It’s time to challenge our concept of teams within organizations! In this episode you’ll hear from Mark Stelzner, the leader of IA HR Consulting. Mark started IA because he had worked with, and for, consulting firms and thought, “there has got to be a better way.” Mark amplifies the voices of the clients he supports, as he believes it’s about finding the right solution to help the organization thrive. IA really focuses on self-sufficiency. Through his work, Mark has been featured by the Wall Street Journal, the New York Times, Forbes, CNN, and NPR.
Let’s learn from Mark how HR can prepare for people analytics with dynamic teams in dynamic organizations.
[00:01 – 05:20] Opening Segment
- Dwight and I welcome and learn more about Mark Stelzner
- Today’s topic – People Analytics with Dynamic Teams in Dynamic Organizations
[05:21 – 16:49] Dynamic Organizations: What They Are, How They Run
- Stepping away from employees and into workers – Regroup, relearn, rest, reskill
- You have to be transparent and hold employers accountable
- The example of a knowledge worker
[16:50 – 32:53] Organizations’ Biggest Struggles Facing the Reality of Dynamic Teams
- Mark identifies the top 5 struggles organizations face
- How to help them address the issues – start with the data
- The importance of internal accountability
[32:54 – 38:15] Actions HR Can Take Now to Prepare for Dynamic Organizations
- How our systems can work together now to evolve
- Stop the protectionism and start seeing the whole person
[38:16 – 40:20] Closing Segment
- Summary of our conversation and final points
Resources:
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“What we’re finding is that a lot of organizations are questioning the whole hierarchy, the whole notion, on what it means to be an employee… is everyone really a contingent worker?” – Mark Stelzner
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“If you don’t know what you have, you can’t possibly understand the undertaking of a good data governance model… What’s the roadmap and prioritization that’s going to get us from where we are to where we want to be?” – Mark Stelzner
Announcer:
Here’s an experiment for you. Take passionate experts in human resource technology. Invite cross industry experts from inside and outside HR. Mix in what’s happening in people analytics today. Give them the technology to connect, hit record, pour their discussions into a beaker, mix thoroughly. And voila, you get the HR data labs Podcast, where we explore the impact of data and analytics to your business. We may get passionate and even irreverent, but count on each episode challenging and enhancing your understanding of the way people data can be used to solve real world problems. Now, here’s your host, David Turetsky.
David Turetsky:
Hello, and welcome to the HR data labs podcast. I’m your host, David Turetsky. Like always, I try and find interesting and fascinating people inside and outside the world of HR to bring you some insight as to what’s going on in the world of HR data and analytics. Today, we have Mark Stelzner, from IAHR consulting, or Infleccion Advisors, right, Mark? Yeah,
Mark Stelzner:
that’s why we changed a tie today because no one can pronounce inflection. Right. So
David Turetsky:
inflection sorry, there you go. Welcome. Thank you. It’s good to be here. Thank you for having me. Good to have you. We also have Dwight brown from Turetsky Consulting. Hey, Dwight, how are you? Morning, David, Mark. Good morning, Dwight. For those of you who are not familiar with Mark, Mark’s been in and around the world of HR for basically your entire career, right? That’s correct. He started IAA, because he had worked with in four consulting firms and thought, there’s got to be a different way of working. And so Mark believes in helping amplify each and every client he supports, by finding the right solution to the organization and then leaving by providing them with just what they need to become self sufficient. And to go, Mark, that’s just the way Turetsky Consulting likes to work. That’s awesome.
Mark Stelzner:
That’s fantastic. And I’ll tell you guys, I mean, you know this because you’re living this every day, this makes us the anti consulting consulting firms, because, frankly, every other firm in the world is incented to penetrate and radiate, put their hooks and claws into clients and never leave. And it’s really shocking, I think, to our clients, I’m sure you guys find this as well, that when you come in, at the beginning with the notion of we are exiting and to whom can we Knowledge Transfer Tool transfer and get you self sufficient. It’s a game changer. So we’re glad to continue to support the same ethos.
