Speaker A Historian who developed a line of mathematics that could predict the future by following things in the future. And it reminded me of conversations I had with Dr. Jax. When you think of a medical doctor doing a diagnosis, what is a fundamental requirement before that can happen? You think about that. Well, it's systems thinking. It develops that way, yes. Symptoms. Okay, what are symptoms?
Speaker B Indications of a problem.
Speaker A Are they also a deviation from norm? Okay, well, here's the point, is that you cannot do a diagnosis until you have a theory of what's right and what's wrong. A theory. You cannot do a diagnosis until you have a theory. All right, we in the business that we're in are doing some remarkably similar things. We're doing them in slightly different ways. But when we talk about levels of work, we are talking the same language. There is a norm built into what we're doing. It's my argument that we should start to think about looking at numbers that naturally fall out of our work and see if there are ways to begin to develop norms and to begin to develop thoughts that are harry sheldon ish that are more predictive, that are more like. Do you want your organization to have 100% filled of what the demand of the roles is? Or do you want more or less? Okay. There's a strategy involved there. There's risk involved there. If you have just exactly a perfect match, you're asking for trouble. Well, there's no development of something different. There's no slack in the process, and things like that. Okay, so that's kind of the groundwork of what I want to talk about. Valuing, requisite design, talent, pull, strength. I want to talk a little bit about ways that we might measure is a bad word. No, actually measures a good word. I'm using it incorrectly that we may assess or count characteristics of organizations. These numbers, I wanted to put these up because Ron Cappel has a database of close to 60,000. This database is a little smaller, but these are numbers that we generate, and we generally generate them the same way. And if we generate them the same way, they should be comparable. We should be able to talk to each other about those numbers. Okay, so, for example, this is person to role relationship. This particular set of data is 4400 points of 23 different talent evaluations the first time that the organization did it. So this isn't a talent evaluation where you did it again the next year and again the next year. This is the first time, and I did that because there's some similarity there. They haven't gone down the learning curve yet. It's all beginner type trial, but what I found is 51% were requisite. And what I mean by person to role is, did they fit the role? Are they above the role, or are they below the role? Okay. Person to manager relationship. Are they one step above or one step below their manager or are they above their manager or equal to their manager? All right, so basically you could say that half the people are either above or below role and half the people don't fit their manager. And when you do the statistics, that says roughly 25% of the people have a requisite situation. Okay? Role to role is basically in the design. And the principle in requisite organization is that you want to design with one step, one step difference. And in that particular sample, 66% of the design was requisite. Let's see. I don't want to say anything else about that. All right? I think it would be valuable for those of us that have databases to put these numbers together because I think we're talking about 100,000 people, more than 100,000 people. And when I've talked to Ron and talked to Ulf, these numbers are reasonable. They're in the ballpark of what other people are seeing. All right? Now I'm going to take you down a path of thinking about creating some measures, and I'm going to kind of feed it one step at a time, okay? Organizations exist for a purpose. We express the organizational purpose through a strategy. The strategy necessitates that we turn it into some kind of design. We frequently do that design through functioning and thinking about term in terms of functions, and we build it with roles. So basically we have an organizational purpose that eventually gets translated into a set of roles. Now, I want to name something. I want to call for a certain volume of work. Right? And we're used to the idea of a job at a certain level. There's a certain amount of work there. All right? So I'm creating a title called a Volume of Work. And I'm saying that that's all the work in the organization, all the work that has to be done by the organization is the volume of work. That volume of work requires a certain amount of human capability. So conceptually, I could say here's a bucket that is the size of the work. I can say, here's a bucket that's the size of the talent pool, and I can begin to compare them together. All right? In doing that, I'm going to give one set of numbers and then we'll build into how we came up with those numbers. So we started using the term aggregate for meaning put together in a big way and a whole bunch of things together. Aggregate, talent pool, strength. And we have two points talent capability and work volume. It's these two points here. Volume of work created by the roles and the people that are in place to be able to bring that work to bear. All right, what I found with the same 23 population is that on average, people had 125%. 125% of what? The volume of work and the judged capability of all of the people that are on staff. Okay, does that make sense? The judge capability.
Speaker C Are you adding time spent together?
Speaker A I'm factoring them by felt fair pay. Okay, so in other words, I'm looking at the well, you'll see that? We'll see that. Okay, sorry to clarify.
Speaker D Does that mean that you had 125% on average human capability in comparison to your pocket of need?
