your decisions. Like, that's kind of the bread and butter of like what these employee surveys have been, like engagement surveys or whatnot. And in organizations, to varying degrees, have been successful at doing that. In my experience, often not very successful, and and especially with that feedback piece and communicating back to like how it's been used, like, most organizations tend to be

• 7:32Speaker 00

  pretty terrible at that, in my experience, but but at least there's that possibility and at least, you know, there's been that that intent, right? But so there's still that value, there's still that value in doing that component. But but what's missing is the contextualization, the the the ability to see how your talent picture fits within the broader talent picture of your surrounding area, your competitors, and not even just your direct competitors, not just, you know, like, like you were saying, the other nursing homes, but anyone who might be competing for your talent, right? So that's awesome. That's that sounds super intriguing. Yeah, tell us more, like, how do you go about doing that with these public data sources?

• 8:14Speaker 01

  Yeah, right. So this is really only being sort of possible. I mean, people have been online talking about their employment since the Internet was created, right? So this data isn't new, but the its accessibility is what's changed. And really, we've needed AI to to help us kind of get those go-go gadget arms and get out there into the Internet and gather all this together into into one usable usable space. So it's really only been possible for the last two, maybe three years tops. And when we say publicly available data, what what do we mean? I mean, we mean the obvious places, obvious, you know, sort of Glassdoor reviews, Indeed reviews, you know, these sort of dedicated platforms, and their local equivalents.

• 8:56Speaker 01

  For example, open work in Japan, you know, these places where people purposefully go online to review their their their employment. But the real power of the the AI and the L L M and systems that we're able to build now is that they can read and understand a lot more free form and type information. So think of your Reddit threads, think of your LinkedIn posts, think of of professional networks or even industry-specific professional networks where there is this like really nuanced, interesting discussion happening all the time. And as employees compare notes, you know, discuss what it's like to work where they where where they work. And and so that's the the they're the kind of sources that we're able to to draw together now.

• 9:41Speaker 01

  And and because it's it's it's publicly available, you know, there's and it's it's virtually instantaneous, you know, you you you compare that compare an analysis and using this this kind of data. You know, our systems can run up a a a two-company comparison in a couple of hours, probably. And whereas, you know, a surveying cycle is going to take you six weeks, two months easily, you know, to to to kind of get through. So so the kind of insights are much more instantaneous, they're much more readily available, they put things in context like we discussed. And it's it's it's all publicly available, so there's no data privacy, infosec kind of kind of issues. And all of this information is is is sitting out there.

• 10:21Speaker 01

  And so it's really just about, it's coming down to now which which which companies are are best at at sort of kind of realizing this and and and folding it into their people analytics strategy. And the last thing, and and from a data storytelling perspective, the kind of exciting thing I I feel about this as well is we've spoken a little bit so far about, you know, the tactical use case, you know, from a talent defense, you know, people people investment type strategy, how an individual company might use this information. But what's really exciting as well is we can do it at a much larger scale, right? So you can start to ask really interesting questions, like if we measured, you know, a particular cohort of companies, say, for example, the S and P five hundred, which we have done. And what are the particular aspects of

• 11:06Speaker 01

  Employee experience that connect with business performance, right? Because now we can line all these companies up and measure them in exactly the same way against the same model. And so we can ask these really interesting exam questions now. And this is what we're starting to to see is these really firm connections between employee sentiment, employee experience, and the actual financial performance of these businesses.

• 11:27Speaker 00

  Super fascinating. And and you alluded to like the power of of AI to to help you to essentially capture all of this, right? With all this online data, um, which may, I mean, it certainly could have been possible, but it would have been way more time intensive um to to have kind of tried to do this in uh previous years. Um, so now it just makes it far more possible. I have to ask, because certainly the the the practicality of this kind of data and like the usefulness as a product to organizations is huge. Um, do you leverage this like for like in a more of an academic sense as well? Are you using this for like academic papers also?