David Turetsky:
And one of the funny things about that is, is that they are actually shocked, they say, Hey, can we get another SOW? And we say, Okay, are you sure? And you know, that’s our ethos as well. So we’re gonna stick with that, we’d like that. And we don’t want to change. Fantastic. So for those of you who know, Mark, one fun thing you may not know about mark is, he likes to gamble. And he’s actually pretty good at it. Mark, you got to tell us why and how.
Mark Stelzner:
Oh my gosh, it was good at gambling is kind of a relative term. And this is a this is a this is a data conversation. So all the data would guess that for everyone who wins, you know, there’s there’s many, many more words. But one funny story just a couple years ago, I was with a client up in the Midwest, in this particular city I was in they happen to have a little local casino, the client had an emergency that came up in the middle of a workshop and they said, Hey, Mark, we heard you like to gamble. Why don’t you literally walk across town and guys, I’m talking like five blocks, right? walk across town, take a break, come back in like two, two and a half hours. And we’ll continue with our working session. So I hope it it’s a beautiful day, I pop into some local casino I’ve never heard of. I just magnetically drawn to the stupidest thing I could play, which is the slot machine I put in, I put in, you know, I don’t know, I probably put in like 100 bucks like a moron right? Put in 100 bucks. I hit a $25 play. And I won $125,000 and that’s exactly what makes the story interesting is not that I want that which was crazy. By the way, it was absolutely insane. But that literally on the way back to the client after the bells went off and they took my photo inside, you know, couldn’t catch the giant check couldn’t fit in my suitcase back in the plane. But But at the end of the day, she guys followed me when I left and tried to jump me to steal the
David Turetsky:
No way.
Mark Stelzner:
and all I’m thinking of they did give me a suitcase full of cash. You know, this isn’t an oceans movie. Like I’ve literally just walk in with a check. So you know, I’ll leave it with this. I still had the money and and they got arrested. The day? Yeah, everything comes with a price but yes, I love to gamble. It’s been too long with COVID I haven’t gambled in like a year and a half. Wow. And so you’re good
David Turetsky:
at gambling and escaping. Yes, apparently to catch her the best
Dwight Brown:
Best consulting gig ever. Exactly.
David Turetsky:
So the topic for today is dynamic organizations and the challenges that a company might face when it comes to teaming as well as analytics. Mark, this is near and dear to my heart, because I’ve worked with many clients who’ve had many dynamic teams, whether it’s consulting firms or investment banks. What is a dynamic organization in 2021?
Mark Stelzner:
Yeah, and I love the question, because what we’re finding, and if we think about I mean, even the work that we do, or the work that we find our clients, employees, or people leaders do every single day, almost everything is truly dynamic. We even had manufacturers where, when we started talking to them about dynamic teams, they’re like, well, hang on, we have hourly workers that come in and work the line, it’s like, but every line is dynamic, right? you’re producing new products, new services, you need new skills, new capabilities, and new resources. And guys, where we tend to start is we start to step away from the notion of employee and we embrace all worker types. Because we’re finding I’m sure you deal with your clients as well, that there’s probably maybe a 30 to 150% population growth, when you start to take into contention and contract labor or temporary labor pools or seasonal labor pools. So part of it is we have to think about all the workers, we have to think about how all the workers are assembled, we have to think about how those workers are dynamically assessed for a tested and verified skills, then we have to think about how they’re provisioned to produce some kind of work product. And then they’re released, potentially rescaled retrained and reassembled and it’s happening constantly in every organization around the world. And even for those that occupy let’s say, a traditional supervisory hierarchy, their days are probably split in a way that maybe 30% is allocated to project day 40% is allocated to really the job you were hired to do. And the remainder is maybe dynamically assigned to three or four other initiatives, products are supporting requirements. And so the point is, our systems, our data, our infrastructure, our pay our benefits, are really ill equipped to be able to manage the dynamic assembly, deployment and reassembly of worker types, for the provisioning of resources and for the the outcomes of work whenever that work may be. And so what we’re finding is a lot of organizations are really questioning the whole hierarchy, the whole notion of what it means to be an employee, we have one very large client, they have over 100,000 employees that is saying, well, is everyone really a contingent worker? Right, putting aside regulatory and legislative concerns is everybody really a contingent worker if we really think about how work is done, so the data, the data story is foundational, and frankly, it’s broken? We’re not quite there yet.