Speaker A That's right. So I had 25%. Say again? Yes, I have a surplus of 25%. All right. Now, in looking at 20 some businesses, that surplus went everywhere from a negative 6% to a positive double what the strategy was called for. And then you start looking at the organizations and there's a story built with them. And what you seem to find is that if they're below 100%, the organization is struggling. Okay? If they're at 105 or 110, they're doing okay. If they're at 115 to 125, those organizations are beginning to be looked at as go to organizations as the place that we need to pull somebody from if we need help or if we need to get somebody on site for a special project. They had that space, and this is really interesting. I'll spend a minute talking in a little more detail. I had one firm that had grown through acquisition of mom and pop shops, all right? So they were across the nation. They had a lot of small activities and they bought those activities over a period of 20 years. And they left the mom and pop leadership in place. So that in each of those small shops, you had somebody who had started a business, they had purchased the business, and then over their lifetime, they began to age and grow, but they didn't change or they didn't use them. They were well up over 125%. So they had excess working capability and they were doing nothing in their strategy to make use of that excess capability. Okay, now let's go through an example of how to do this. So here we have three Stratum, and that's the Felt Fair Pay multiple. Now, this is not a precise this is an easy way to do it, all right? I'm not trying to say I'm extremely precise because I haven't done thirds of Stratum and I've done a couple of other things to make it easy to do this, all right? And to make it easy to be compatible across different consultants. Okay? So, anyway, stratum four, the felt fair pay. Multiple is two. Stratum three. The Felt fair pay. Multiple is one. And I know it's on the border, but I haven't treated it that way. I've said we're just going to use that because it makes some sense. And at stratum two, the felt fair multiple is 00:55. I've used zero five to make it easy to do. So you can do it in your head. Okay? But those are the multiples. So here conceptually here's, seven rolls. Seven rolls? Yeah, seven rolls. I use boxes to represent rolls and ovals to represent people. So when we see ovals. It's people. So here I have seven rolls. On these two rolls, I'm weighting them with a felt fair pay factor of one. So I have two units of work. Okay, makes sense. Makes sense what I'm doing. All right? At four, the multiplier is two, so I have another two units of capability. At stratum two, I have another. These four roles will give me another two role, two units of capability. So I have seven roles requiring six units of work volume. Does that make any sense, what I'm doing? You follow me? What I'm doing? Anyway, you don't have to agree with it. You don't have to agree with it, but follow it. Okay, so now if I put seven people in those roles and I match the people to the roles, I've got six units of capability, six units of work. I have 100% match. Now, if I knew that number, like the first major job that I did, we did 18 talent gearings in one organization, so they were the same organization. We could compare that information across the organization and see if it told us anything we're talking about. Once again, what are the norms? What will make a difference? All right. Okay. Now, it's interesting to look at what happens when you start moving organization around. So in this case, what I'm saying, we've got to start with the same seven, but now I'm going to take somebody out so we'll have a vacant role. So now instead of having two units of work or capability, we only have one. So you got six people with five units of capability, or 83%. The first time I did this, I was looking for ways to try to understand what happens when you're dysfunctional, what happens when you don't have roles filled, what happens if you have high potentials that are above the role, what happens? So trying to get an idea of, well, what significance would this be? Anybody's reaction to 83%, just you don't know anything other than that.
Speaker E Well, the only way the other 17% of work can come from is from level four.
Speaker A So now your demand on level four, you got 17% of level four's effort. That isn't going to go to level four work. It's going to go to level three work as an example. Okay? Now, what happens if you have a high potential where they're in this role at level three, but they really have capability at level four? So we got seven people with seven units of capability, six units of work volume, you got 17% more capability. So when you look at the aggregate strength, the one we started with, which means all the people and all the capability, and you divide it into all the work, you're starting with a number that is kind of useful in saying, what does it say about that business's capability? It doesn't tell you how well you've executed the measures that we first looked at. Really? Are measures of how well we executed Requisite here. It's trying to give us a gross idea to be able to look at kind of business unit size units and have a rough idea of where they stand from an organizational soundness. So judge capability over work volume. Now, the idea my background is manufacturing, okay? In manufacturing, you're always using variance reporting. Who's familiar with variance reporting as a general theory, general idea. Okay, so what you're doing is you're looking at the financial data and you're trying to attribute variances positive and negative to it could be to shortages, it could be to rate changes, it could be to quality issues, a lot of different issues. So I'm saying is there an equivalent in our organizational realm to try to get a handle around different aspects of how we're doing on the way we're filling the organization structure? So here's an example. I've got 879 roles on the chart, all right? Those roles are calling for 404 units of work volume. I've got 74 vacancies, which makes me short 38 units of work volume. So the work volume times for the filled roles, the work volume for all the roles, 91%. All right, it kind of gives me an idea of let's see, what are your thoughts.
Speaker C Work volume in your analysis, have you also compared if you have oversupply or undersupply, if you like, on different levels? Because it's one consequence when you have it on the top and when you.
Speaker A Said it's normally in your average was 125.
Speaker C But my thinking in top of the companies is an undersupply of capability.
