Jeff Higgins Live on Shally's Alley

All right, party people, how's it going? You are live on Shally's Alley. I believe this is the last Shally's Alley of 2023, and man, I cannot wait for this year to just be done. I couldn't think of a better way to wrap the year up than with one of the deepest thinking minds in HR analytics, workforce planning. I mean, we're talking about literally wrote the book. Actually, how many books did you write?

Just one book, but lots and lots of articles.

But the textbook that everybody uses, right? The playbook that everybody uses. So yeah, so Jeff Higgins is here with me. As our guest. He comes from a long line of a really interesting background, actually, believe it or not. Former CFO, recovering CFO, I guess, who turned into HR, you know, full speed and full steam ahead, went into an executive HR function. And then some years back, 15 years or so, started something that you might have heard of, called the Human Capital Management Institute, or for short, HCMI. And if you're looking for the website, hcmi.co, I'll drop that into the video here in a little bit. But so here's essentially an accountant, finance, former officer with an MBA from Marshall who has spent a lot of his time looking at data and really understands workforce planning, human capital reporting, disclosure. So I wanted to talk with Jeff about basically what's going to happen next year, what the crystal ball has to offer, and I thought that would be an excellent way to wrap up this year. So without all— without further ado, I'd like to introduce you guys to Jeff Higgins. From hcmi.co. Jeff, what brings you into HR? I mean, there's got to be an origin story there, right? You and I met when we used to both be at the ISO TC, the, the technical committee for HR, and you were on the workforce planning, workforce analytics side. I was in the talent acquisition side, but our committees sometimes overlapped. So we had bumped into each other, but it wasn't until HR Tech that we really got to have a tête-à-tête. And I was blown away with the things that you were talking about your company does, like including certification and everything. But really, how did you— I understand why you left being a CFO. I get that. But why come into HR?

Yeah, yeah, not the typical origin story for, you know, hey, finance person seeks asylum in HR. So I jokingly say I'm paying for my sins and evil deeds of the past as a CFO. I kind of wish I knew back then what I know now about linkage because I knew how to improve workforce productivity and get more out of the people. Just do a layoff or reduction in force and that'll cut costs and save us money and profits will go up. Well, unless we cut the wrong people and then we lose customers, projects don't move forward, other people that we didn't want to leave leave because you let go somebody they new or respected. So, all kinds of things that I didn't really think about or take into consideration in my finance life. I actually quit as a finance person. I was between jobs as a CFO and got an offer to go interview for a publicly traded financial services company in HR to run their compensation in this new thing called HR metrics.

And I said, "Rich, so, compensation, so, CFO, compensation. Okay. All right." They're like, "All right, he knows about money." some numbers. Accounting money. Yeah, gotcha.

But I said, I don't speak HR. I said, you know, HR, because I used to be the one who would go and take money from HR's budget, not put more in. And they said, well, can you present HR data a little more like financial statements? Because management's all MBAs and CPAs. And they said, we don't speak HR either. So we need somebody who can translate this stuff for us. And they sold me really well. I gave it a shot. And 6 months in, discovered my true passion in life. All my finance colleagues thought I was crazy, but I'm so glad that it happened. And so I've been doing it there as a practitioner. And then, yeah, for almost 15 years, I've been leading HCMI, helping organizations basically use data to make smarter decisions about their workforce.

You know, so that's what really kind of resonated with me when we had a chance to sit down face-to-face. I had a very similar transformation about 7 or 8 years ago, where I was working at a very large company. I really liked working there. It was great people, great organization. And they took a chance on, on me in kind of letting me dip my toe into this whole, you know, workforce analytics and workforce planning. Because I come from my industry where I originally started was in sourcing, but really talent sourcing has a lot to do with, with technical stuff. Kind of like, kind of like being a CFO has a lot to do with things that are not accounting, right? Sourcing has a lot to do with things that are, that are not recruiting. There's technology, there's analytics, there's competitive intelligence. And so they needed somebody to kind of run some reports, and I, and I was like, sure, I'll learn it. And before you know it, I know Google Script, I know Python, I know R. I'm doing, you know, I'm pulling in all these complicated spreadsheets and writing scripts, right? And I'm actually the only person in the entire organization that's doing— here's the, here's the tieback to you— that's actually doing workforce planning. Everybody else was doing reporting, right? And I was the one that was doing workforce planning. And I never really understood— it was always lumped together, right? Workforce planning and analytics and reporting was kind of— but the entire day, it was like a 7-person team that was the official workforce planning team. What they did was analytics and reporting. And so when you and I spoke and you're like, no, no, no, this is this, that is that. Can you share with the audience really what the difference is, what workforce planning is, and how some people do it but don't really do it?