David Turetsky:
But there’s also another part mark, which goes back to corporate culture, right? It’s the How do you espouse the relationship between the employee and the organization? What is the value proposition to the employee? What’s the value proposition to the organization of that bond between the employee and the organization? And when you start to question that, or when you start to change it, you upset some of those, especially the people who you consider to be permanent, quote, unquote, permanent, I’m using my air quotes, permanent full time employees, you start to question the foundations. And that kind of puts a rumble underneath their feet, right? It makes that transition, or the communication very difficult of how do I change your relationship to the organization? I know that was a loaded question. But no, no, I
Mark Stelzner:
don’t think it’s a loaded question. Honestly, David, and I liked the question, because frankly, if we go back to a pre COVID world, we had this problem staring us in the face for all these worker types. Anyhow, so you know, I used to live in DC and work in DC, and we used to do a lot of work with government agencies. And one of the things that you noticed is there were different colored badges, right, some work, some more contractors, some might be consulting firms, and some would be those full time federal employees. There were all sitting in the same rooms, they were all side by side in cubicles, they were all working on the same projects and initiatives, when the differentiation in that employer value proposition came into play, is when there was, you know, a beer after work, right, or the organization decided to assemble something but but when we were on the ground, and we were all on the ground, you know, in pre COVID errors. This happened every single day, those people that were the other who were literally doing the same job, were literally in the same facility, probably in the same cubicle block as as their full time employee peers. Were excused from the promise of that employer value proposition. And one of the things not to go on a mini rant but one of the things that I’m challenged with with the VPS and this employer promise, is you have to be transparent meaning is this factual. Is that aspirational? Is it inspirational. isn’t meant to be some combination there. And I was literally with the CHRO on Monday, challenging her, she’s putting her new people strategy. They’re headquartered in Europe. And I said, Well, your employees called bullshit on this. Well, they say at the end of the day, that this is not factually the organization that I work for. And it’s okay if it’s not as long as you declare your own self awareness that this is who we’d like to be. And these are the actions that we’re going to take to get there. So absolutely, I think there’s a there’s a promise, maybe a false premise, in some cases, in terms of how to hold the employer accountable for what they claim life is intended to be while working for the organization.
David Turetsky:
Now, I know you said Mark held everything equal, or you held everything equal, including regulation, and laws, you can’t do that in the world of HR, because the value proposition leads to regulations, or the promise of value proposition to the employee leads to regulations, which has a direct impact to those two people sitting next to each other one getting one not getting and the potential for litigation, or the potential for, you know, class action, like we’ve seen, you know, Microsoft, but when Microsoft got sued for having contractors and employees doing the same job, but yet the contractors weren’t getting the benefits and pay. They were being treated as employees, but they weren’t getting paid like them. I think that was the example of it happened. It feels like a long time ago now.
Mark Stelzner:
Yeah. And we see what the gig workers as well, right, you know, mass litigation associated with the gig economy, you know, with Uber and Lyft is probably the most prevalent examples. So at what point is the legal manifestation of directing work, right is directing one’s work and controlling one’s work move you into what certainly here in the States, we would designate as a full time equivalent, right. And that’s a problem that I think people are wrestling with, but but not to pick on Uber. But Uber was a perfect example of how they advocated to frankly change the laws and created an economic incentive to do so. So we’re talking about a long time horizon. But even if we set aside maybe the legal implications of everybody being a dynamic worker, or everyone being a contingent worker, we’re still acknowledging now with mobility, that location, right is no longer a barrier to being an effective knowledge worker, let’s say certainly manufacturing and certain retail hospitality presently is a core requirement. Yep. But as we’re watching what’s happening with the craziness in the housing market, right now, people are fleeing, you know, I left I left San Francisco, I left San Francisco a couple years ago for Nashville, Tennessee, I’m about to leave Nashville, Tennessee, and move to Atlanta here in about six to eight weeks. So, you know, if you’re a knowledge worker, you can, frankly live anywhere. But if we think about data, right? Will employers take the position of paying you where you live, or pain you the value of the job? or dare I say jobs, right, plural that you occupy? That’s when we look at market pay, right? I mean, just again, if we focus on one subdomain of HR, which is compensation, or the compensatory elements associated with market today, and then we think about the mirror process for comp or ratios, and let’s say annual or targeted adjustments, do we do it based on the roles that you’re fractionally applied to we do it on the job that you were hired into, which is, frankly, unrecognizable, compared to the work you’re actually doing every day? Was there some hybrid there in? One of our very large tech clients is trying to figure that out right. Now, how do they do dynamic market pay? Yeah, and it’s an incredibly complex algorithm. But again, if we sent her on our HCM systems as the system of record, again, we haven’t seen a maturity model quite yet come forward from the major HCM systems to be able to support an employee record with this level of complexity.