• 12:08Speaker 01

  Yeah, so so so we are producing um research and business white papers, right? So it's kind of like there's there's there's sort of two parallel uh uh research tracks, you know? So in terms of of of proving its efficacy, we, you know, we would have, our team would have published uh research papers validating the results that we get from the public data against um a cohort of survey delivered data. And so we see this really nice correlation there, um, which is important, right? Because it's, you know, people, it's a natural question people will ask is, oh, does the, does the data not skew negative on the internet? For example, um, and by and large, actually, that's that's not what we see. We see these really, really strong correlations between uh what the the signal that we're picking up from the public data

• 12:52Speaker 01

  and say, for example, you know, employee net promoter score um for a for a given cohort of of companies, which would be based on survey results. Um, so so that kind of, that's driving that sort of academic research. And of course, we're always kind of working on on on validated scoring models and psychometric models as well. That's that's formed a big part of the the the the basic core research in in Wellaba. But then on the other side, we've got, we've got these really interesting business analytics white papers. Um, you know, which which we're able to sort of use this technology now as as the research tool. You know, the the the technology is both a research goal in itself and also a tool to do further research. And this is where my team, me and my, me and my team have been doing a lot of work. So, you know, I mentioned the S and P five hundred.

• 13:36Speaker 01

  So we set out to measure, measure five, those, those five hundred companies at the end of, of twenty twenty five in terms of their employee experience. And very, very simply, just stack rank them, the happiest companies at the top, the, you know, the, the unhappiest companies at the bottom. Cut off the top twenty percent, said, these are our, these are our happy performers, these are the, the, the, the, the top EX companies. And then we looked at their total shareholder returns over the past five years. So that's a combination of share price growth and, and, and shareholder dividends. So a really strong financial metric. And we saw this really clear performance gap, those, those companies with the high EX scores are outperforming the market by five percent. So there's this really, you know, validated connection now between.

• 14:19Speaker 01

  And the, the sentiment and the, the, within these workforces and how the businesses ultimately, ultimately perform. And so that's been really exciting to, to, to kind of use this technology to help answer some of those kind of questions as, as, as well as researching the, the technology itself.

• 14:34Speaker 00

  Super fascinating. Um, so you have like a, just a ginormous number, it's like, like a hundred and fifty thousand websites, twenty five million data points. Um, you, you've already pointed to, you know, a couple of like the headline types of findings. Are, are there any others that you would point to, you know, from a high level of like some, some of the major things that you are pulling from some of these analyses?

• 14:58Speaker 01

  Yeah, so I mean, we're still kind of, you kind of, you mentioned a few of the numbers there, we're still kind of unpacking the data set. We like, we've, we've published a white paper based on, on our findings so far. But there's so much detail and nuance and, and richness in there that, that, that we're still unpacking it. Uh, what I would say to your, to your listeners is, is if you go to our website, uh, on wellabout.ai. We've made the full data set publicly available and interactive. So people can get on there, they can kind of, they can throw up the, you know, they can, they can compare, say, you know, Netflix versus Disney, for example, you know? And they can kind of start to unpack what the different employee experience is like in those two companies. Compare them side by side and also look at things at a, at a wider scale.

• 15:40Speaker 01

  So, yeah, I mean, I already mentioned the, the big headline figure of, you know, there's this strong connection between employee experience. And and business performance, and I think that's going to become more and more important. As as as time goes on. But but then kind of taking a step into the data and seeing, okay, well, what are the individual factors? You know, employee experience is a broad term, lots of different aspects. You know, go into contributing to how people feel about where they work, you know, their managers, their their colleagues, their rewards, their compensation, their flexible working policy, like all of these different aspects. And it's been really striking to see this very, very strong theme carrying through the entire data set, which is this this this really positive sentiment around people's human to human interactions.