Wow. Yeah, that's a, that's a great, great question. So analytics, by the way, feeds into workforce planning. Of course, if you have to have analytics, if you've done a lot of analytics, you've got the data, you've got, you You've got the trends. You've got some predictions. You've got some correlations. That's how I started.

That's exactly how I started.

Yeah, it's sort of like, well, what next? Well, you put that into a plan and you come up with it. But the essence of workforce planning is looking forward, not back. So, you're looking forward to say, okay, what's likely? Because we don't know, right? What's likely to happen in the future? You can call it a what-if. You can call it a scenario. You can call it a lot of things. But that's basically it. Say, Okay, if nothing changes and next year is exactly like this year, well, that's a scenario. That's basically the default scenario. Everything will be next year like it was this year. Okay. What does that mean for us? Let's take our analytics and make an aggregate projection. And I would argue workforce planning on the hierarchy of complexity and advanced utilization of data metrics is the penultimate. Because you put it all into a plan and the idea is the plan based on the scenario or the assumptions you make is actionable around what you're going to, you know, to your point on sourcing and recruiting. Who are we going to hire? Where are we going to get them? How much are we going to pay?

Are they even there?

Are they, yeah, are we going to the right places or the wrong places? Do we build versus buy talent? Are we over- or underpaying? Are we, you know, what are our root drivers of, you know, better productivity, employee engagement, performance, by the way, it's leadership. But you got to have the data to, to basically pinpoint that.

So it starts with the data. And a lot of companies have data. But let me tell you, Jeff, and I'm sure you've seen this a lot more, I showed you kind of my deck of spreadsheets. There are companies that have the data, but the data itself is incongruent, and it's a complete mess. So the first step is like cleaning the data, data hygiene, right, organizing that. Then the second step is Putting the data together into an analysis that starts to tell you something. Now, what it tells you— here's where I kind of, I admittedly, you know, came clean to you and said, here's what I'm hitting. I was able to get the data and massage it and make it, you know, reportable and everything. But where I hit the brick wall was, um, I knew what the data was telling me and I was putting it into pictures, but nobody was buying it, not that they had to. It was just, it wasn't, they were like, uh-huh, yep, yep, next. And you know, like, it just, so that translates. So now you have the analysis and it still doesn't go anywhere, right? And that's only the data analytics part of it, which is making the recommendations. You're talking about actually planning. So taking that analysis with the actionable intel and doing something about it or putting into play something that's going to get done about it, right?

Right, right. And it's a, it's a strategy. What's our workforce and talent strategy that we're going to execute on? And of course, everybody can talk about that at a super high level. But to get granular, how are we going to get more people to stay? How are we going to do a better job of growing and building our own talent? Managers always say, "Oh yeah, we grow our own." And like, well, what percentage of your managers do you fill internally? "Oh, we don't know." OK. Eh. So, it's taking that data and putting it into an actionable plan. The other part that, and this is, this is a funny thing, I actually have written multiple articles on this, is building a business case. One of the things finance people are really good at making a business case. Because by the way, I used to do, I used to support M&A, new product investigations, you know, big, are we going to build a new $500 million, you know, manufacturing facility or not? I would do a lot of the analysis. On that. And then we present it to management. And you know what? We had no idea what was going to happen. So, you know what we did? We did scenarios. For like an M&A, we might do 100 scenarios. We throw 97 away. We keep a best case, a worst case, and a likely case. We present that to management. And that's how they go, "Oh, best case. We love that. You know, hope that happens. Worst case. Ooh, is that good enough? Can we, you know, can we make that work?" And then the most likely case, that's what they expect. And from that, you know, kind of the high, the low, and the middle, That's how they make billion-dollar investment decisions. And if they don't like any of the numbers, you say, well, what assumptions would you like? We'll go run another scenario for you. So, but part of that was a business case that had data, visuals, compelling questions, and we had to stoke the magical risk and fear factor. You know, if we do nothing, this is never going to fix itself. We're not going to be ready or happen or not happen. This will happen. Yeah. And so, hitting those components with a forecast that goes out there and actually maybe multiple. Like here's the best case. I tell most folks for workforce planning, just do two. Do a best case, which is not, hey, you know, all of a sudden somebody stops by and drops $1 billion on our front doorstep. Or worst case, oh, an asteroid hits the Earth, wipes out all— No, no, no. Realistic. What if growth picks up next year? What if growth stays the same or drops a little bit? Do two very realistic scenarios and show the differences between them because that educates management. Management, they don't, they tend not to admit what they don't know. But if you show, if you show them these differences, they can often be like, "Oh, that's really insightful. Can you do this and this?" You could make a few tweaks. Boom! They're ready to actually action the stuff that you put together and spend all that time on.