Dwight Brown:
One of the things that you touched on that really underscores that as the, the multinational corporations, and when you get into pay a multinational, David knows this, I spent a good amount of my time in South America this past year and a half and in Colombia specifically. And as part of that, in the Colombian economy, average pay is probably about a quarter to a third of what the pay is here in the United States. So if somebody lives in Colombia, are you doing overall market driven pay? Are you doing country specific, as you touched on, there are a lot of layers to this and each layer, you have to peel back and push things forward again, after you peel it back. So Well, I
David Turetsky:
think, I think Dwight, that’s actually giving rise to even more of the gig economy where there are resources available around the world if you go to Fiverr. Or if you go to Upwork. Or if you go to some other places that give you the ability to get access to specific skills and specific types of people who can do things for you wherever they are, you’ll see that you’re paying, you’re paying similarly around the world for those types of activities, focused on the skills that those people have. Obviously, that person who’s in that market isn’t getting the benefit of the place arbitrage, right. You’re giving up control of the person as Mark was saying in the place that they need to be. Well, they don’t really need to be there right now. So but you’re paying similarly, you may be playing less. And in fact, most the time you’re paying lots, but you’re not paying substantially less like you were used to. Because people say, Well, you know, I don’t need to charge $5. Because that activity in the US, I can get 25. And I’m really good. And I’ve got all these great views. So I can at least do 20 or 25. And someone will pay me that rate, because that’s the going rate, though.
Mark Stelzner:
I think, guys, you’re you’re dead out. I mean, Dwight, to your earlier point, you know, I, we just finished an assignment for a large global manufacturer. And they have real issues with mobility, even cross European mobility, right, because of the statutory benefits that are offered in each of the countries in which they operate because of the familial connection that one has, in their locale of choice, you may have an opportunity in another local country, right? That’s, that’s, you know, presumably within mobility distance for relocation, but the friction is too high to warrant that. And then David’s, your point, then is that the value of the work or the value of the location because you know, I may buy that international resource at what would be a premium compared to their local valuation. Exactly. But in our revaluation of the work product they’re producing, it’s still fractional, it’s it’s, it’s, it’s the same equivalent to what we’re seeing in the housing market, right, which is, frankly, I can take my millions of dollars from California moved to another low cost locale, I’m getting more house for that. It’s the same thing for cop, like, we need to be paying people based on the value of their work, not necessarily based on where they’re located. But it’s very tricky for people to navigate on both sides, frankly, yeah.
Announcer:
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David Turetsky:
So Mark, that actually translates to an issue that companies are going to have when they’re dealing with dynamic teams, which is the data around the dynamic teams and some other struggles that they may face to actually have implementations of those dynamic teams in the organization? Can you kind of give us like your top five of what the struggles are? I think I kind of see that one, which is data, but what what are the other ones? Or kind of explain what you think, are those major struggles that they’re going to have?