• 16:25Speaker 01

  So this is their interactions with their colleagues and with their direct managers. And actually, that finding goes beyond even the S and P five hundred. We've done similar analyses in the Nikkei two two five in Japan. We've looked at the Euro next, you know, top one hundred big cap companies in in Europe, FTSE one hundred. This comes up again and again and again, as as a as a top positive factor, right? And that that people, the the aspect of their employment that they enjoy the most is is their interactions, their daily interactions with their with their human colleagues. So to really, and I say human specifically there, right? Because we're having this debate now about how, you know, the the workplace of the future, combination of humans, agents, what's all that going to look like? So really important finding there.

• 17:08Speaker 01

  And and a sort of a word of warning as well, right? Because even we see this as being a positive factor, even in companies where the overall experience is negative. So even where where employees are broadly speaking unhappy, the one bright spot spark or the one bright spot in their

• 17:27Speaker 01

  in their experience tends to be their interactions with their colleagues. And so this is where it goes all the way back to what we were talking about at the start, right? Which is what are the limitations of your survey? So if you're if you're running your survey every year and you keep getting this, these, these, these results saying, oh, well, we're doing, we're getting great scores in terms of people's experience with their managers, their team dynamics, you know, the individual team culture seems really strong. And you're like, by all means, you know, take a moment to celebrate that. That's obviously better to get good scores than that than bad scores. But what this research is showing is that the chances are, you know, your competitors are getting similar scores, you know, that this is what people enjoy about going to work. And so that's not a performance differentiator. That's table stakes. Like, everybody gets that.

• 18:09Speaker 01

  And and so really, like, if you wanna, if you wanna make the difference, if you wanna jump from one level to another. You, well, the phrase we're we're using is you need to start looking at fixing the floor rather than aiming at the ceiling. What are your low scores? What's going wrong? And like, those are the things, the companies that address those are the ones that we're seeing getting those performance gains in in this data.

• 18:29Speaker 00

  Yeah, super interesting, because I see companies pointing to that all the time. And that's my first kind of reaction is like, okay, great. So what? I was actually at a dinner last week with someone and they were pointing to like their employee engagement score. And it was like, it was crazy. Like, it was crazy high. It was like ninety eight percent or something. I'm like, how how was your employee engagement score like ninety eight percent? And and they kind of laughed it off. And they're like, well, it's easy. If if they don't like it here, we just get rid of them.

• 18:56Speaker 01

  Self-selection bias. Yeah, exactly. Yeah, yeah.

• 18:58Speaker 00

  Like, well, that's that's one way to do it.

• 19:01Speaker 01

  Absolutely. I mean, I mean, a company with one employee presumably has a one hundred percent engagement score, right? So, you know, that's the that's the natural endpoint. Yeah.

• 19:09Speaker 00

  Yeah. Uh, yeah. So so the the employee experience, uh, dynamic, being able to to to look at it and how it changes over time in comparison to all these other organizations using this public data. I think it's super fascinating. Uh, and the fact that you have, you know, the data set publicly available that other people can can dig into it, I think, is also equally equally awesome. You know, for for anyone to dig in, I, you know, that's something I think I personally am going to go check it out and go go dig into it, because I just think that sounds really cool. What what do you think? Like, anyone who's listening, who's a people manager, an HR person, or a senior executive, anyone who's listening to this and they're like, oh,

• 19:53Speaker 00

  maybe the way we've been doing it all along isn't sufficient anymore, you know, like, what what can they do? What's actionable? You know, for them to take away from this conversation today, what are the like next steps?

• 20:04Speaker 01

  Uh, yes, I think it depends a little bit on which persona specifically of the little list you had there. You're you're talking about, um, you know, for for for C suite, you know, for sort of executive level CEOs, CFOs. I I'm watching with real interest to see when this type of data becomes a standard part of earnings calls. Cause I think analysts are going to start asking about it, especially as this connection, like it's not just our research. You know, World Economic Forum published similar similar research, um, the end of last year as well. Um, so I think this is just becoming, and it's it's also intuitive, right? Like, anyone who's worked in a in a high performing organization with, you know, just kind of under like feels that this is true, right? That that, um, you know, motivated, happy employees are probably going to produce better business outcomes.