So I've heard this, this is, this is kind of a probably an old trope. I've had a few mentors in the industry. That have— I've been fortunate that have taken me under their wing and, you know, the former CFOs and CHROs that have talked to me about what's realistic and what's not realistic. Does it still stand true that workforce planning and workforce predictions can go as far as maybe 6 months, but anything beyond that is absolutely just make-believe fairy tales? Like, is it— is that— is that still okay? So that, that was what I was, I was brought up on, was that you can go 6 months out with some degree of accuracy, but anything beyond 6 months, it's like gambling. Um, and I, I always wondered, I mean, we have— we, we have— especially if a company's been around for more than a few years, if you have 10 years of data, there's been recessions before. So we, we, we know what things look like. So I always wondered if that was really true or not. What's your, what do you say?

I would take the opposite. I would say there's a tendency in workforce planning. And by the way, I like to poke at workforce planning, say 95% of the organizations that do workforce planning never actually complete a workforce plan. So they have a strategic plan, they have an operational plan, you know, they have a financial plan. They don't have a people plan for their most valuable asset. Oops. But it's not, and the problem is it's hard, right? If it was easy, everyone would have it.

It's hard. There's a lot of uncertainty, right?

There's a lot of it, and everyone hates uncertainty. Nobody wants to make a prediction unless they know it's going to be right. But guess what? All predictions are wrong. When I use Google Maps to go from point A to point B, I actually make— I make a game out of it. I have Google— it's going to give me a prediction. You know what? It's usually wrong. And they've got all this data on traffic. It's, you know, if it's not live, it's close, and they're adjusting.

This is what you're saying is Google Maps says it's going to be 27 minutes, you're giving yourself 20 to 30. Because you—

it's going to be, it's going to be a little more, it's going to be a little less. Sometimes it gets it egregiously long. My favorite, my favorite example is it once told me to get off a freeway, uh, just before I crossed the, the Bay Bridge to go from San Francisco to Oakland because traffic was really bad on the freeway. And it got me off the freeway right near, uh, San Francisco Giants Stadium just as the game was getting out. Guess what happened? I was stuck on the surface street for 2 hours.

True tough reality.

Oops.

Yeah. So, you know what the other thing happens as well, which probably is similar in analytics, is Google predicted that there was going to be a lot of traffic, so they told everybody to exit the highway. So now everybody exited the highway and now the traffic went that way.

Right.

Yeah.

So sometimes, sometimes you just have to take it with a grain of salt.

Self-fulfilling prophecy.

And the point is, you can't have perfect forecasts. However, if you've got enough historical data, it's going to be pretty accurate because you've got what I would call all this detailed data for a bottoms-up analysis. Most forecasts don't have that kind of bottoms-up analysis. That's really accurate data. So as long as your data is pretty accurate, back to your, is your data cleansed, standardized, integrated, which is no small feat, but if you've got that data all together, and it's kind of integrated. And by the way, ideally, you'd have some algorithms to say, if this, then that, some if-then type algorithms. You can actually do some really cool forecasting about what the implications of, say, increasing your internal transfer and promotion rate would do to your turnover and your employee engagement, which would increase productivity. And people might call that, you know, black magic or, you know, dark science. But it's not. There's a— and by the way, you can't predict the exact amount, but you would get a ballpark guess.