Mark Stelzner:
Yeah, I mean, struggle. Number one that we see is the relentless catalysts for change, right organizations can certainly try to establish a three or five year plan. But let’s be honest, you know, those don’t sustain. We’re seeing unprecedented C suite turnover, right? The average tenure for a C suite leader is now down to about 14 or 15 months. So the expectation is, when a new leader arrives, I don’t care what role you’re occupying, you’re there to foster change. And to drive change in the organization, you are a catalyst or a trigger, we see a massive increase in m&a and divestiture activity, constant catalysts for change, we see a need to rationalize just within the four walls of HR and people communities to rationalize the HR ecosystem to develop deeper and fewer meaningful relationships to govern, which means our HR tech stack, right is constantly changing or rationalizing. And there’s almost a Darwinian consumption of the hierarchy of who owns the front door of the employee experience across talent acquisition, talent management, core HR payable rewards, or any combination they’re in. And we see frankly, that the populations are changing, people are either opting in and out of organizations that are higher frequency, or the categorization in which they occupy is changing. So I may have retired from organization a, but guess what, in six weeks, I came back as a part time gig worker, or contingent labor. So don’t really ever leave or I’m an alumnus, right, I’m going to go graduate, as it were, go get additional skills, and then come back in two or three years. So all of this means that everything is changing all the time. And one of the biggest issues that we find with employers right now, and I’ll get to the data side, because that’s where we want to center for this conversation, is the prioritization, that HR is ill equipped, in most instances, frankly, to be able to ingest this quantity of change, to be able to demonstrate, frankly, prioritization and to able to extract insight, insight from the information and God forbid some level of predictive information that allows us to inform the decisions that are the underpinning or outcomes of this dynamic infrastructure that we’re describing. And, you know, go back to the CHRO I spoke with earlier this week. I said, Well, what’s your key pain point she’s looking at, you know, a global harmonization project for their 79,000 employees and 76 different countries and she said data, my biggest problem is data. I have no data that is accurate. I have 125 different HR systems that are touching my people across various geographies around the world which is not unusual, frankly. How do I extract accurate information because let’s say diversity, equity, inclusion and belonging is a key care about back to your point, David about about you know, What’s their employee value proposition? How do we live up to what we’re saying? Let’s just focus on dei and belonging for just a second. I don’t even have accurate data, demographic data on the profiles of my employees, and are we losing disproportionately, you know, females of color who are non binary? Like, I have no idea because by the time I get the data, the data is out of date. And it’s an accurate it’s the age old story of data in jeopardy. So with so much change happening all the time, how can we center ourselves and ground ourselves on what is the core truth of the organization, which is foundationally built on data? Right? So that’s really the number one thing that we’re trying to advocate for is we’ve got to start with data. And we’ve got to start with a common data repository or source that, frankly, we can have some level of trust and veracity behind. Go ahead, David?
David Turetsky:
Well, the thing I was gonna say to that is, is that what we’ve been advocating for is data governance, which is having good definitions, having a really good understanding about what is the truth? What is the source of truth? Where is the data coming from? What is its velocity? What’s its veracity? Where can you point to and say, that’s where I’m going to do my reporting and analytics from and feel confident about it, what we have to do a lot of times is step back at least one or two steps with a client before we can actually move forward, because they haven’t taken that good, hard look at their data to actually look at what the holes are first, before they actually go and start running an analytics program, or even just trying to get good headcount data or to solve a higher order problem, like you were just talking about, about who’s leaving, and why are they leaving, they can’t do that until they take a couple steps back, they look at the configuration of their system, they look at the configuration of their data. And you know, Dwight just wrote a great blog, and we had a podcast about it a few weeks ago, about data governance. And I think it really speaks to the fact that we actually got a really good reaction to it, that companies really do believe data is the foundation of understanding your organization.
Mark Stelzner:
I couldn’t agree more. And Dwight, I’m looking forward to reading that post and amplifying it because you’re 100% correct. And part of this is, HR needs to establish a firm and fixed point of view of their role in governing and managing data. And part of that is, are you intentional about a taxonomy? Like? Do you have a global taxonomy that you can harmonize to if you don’t? Whether you’re aware of it or not, you’re subscribing to others? taxonomies? And have you Have you even deconstructed or self discovered the fact that you are? And do you know what their data sources and data taxonomies are? So part of this is being you know, what we affectionately refer to as HR private investigators, right? If you don’t know what you have, you can’t possibly understand the undertaking of a good data governance model, you can possibly understand the change management that will get you from current state to dare I say, like an idealized future state. And then again, what’s the roadmap and prioritization, that’s going to get us from where we are to where we want to be? And how do you not cede too much ground because of maybe a lack of discomfort, a lack of expertise, even a lack of storied and capable resources within the four walls of the people function? And how do we lease that talent right from either other parts of the organization that perhaps are a bit ahead? You know, there’s great examples within almost every industry, frankly, where data is at the center of every experience for every business, I think, I think that’s, you know, almost table stakes today search. So HR is behind, and we have to have a certain firm point of view. But But that means resourcing that means stopping something else. And this is the hardest part, right? I mean, that means stopping something else, and creating both operating and capital funding, and creating resourcing full time and part time Rex to be able to explicitly focus on this problem to separate signal from noise. So Dwight, thanks for your advocacy in the market. I think it’s well needed.