Speaker A Okay, I acknowledge what you're saying as an important factor. I will say that the felt fair pay will take up a certain amount of it, but then you have the risk of not being able to execute at all. Okay, this is a start. This is a beginning.
Speaker E Glenn. The model does not yet take into account, does it, the compressions.
Speaker A Right.
Speaker E So we have all those roles that we have seen on the central chart in Requisite strata. But what happens if we have two roles and two individuals who have the same level of capability as the roles.
Speaker A Required in the same strata, and it'll show up because we're comparing the person's total capability with the particular role. So if you have two roles in the same stratum, it should show it.
Speaker E Up so it would not change the ratio. But arguably, one of those two roles is redundant if they're in the same yes.
Speaker A Now, remember, the whole reason for doing this is to try to back up and take a global look, because the other three measures give us very solid micro measures about that, say, what kind of action we should take. They show what you're talking about, they would stand out.
Speaker E I'm just wondering whether we can combine the two and actually say that because some of those roles are not needed, are redundant. Therefore, the volume, the total work volume should actually be less?
Speaker A I don't know. I have to try that to link those ideas together.
Speaker F Could it not be that if you're wanting to shift an organization from one to eleven higher based on the strategy, that there'll be times when it will be advisable to have what appears to be spare capacity?
Speaker A Because it's going to be probably absolutely. And that's the kind of question I'm more inclined to be seeking answers to is movement of the whole unit.
Speaker F Comes from an external analysis.
Speaker A This came from talent pool evaluation data where you're positioning role, extent, positioning of the organization, and managerial judgment of the capability.
Speaker F Okay. So this 91% will mean that the actual throughput of the organization will be 9% below what it should be.
Speaker A It's basically saying our strategy says we should have this many, this is how many we actually have. And this is the roles. This didn't take into account the human capability yet. This is just roles.
Speaker D I got ten minutes left.
Speaker A Okay, here's another way to look at it. Got 800 people on staff. Their roles call for 366 work volume, their current judged capabilities. So this is where that one came from. So we've got a talent evaluation coming up with that number, or 115%. So the judged capability of the bodies that are presently on board as compared to the total strategic image of the role is 15% higher than what the strategy is.
Speaker F That indicator is clear for me. Explanatory the other one.
Speaker A Obviously, it's not clear for me yet either.
Speaker F So you're in the current versus prerequisite situation? No, the second one. So the work volume that you are missing, 38 units is the result of an extant analysis.
Speaker A Yes.
Speaker F And the other would be the requisite situation coming?
Speaker A Yeah, this would be the organization as built by the strategy. Okay. This is how much we've filled to this point in time.
Speaker F Okay.
Speaker B Open positions.
Speaker A Open.
Speaker F Well, no, actually positions are 74 translated into workload.
Speaker A Right into work. Brian is 38.
Speaker C Yes, but also according to Andre's question, this is not measuring requisite, this is measuring workload and capabilities. Workload as an addition to what we measure when we say this is how well the structure is put together and.
Speaker A Fit to role and fit to manager. Yes. We got one more here. We have all the roles and the judged capability of the pool. Okay. This case a lot closer than 115.
Speaker C If it's very unrequisite, if you just shuffle around a little bit, at least you have the work power.
Speaker A Well, in one sense, if you don't have the percentage here, you're not going to be able to get to requisite. Okay. It has something to say about where you stand now relative to your ability to move toward a requisite structure and how much. If you're talking about three business units, there's going to be differences. It's going to give you some relative information.
Speaker F Don't you require a segregation of this data to better understand what is going on, because maybe you got, I don't know, surplus of capability in the higher roles, and you're having a deficit in the lower roles in the lower data.
Speaker A You have to get to this. I mean, eventually you have to get to these measures. Yes. Okay. But the other ones will give you a more global view of the let's see if I can go. Yeah.
Speaker E So.
Speaker B The things that you're asking about, we're really good at evaluating micro conditions, manager to person, role to role. One of the things that I think this starts to get at is how do we roll that up to a bigger level? Macro. This is an indicator, and it's a nice number in and of itself. What we need to do is start to tie it to other numbers, success criteria that we don't have at our fingertips, but we need to work with together. All kind of like your research, right, with respect to leaders of an organization versus success criteria. I think this starts to give us another way to start to look at that at a bigger level.
Speaker D So is it another way to possibly describe it like a scorecard?
Speaker A Well, it could be. Now, what we're looking at, we're at the stage before getting normed. We don't know exactly what norming looks like in this kind of data. This is really a proposal for the kinds of things that drop right out of the data that we're taking. I mean, many of us have the databases that will generate this kind of look. And if we compare notes with stories, we start to get some norming of how good or how bad the structure is.
Speaker C And you want us to start the thing? Yeah, we might end up with something else, but you can end up with this as well.
Speaker A It's a beginning. Yeah, it's a beginning. Okay. Any questions? Any other questions?