No, but these are real human factors.

It's just a range. And so, what you do is you cover yourself. By the way, again, like I said, back to the CFO, we didn't know what the numbers were going to be in the future. So, we'd pick the high and the low. Guess what? If the actual is anywhere in between the high and the low, you're a genius. If it's above the high, you're still brilliant. The only way you lose is if it's below the low. Now, you can't do like zero to a billion dollars. But you know, you do a forecast, it turns the odds of you being correct from very small to very high. And that's how you build that credibility and you build a forecast that people can action and rely on. And by the way, maybe they're, you know, if they're, you know, what you really have to do is get them over their fear to act. And that's why you stoke that fear, which by the way, and here's my fear item for the day. I'm seeing a lot of predictions from different kinds of people with different perspectives predicting turnover rates to go up next year. One of the main reasons is 40% of the workforce changed jobs in 20, you know, basically starting in late 2021 through 2022, beginning of 2023. And turnover rates have settled down for a lot of industries and jobs. Now, of course, companies are doing their layoff thing, which I think is very foolish considering how scarce talent is about to become, which by the way is another topic we talk about. All the assumptions of the past are gone. We're going to have scarce workforce, limited workforce for the foreseeable future, 5, 10, even 20 years. There's not going to be enough good workers out there. Thankfully, AI will help. But anyway, what really is going to happen next year because a lot of people wanted to stay and get some time in their role? Well, the market is still really hot. So, there's going to be, I think, and I don't know it's going to be again a version of the Great Resignation. I would definitely see turnover rates ticking up a little bit more for companies, especially ones who do these semi-arbitrary reductions in force when they're still hitting record profits just because they want to get a little more profit.

So essentially, you're saying that it's almost like a reaction to, okay, I left— I was afraid to leave my job for many years, finally left, went to this other company, did what I wanted to do for the last 2 years. Now I want the actual job I really wanted.

Yeah, yeah. I tried this company. Hey, the market's great. I'm a hot commodity, I've got some skills, why don't I look at the market? You look at the market, you're probably going to end up jumping.

Okay, okay. So any— it's— this is, this is part of what you discussed as predictive analytics. Um, any other crystal ball, you know, predictions about— so turnover potentially increasing, which I think if you look at the industries, in some industries, that's going to be much higher than others. And let me interject with that just one second. So there was a mass exodus of healthcare workers during the, especially at the tail end of the pandemic, when it was really in its peak, because they weren't turning over to other companies. They weren't leaving this company to go to that company. They were leaving the industry, and we saw a huge decline in candidates available to do some of the work because they literally just disappeared. I mean, they vanished from the workforce. They went to go do teaching or something else. So that's not even— that's a, that's a kind of a turnover that's not— I don't even know what to call that. That's not turnover where you have to replace the seat with someone else. That's like you have to literally go out and get someone fresh that hasn't even done the job almost. So there's going to be some of that, and there's going to be some of the, you know, industries being repatriated. But overall, is this— the prediction is just overall turnover rates are going to increase, not—

yeah, industry, okay, across industries. Um, I also predicted next year— I thought it was going to happen this year, so my prediction for this year was wrong— but, uh, the SEC just updated their website. They now show a date of April of next year for the next phase of releasing human capital reporting requirements for all public listed companies, which will trickle down to privately held companies over time. But it'll start with the public listed or international firms who list shares on any U.S. exchange. So, they're going to have to start reporting and disclosing even more. More companies are disclosing more and more, but it's still, you know, very small baby steps. They're going to have to disclose a lot more. The big prediction is going to be turnover. What's going to be required to be disclosed, headcount in detail, meaning how many of certain kinds of jobs and labor costs. In fact, the Finance Protection Act, you know, they're never early to any party. They got on board with this, actually submitted a separate petition to the SEC asking for greater labor cost disclosures, especially contingent labor. So your breakdown of your workforce costs and contingent workers, because they're a part of providing a good service. But they don't show up in the employee headcount. So an easy way to cheat your revenue profit per employee is you have lots of contingent workers, like some of the big tech, 50% of your workforce. So you look like you're super productive when in fact you're spending all this money and just not reporting it.

It's just a, it's just a cost. It's hidden.