Dwight Brown:
Yeah, most definitely. I appreciate that. And one of the other major challenges that, that I’ve seen is the cultural aspect of siloing within organizations. And if you want to look at data governance, you have to break down those silos somehow. And when you’ve got such a cultural underpinning, that perpetuates siloing, it makes that job so much more difficult, along with the fact that the concepts of data governance and data quality for people are sort of there in the back of their minds, but getting them to wrap their heads around the need for a data Data Governance Program is also a difficult barrier for getting through that. And so like you talked about with HR data, the organization needs to really give the value equation of where HR fits into this, and then move on to how do we break down those silos so that we can get the data governance we can start to build those data warehouses or data lakes or whatever the aggregation mechanism might be, so that you can start to use that data on an ongoing basis, but definitely A lot of difficult elements that that go into all of those pieces.
Mark Stelzner:
Yeah. And boy building on that, I mean, I’m not sure if you guys see this with with your clients, we certainly see this at times, understandably. So you can’t outsource the accountability for this to your third party providers. Because your third party providers certainly have a point of view to the extent that their point of view and their established framework, and taxonomy and approaches are aligned to your particular outcomes. Fantastic, right. But But any organization of any strength, will say, Well, what are you trying to achieve? What are the outcomes, so we’re big advocates, guys also for really driving specific use cases, because I think at times, it’s difficult for certain leaders in these organizations to get their minds around how this data will actually be brought to life in the flow of work. And in making frankly, really key and critical and strategic decisions. So by bringing use cases forward, which we would collaborate to develop in partnership with our clients, we can then bring the best value propositions of those third party providers forward because it’s got to start with the one and then the providers can bring forward the how, but I see a lot of temptation to sort of outsource as much of that accountability to third parties as possible, when frankly, the the employer can see that much ground. I’d be curious, David, boy, what you guys are seeing as well.
David Turetsky:
I would like to think that organizations have centers inside their organization that they could tap, like you were saying before, who have had these experiences in the past, whether it’s sales, whether it’s marketing, whether it’s in their IT organization, have champions in the IT organization, that HR could borrow, and be able to bring to bear or at least be able to help them see some of the issues and be able to focus on them, so that they don’t have to borrow resources from outside the organization. And so everything is kept inside the four walls of the company. But like you were saying before, though, sometimes we need to look outside, we need to buy or borrow some kind of taxonomy, or some kind of capability, and then own it, and then bring it in and make sure that it’s going to be yours and make it yours. Companies like mZ, or salary comm have done a pretty good job of being able to provide things like open source or for sale taxonomies that companies can use, and then build on them in their own organizations to be able to make them there’s so I’m hoping that there is a combination of the two, and that the organizations can then build on that get at least some little win, like being able to fix a job table, and then work on getting incrementally better from there. But I don’t know, what do you think do I know I,
Dwight Brown:
I totally agree, you have to have some sort of framework. And oftentimes, that does come from the outside. And if you can use that. And then you know, Mark, to your point really having good champions within the organization. And that’s always the challenge, because for a number of reasons, you know, getting somebody to agree to it, number one, number two, they get into it and figure out that they’re taking daggers from all of their colleagues, and it gets to be a tough job being the champion. But if you can get that and you can get some traction, you’re gonna have good results I’ve seen I’ve seen in a number of systems implementations. And I’ve seen both scenarios take place where a lot of the failed system implementations relied on that third party outsider to have the accountability for all of those pieces, the data governance pieces and the rollout and everything just sort of brought them in and said go. And they just weren’t able to do it, because they weren’t part of the cultural framework of the organizations and the successes that I’ve seen, have been those scenarios that you just talked about mark where there’s internal accountability, and you have strong champions in place to really push things forward. That to me is going to be the big difference between Are you going to be successful in the HR data space? Or is this not going to work the
Mark Stelzner:
way that we want? Yeah, and part of this guys, I would, I would think is also, you know, frankly, a little bit of marketing. And salesmanship as it were, you know, the operating businesses that we’re supporting, they’re not going to wait for HR, if they have a problem with, you know, how did they provision the right resources to open 150 new stores for a retailer or stand up, you know, 87 new hotels for a hospitality provider, or open 14 new manufacturing plants for you know, a new manufacturing set of clients that they’ve run around the world, the operating units are going to figure it out, right, they’re going to get after it, they’re left to their own devices, they’re going to find local talent. They’re going to they’re going to provision an acquisition if necessary, and they’re going to move forward. So part of this is we need to Stop marketing this almost as an HR data problem, this is a business data problem, right? And if we, if we can wait, the business is inextricably linked to both tooling and to resources and workers, then so be it. And one of the more fascinating conversations I had last year, because we were focused a lot on this what we were calling the war for skills coming out of 2020. We did a lot of research around this sort of global skills, taxonomy, and some of the bellwether research coming out of the World Economic Forum and others, is the fact that we haven’t thought about technology in a skills taxonomy, meaning what skills do our robotics AI and machine learning tools and capabilities have? What skills are they developing? And what skills remain and need to be developed for our human workers? Right, as we continue to evolve, and I’m not an economist, and certainly everything would say that, yes, we’re creating new jobs and new requirements. And that’s certainly true, but the amount of displacement that I’m seeing for jobs that will frankly, never come back and the speed, and to use the term you mentioned earlier, David velocity, the velocity with which we’re seeing now the infusion of technology, certainly as an accelerant to outcomes for replicable skills. It’s coming faster and more materially than I think ever before, what we’re not seeing, although the expectation is 50% of rescaling will be put on the shoulders of corporations, we’re not seeing the rescaling happening fast enough. And we’re not seeing centers of ownership either within or outside of organizations to say, well, we’re gonna have a real crisis on our hands with the velocity with which technology will displace skilled workers and skilled resourcing.
David Turetsky:
so fascinating topic. And we could probably spend entire, because we’ve had these conversations, and Chris have rilla, who I love from Deloitte, one of my best friends, we had a great conversation with her about this. And one of the things I think that’s come up mark is that when you start treating all of these resources that are providing value, as workers, whether it’s an AI, whether it’s a robot, whether it’s a person, that’s where our HR systems need to get to, and be able to not just skills, because skills are our building blocks to jobs, that are building blocks to output, right, the equation still there, it’s still the same. It’s just there are different actors now who are actually doing it. And to your point, there’s even a new equation because the work has changed completely. In some ways. It’s not the same output, it’s not y equals mx plus b anymore, the equations a little different, because there’s now new x’s and the resulting wise, a little more complex than it used to be offline, sometimes online, some physical systems electronic, so we could definitely get into at night, I would probably welcome you back for that as well in a different podcast. So I wanted to kind of end this segment by saying, it’s an incredible question. And I think what do you know, to wrap this part up, Mark, we’re going to have to figure out how do our HR systems and all the other systems, whether it’s GL, whether it’s eirp? How can they work together in a next generation of thinking, without throwing the baby out with the bathwater? Because we can’t do that we have to have an operational set of systems to keep us going. How did they evolve to get us to be able to have that foundational set of data to make business decisions? Not HR, this is not about HR anymore? It’s about our it’s just about resources. How do we change to get to the r? Yeah,
Mark Stelzner:
and let me let me take that on. And I’ll start with the beginning, which is talent acquisition. So if we think about foundationally, how talent acquisition works, right? We put together a job requisition, we put together desired and attested qualifications and skills that were required. And if I were offering David Dwight, you guys career coaching, and you said, Wow, I saw this great opportunity at my my dream job, what would I recommend you do? Well, first inventory, everything you’ve ever done, right? quantify every outcome you’ve ever created. narrowcast your resume in your application, take the collective wisdom that you’ve had in your entire career, and winnow that down using the same language and the same skills and qualifications that are on that requisition. And make sure that those two are inextricably linked. So by virtue of the best career advice that any coach would give to any individual today, the idea is I’m taking a fraction of who I am, and I’m taking that fraction of who I am, and I’m connecting that to the requisition that’s posted to increase the likelihood of the technology matching me right, because let’s face it, right, the algorithm needs