• 20:50Speaker 01

  So if I was an analyst, you know, maybe picking my portfolio for the coming quarters, like this would be, this would be definitely going into my my thinking. Right? It's like, okay, tell me what your current employee experience score is or your employee's sentiment is. How does that compare to your closest competitors? And how do you think it's going to impact your your your growth? Or or our returns over the coming quarter, two quarters, three quarters? And the first time a CEO gets that question in earnest and doesn't have an answer ready, I think it's going to be like quite interesting. Um, and so, you know, it it that that hopefully that will result in in in CEOs going to their

• 21:31Speaker 01

  or CFOs going to their people analytics function or their HR function and banging the door down and saying, hang on, we have to understand this properly. And then connect it to to what we're doing. So, um, yeah, so so so so I think, you know, from a CEO CFO CFO perspective, it's really about about starting to think about that connection. You know, using it as a forward facing metric, you know, are are it's it's it it should be a a fundamental business performance metric. The same way as cost of goods or, you know, um, cost of capital capital is, and I would expect it to become that. I think if you're a HR leader, um, you you probably have a, you're already aware of all of this, right? So you're you're and you've you already would have would have would have been. Feeling it. So there it's more about asking like coming up with a good exam question.

• 22:14Speaker 01

  You know, what is it that you that you think is true about your organization? What do you think would make the biggest, you know, point of improvement? What do you need budget for? You know, like I said, fixing the floor. And then and then maybe having a look at this type of data as a way of unlocking that budget from your from your your colleagues in the in the C suite. And by by being able to point to these things and saying, this makes a difference. This makes a tangible difference to the performance of our business. These are the of the three things. These are the three things that we need to fix. Not only to improve the motivation and productivity of our own workforce, but to defend against talent drain to our nearest competitors and potentially to to to target the kind of talent that we need to to to future proof the company.

• 22:57Speaker 01

  And so you can just be having way more impactful and punchier conversations when you've got these kind of numbers and this kind of evidence, you know, on your side. So I think that's really the place to start is the exam question. And but then, but yeah, this this this this type of of methodology is is going to become standard practice pretty quickly, I think. So so people should should be paying attention. Yeah.

• 23:20Speaker 00

  Yeah, absolutely. Well, Jake, this has just been a super interesting and eye opening conversation with you. I really appreciate you taking the time to unpack this with us and to share your insights with us today. As we wrap things up, I just wanted to give you a chance to share with the audience how they can connect with you, find out more about your work, your team, and then give us a final word for today.

• 23:40Speaker 01

  Yeah, well, thank you, John. It's been it's been a pleasure to to talk to you today. And so, yeah, I encourage people to, obviously, if they want to connect on on LinkedIn, always always there to to connect and to discuss. And I think, you know, the the first port of call for people particularly to understand more about this research and explore the data themselves would be our website, welliba.ai. So that's W E L L I B A dot A I. And that would be a good place to to to start. And and I think, yeah, a a final word is maybe not to like I I take an optimistic view of this. I think this is empowering, this kind of analysis and insight, because it's easy to get, it's empowering. So definitely the the take on message is not to be afraid of this embrace it.

• 24:23Speaker 01

  It's a it's it's really unlocking a whole new level of analytics and understanding, which is good for everybody. It's good for businesses and it's good for employees.

• 24:31Speaker 00

  Yeah, I absolutely agree. I think it's awesome. Thank you, Jake. It's been a real pleasure. I encourage the audience to reach out, get connected, find out more about what Jake and his team can do for you. Check out the website, check out the data, all just awesome stuff. And as always, I hope everyone can stay healthy and safe. They can find meaning and purpose at work each and every day, and I hope you all have a great week.

• 24:55Speaker 00

  Thanks for joining us for this episode of the podcast. We hope you stay healthy and safe and please join us again soon.