It's a hidden cost.

Yeah, it's a hidden cost. So, um, is, is this similar to what you were doing with the ISO committee. I mean, these kinds of requirements, because I, you know, but what I, what I learned after many years working with the ISO was that they don't create a requirement. They create a standard that people can agree to adhere to voluntarily, right? What you're talking about now is this is becoming law. Yeah, how different is what you were actually defining in that, in that committee? And can you share, has that been established, is that already published?

Oh yeah, so ISO 30414 is probably what I would call the basis of GAAP accounting for HR, how to measure and report the workforce. It's, uh, 60 different metrics. Anybody can go buy it. You go to the ISO website, do key in ISO 30414, 414, human capital, you know, reporting and measurement for, you know, internal and external disclosure. So it recommends metrics to be disclosed, right? But the SEC is now mandated and to measure. And we hope there's a tremendous amount of alignment between what the SEC comes out with in this ISO standard, because for organizations, they don't want to be on the hook to just come up with their own metrics. That's a great way to get sued, especially if you're off or You're not able to aggregate your data properly. So actually leveraging the ISO standard would be a great way to, you know, let's tap that fear button, a great way to reduce risk and reduce adverse events by saying, hey, we're in compliance with this global standard. And yeah, all ISO standards are voluntary, but it's an easy one to take. Hey, we read the standard, we're applying these, we're using this in how we measure and disclose. So that should give you some safe harbor if anyone asks tough questions about why are you measuring it this way? Why are you not measuring or reporting it that way?

It's somewhat standard. I mean, it may not be law, but yeah, that makes sense, right? Yeah. ISO 30414.

And by the way, we're actually updating it now. It's been reopened. It's 5 years old. And if the SEC comes out with something new, we're just going to update that standard.

You're going to add it in there, right?

You're going to compliance. Yeah.

Right. Because now they'll be compliant. Yeah, it's amazing to me as I, as I walk through the halls of talent acquisition. And I've, you know, as a consultant, I worked with a lot of companies, more than 300 companies in different capacity, and as a, you know, as a sourcing leader as well. And I'm always shocked and amazed at how little our profession—TA, not HR, TA, so the subset of HR in workforce management, that is talent acquisition, how little TA is aware of regulatory and compliance bodies that are, that have supervisory roles over our, our work. You know, everybody knows EEOC, some know OFCCP, but very few are aware of the regulations from Sarbanes-Oxley, and at least 7 different, you know, federal acts that actually require us to do certain things in a certain way. It kind of falls on the hands of legal and HR, so TA doesn't really see it. But it's really— it, to me, it seems like they're painfully unaware of these requirements that are out there, you know, like Sarbanes-Oxley, for example. So now the SEC— this is going to be another one— SEC is going to be requiring which affects compensation, for example. Is this gonna, is this gonna move the needle with pay transparency at all? Or— because one of the things that— it is? OK. Well, I find that—

I was never a fan of that CEO-pay-ratio thing. I think that's like a, you know, I don't know what purpose— that's, that's like a, that's like a gotcha metric for CEOs. CEOs are probably overpaid. But having the total labor costs divided by number of employees by different categories is going to shine. That's not going to give away the secret sauce, right? Exactly how much you pay people at this level of tenure and seniority, or this kind of job. But it's going to give a better direction. And really, in an aggregate, I would say it's going to be a reflection of the strategy of the organization, which is do you bring in young talent and grow them? Or do you buy the free— go to the free agent market, you buy all the best, and that's how you run things? Well, buying all the best is going to be more expensive. You know, if we're a customer, that means we're probably paying more for the product or service.

And I think this is a, this is a good measure because there's, there's another measure that may be a little bit underrated, which is the total productivity divided by number of employees, or in other words, the individual contribution. Right? So companies like Cisco at their peak had $750,000 per employee of net contribution to, to EBITDA, right? So they were essentially generating $700,000 in profit for every person that they had. So that's the profit side of it. This is essentially kind of the opposite of the cost side of that, which, you know, is, is going to help make those numbers a little bit more transparent, I think. Um, so there's this— I know that you said we can go buy the, uh, 30414 from ISO. But there's this other thing I wanted to thank you for. You very generously shared with me a document that is essentially the 25 key human capital questions that you should be asking yourself. Now, I received that as a favor from you. Is that document something that can be obtainable if people go visit your website? Yep. Or, OK, because is it something that you, that you can get?