to needs to rank and rate me based on the information that I’ve provided. The challenge right now then I go back, David, to where you started in our in our conversation about this promise of what it means to work for these organizations, right. The promise that we hear and that we Bandy about within the people function is I want to see the whole day that I want to see the whole life They want to see the whole person. Well, by virtue of the application process, we’re starting with imperfect data about our people at the outset. And very few organizations, frankly, have been super intentional about once you’ve gone through that funnel, and let’s say I’ve made you an offer, and now you’re in pre boarding or onboarding, how do I get the rest of you into my systems? Right? The fields exist, right? If we go to the employee record, that field certainly exists, but what incentive do I now have to expose all my David Miss and whiteness, right to the organization so that they know I speak four languages, or Dwight, right, I’ve worked in South America for 18 months. And you know, I speak Portuguese. And I’m and you know, so the moment that an opportunity comes up, I can actually surge into the day. I mean, this is these are the dream use cases, right is that we see the whole person, the whole person is represented in the data. It’s not just limited to the role I occupy. And as I develop skills, and as projects that I complete, and as performance reviews come in, that I create data portability, that all this data is is visible. But then we have all these political movements and organizations which are around restricting people, right, David, you’re on my team, Dwight, you’re on my project, I’m not going to lose you, I don’t want to incent you to raise your hand and expose your fullness of who you are. Because I don’t want somebody to find you in the system. The questions we get when we talk about these use cases, guys is Whoa, whoa, whoa, hold on a second. So wait, who can search on this data, any manager and any look, because we have the skills internally. And I’ll tell you just just a quick story on this. You know, in the heart of COVID, we had a client, a chief people officer out of La hospital system, who could not get background checks back, right, the counties weren’t responding. The universities weren’t responding. This was this was probably June of last year. And they have different workers that have been dispositioned, outside of the organization or part time work. So what they realized is while we might have all the skills we need for these 400 jobs we’re trying to fill within the people we already know. So they asked all their people to tell us about all their certifications and all the skills that we never frankly asked you about before. And guess what they did, they filled all 400 positions with people that are amazing, right? So we know nothing, we are fractionally aware of the skills and the capability and the data around the people we already have. And so if we stop the protectionism, we’re more intentional about seeing the whole person which we espouse right as a function. And we create the data library. So people know, frankly, what terms to use back to your foundational advice from the last segment, guys, then we know that Wow, great talent already exists. The project that David just completed, right means he just has a verified skill or a verified outcome that his performance would suggest through continuous conversations, is the level of validation we’re looking for. That means he’s ready for the next project. And again, it’s just it’s self perpetuating guys. Yeah.
David Turetsky:
So Mark, we talked about dynamic teams. And we talked about the dynamicism of an organization in 2021, we talked about a lot of the challenges that HR is going to face around data, and how they’re actually going to have to face those challenges and be able to come up with solutions that they’re going to have to look across the organization to help solve. And then we talked about some of the ways in which we can get started with that, or at least some of the things we’re gonna have to face. Mark, is there anything else that you wanted to bring up before we close?
Mark Stelzner:
The only thing I’d say guys, and thank you for the time today is is you have to have a point of view. So I would say do not see this worldwide round of HR being in the spotlight to the rest of the organization, establish a firm and fixed point of view and just get started. Get started with something pick a use case and outcome, a particular strategic initiative, a key care about that you can build some momentum and muscle and then grow that momentum and muscle through success, iterative success and demonstrable success with your organization writ large. But it all starts with being intentional. If we’re not intentional, as we all know about anything. Nothing’s ever going to get done organically. Absolutely.
David Turetsky:
Great. Thank you very much, Mark. Appreciate it. Thanks, guys. pleasure to see you today. And thank you for listening to the HR data labs podcast. If you liked this episode, please hit subscribe. If you know somebody who might find this episode interesting. Please send it their way. And if you have any comments, please go to the Turetsky Consulting comm slash podcast page and leave us your thoughts. Thank you very much. Take care and stay safe.
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