Go to the website. Yeah, they can get— it's a great place to start. I've seen organizations use it as a survey tool to figure out where analytics and workforce planning should start in terms of a focus. Survey some of your executives, say, which of these questions or pain points seems the most important now or going forward? And you can aggregate those into, you know, a bit of workforce strategy. And by the way, you know, from my side, if somebody says, here's our top 5 key human capital questions, I could tell you what metrics you should be measuring. And then link it to if this metric improves because, by the way, the old CFO hat never comes all the way off. I'm still trying. Basically, if the metric improves by 10%, what's it worth to the business? Because I find that that's a huge way to help an organization and to communicate to non-HR leaders because we come in with our HR metrics. And we assume, or we want business leaders to speak HR. It's not going to happen. We need to learn a little. To be fair, it's not going to happen. We need them, we need to learn a little bit. We don't have to become MBAs. We need to learn a little bit of business language, which is basically just, just put those HR metrics to a dollar impact. Do a ratio or do a range. Do a high and a low. Get, you know, gives you some cover. And that's enough for management to act on. And if they don't want to act on it, it's like a rock, a little pebble in their shoe. It's going to irritate them and they may come back to you later. And it might actually then be their idea and they're asking why you haven't done anything with it already. Right.

Well, at the very least, they can't say they didn't know, right? Yeah, yeah, yeah. So I, I found those questions to be fantastic because, and by the way, I don't want to mislead folks, these are, these are questions, not answers. So it's, these are the questions you should be asking, um, and, and some of them are really hard questions to answer. I mean, they're, you feel like you, you feel like you want to say yes, we can, but it, it's almost like if you don't have like the, I'm, I've learned a new term lately, uh, data harmonization. If you don't have harmonized data, you won't be able to accurately forecast. So one of the— I think the first question is, can we accurately forecast our workforce needs in the future? And I think a lot of companies are going to want to say yes, but then we go back to, they say we can and then we don't. Yeah, right. Yeah, especially if we have a bunch of contingent labor that's kind of swept under, and then those numbers aren't really showing up in productivity. We have turnover, and we don't really understand the difference between, you know, a newly hired and a productive employee. So how long does it— you have to be able to answer things like, how long does it take someone to be productive? What is the lag time in order to know what our forecast is going to be for workforce force, we also need to know things like that. We also need to know how long it takes someone that we hired to actually get up to speed. And if you don't know that, then it gets harder to forecast, right? Right. So these are big questions that you want to start thinking about. Honestly, it's a, it's a very— 25 questions is a lot. I think if you took that and made a 5-year plan out of it and tried to tackle 5 a year, you'd be in good shape. But I'm sure you have other plans for that. So they can go to you, they can go to hrci.co and look for that as a, as a downloadable.

Yeah, sorry, hcmi.co.

Oh, hcmi, sorry, hcmi.co, and then find it there. Right, there we go. I had that right on this one before.

And lots of, yeah, lots of case studies, white papers. We kind of punch above our weight for all the information and sort of proof points. And we find also case studies are great for, let's see how somebody else did it, and then I can, you know, mirror a lot of what they did and how they did it.

Well, I gotta tell you, I'd love to, if you would be open to, I'd love to have you back on the show early next year to talk about this once what we've predicted here actually has had time to happen to talk about our predictions, um, you know, to just kind of revisit what we discussed and see how— would you be open to that? I'd love to do that.

I would love to do that. Would love to do that. And happy to eat something that doesn't taste good if my predictions were wrong.

No, I'm just— I just want to put, you know, I want to— I want to close the loop on it. These are— these are predictions that are very specific. We can't, you know, like, turnovers could increase. I mean, we'll know that within the first quarter, right? Yep. And how much did it increase, and does that project into the year ahead and all that? Before we wrap up, I always ask my guests two questions. The first of those is, can you leave us with something to chew on, a thought-provoking idea or a question for us to think about that's not in the Top 25 Questions, to really analyze over the weekend and, you know, deep thoughts, right? Like, not an answer, not, not a thought from you, but more like a question for us. What would you like us to think about over the next few days?

How your organization can truly think about and act as if employees are the most valuable asset that the CEO usually says. Because all the accounting rules capture them as a cost. And there really are no good metrics for the positive side. When you hire somebody, you have a cost. One can argue that's a negative. Sure, it's a drag on profitability. But if you didn't need them, why are you hiring them? So, obviously, there must be a value that's greater than the cost that's being provided there. And so, how is it that the organization is going to measure and act on that. Because the joke I always tell is if people are the most valuable asset, where are they on the balance sheet? And the answer is nowhere, which is partly true. In reality, there might be something on the liability side about people, like anything that's owed, like accrued bonus, accrued retirement funds, accrued payroll. So, anything that's owed to people is listed. But on the positive side, zip.

It's not an asset. No, it's an expense on the Yeah, it's an OpEx, and then it's also a liability when it's unpaid vacation time and things like that. So yeah, so where is it really an asset? And that's where I think the two sides of the ISO question and the question about, you know, what's your net profit from per employee are really good questions to help answer that. But yeah, I think what you're saying is, how can your organization actually follow through with people are our number one asset, right? Is that kind of—

Yeah, we should be investing more in them and not just comp, you know, investing very surgically in training or in, in career development. And of course, pay, you know, where it makes sense. But, you know, if you do it right, especially with the talent acquisition sourcing, you might be able to get better talent that even costs a little bit less if you're really good at it.

That's definitely a— that's a huge argument. That I make all the time is that we're able to find macro commonalities and bring talent in. You know, the joke I always like to say is you don't want to hire the guy that invented the iPhone because they're not going to invent the next iPhone. You want to hire the guy that's going to invent whatever the next iPhone is. They didn't know, they didn't already do it. If they'd already done it, to your point, they're going to be really expensive and there's no guarantee they're going to do it again, right? Um, So, you know, you know, they'll be good, but do you know if, are they really going to have that same, you know, mass multiplying effect? We don't know that, right? We can't predict that. Great point. And then the last question is, who should be our next guest?

Oh, wow. Um, I, you, you caught me off guard on that one.

I mean, you'd like to interview if you could.

Who would I like to interview? I would like to interview the, uh, SEC commissioner.

Okay, well, somebody that I can actually get to.

Yeah, yeah. Why they're— why they're holding— by the way, Congress actually— a bunch of senators actually wrote a letter to the SEC complaining about that delay on the release of new reporting requirements. Because, uh, actually, I would say there's, you know, you should talk to an institutional investor and get an investor perspective. On all of this, on people, human capital. Why do they care? Why should all of us care about human capital, people, talent, if you will, and what the potential of that data is? Because I think it— I'm putting words in their mouth and I can even come up with a couple of names for you. That would be great.

We can do that offline if you want, but that's a really good one. I like that. Yeah, sure.

Because they're going to say that, you know, companies say they do all these things really well, but because they don't have to disclose any metrics, they can be saying that either out of, you know, wishful thinking or just plain lying. Right.

Well, we'll hope it's just guessing, but yeah, I get you.

People are our most valuable asset. And then as soon as the camera turns off, quick, throw more people in the fire to burn them. You know, we need that. We need to burn that oil, we need more fuel. Yeah, yeah. And like, that's not how you're—

yeah, and that's sometimes how it feels, even though that may not be the intent. So, okay, an institutional investor. I'm gonna get some names from you. Okay. Well, thanks so much for appearing. I know it's, uh, close to the holidays, you probably have a ton of other things to do, so I appreciate you spending your very valuable time with us here at Shelly's Alley. And I look forward to doing an encore of this, uh, somewhere in Q1 next year. All right. In 2024. Thank you, Charlie.

I'm so glad we bumped into each other at HR Tech. Me too. And we, you know, and realizing we've actually worked together before and we didn't really realize it. Yep. This has been great.

Each other's names on lists and stuff like that. That was fun. That was fun. I thought I knew you. I thought I saw you before. Oh yeah, we were in. So thanks, everybody. Happy holidays. We won't be doing another show until next year. It's only 2 weeks left in the year. So please be kind to yourselves. Be kind to each other. Happy New Year, happy holidays, and we'll see you in 2024.

Happy holidays.