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[S4E20] The Things We Get To Say

The caravan of refugees was very timely, as we've come to expect from these writers. The actual refugee caravan just reached America's southern border this past week, and things aren't going as well for the actual migrants seeking asylum.

[S4E20] The Things We Get to Say


Yeah, well, you know, I'm a chemical engineer. So naturally, that fits right into the world of HR and data, of course, an absolute natural transition. So I came to ADP as you just introduced me through my title through the Marcus Buckingham company and actually started with the Marcus Buckingham company, I think seven and a half years ago now. And because we are a small company did all kinds of things for them, including lead product development. And when you're small, you do everything, including working with sales and all kinds of things. But as ADP acquired as I kind of migrated and settled into doing actually my three favorite things, which is beautiful. And I'm so lucky to be able to kind of craft my own job, if you will. And that is I lead our applied research team. I lead our professional services team. So I spend most of my time working with clients and working with data and gathering insights and thinking about things we want to get curious about and learn more about in terms of the world of work, then I spend a little bit of time doing this. I spent the bulk of my career as an HR practitioner leading HRIT teams HR analytics, pretty much everything at a talent field learning and development, leader development, performance, management, engagement, all the things I spent a bit of time in academia and started my career as a chemical engineer in the pulp and paper industry.

Well, it's also it kind of speaks as well to benchmarks and we live benchmarks in HR, you know, whether it be you know, salary benchmarks, or engagement benchmarks, or whatever it might happen to be. And benchmarks are also a little bit tricky as well, because benchmarks are helpful. And they do give you context, that organizations and people and teams are unique. And so when we're comparing to benchmarks, it's often misleading because your benchmark your norm, your kind of where you happen to settle in might be very different than someone else's. And although we look at temperature, you know, 98.6 degrees Fahrenheit is that you know, the human when we say normal temperature, people run different. Some people run a little warmer, some people run a little cooler, just like organizations do. So I think we've gotten so used to thinking that because something has multiple digits after a decimal point, that implies precision. And that's not always the case. And you can take engagement as an example, or performance. Performance is such a great example of this, actually. But you measure someone's performance, and you say, Oh, your performance rating is a you know, 3.79. And that 3.79 is better than the person sitting next to you who has a 3.60 you know, performance. Really, I don't know if I can tell the difference between a three and a four, let alone a 3.79 and a 3.6. So we've, we've carried over this scientific precision of some things into the world of uncountable, and particularly we do that in the world of HR, because humans are you we're variable, we're very different. We're very unique. And it's led us quite frankly, down a path of a lot of not so great practices in the world of people at work.

Yeah, but but to be honest, what was before was either a vacuum. And we all know nature abhors a vacuum, especially the world of work abhors a vacuum, because people make up their own stuff for their own or like managers will make up rules or make up while their own their own law, if it suits them to make to make their lives as a manager easier. And so having those things having those measurements having those benchmarks, having those policies, give them something to hold on to. They may be, they may be terrible, but the lack of them is even worse. And I've been working with a lot of clients, especially lately, who didn't have, there was nothing. And putting in some structure means there has to be a change in culture, right? Because you can't just implement something, even if it's good. Actually, if it's good, it's probably worse implement something without change management without training without communications, because that will, you know, people will resort to their old ways, won't they?

I think to some degree, I kind of go to root cause, you know, I'm gonna put my engineer hat a little bit and go to root cause, well, like, what's the root cause of that? Like, how do we actually do some of these things like I'm gonna say, measuring performance or measuring engagement, or helping people do more better work, like, let's let's go to the foundation and not settle for mediocre, let's not settle for a bad practice, just because it yields a number that we might want to do something like, I don't know, inform compensation with perhaps, or promotion, or decide who we're going to riff or not, like the data that we use in HR is. So I mean, that one might even argue it's some of the most important data that we use in the world of work, because of the downstream implications, the downstream decisions that we use. I mean, we're impacting people's livelihoods with this data. And some of that data is not only poorly collected, infrequently collected, but some of it, quite frankly, it's simply not even valid.

Well, and that's been, I guess, the criticism of Performance Management for so long. Rightly so because we, we started this terrible expectation that you have to have at least two conversations a year around performance management. One is goal setting. And the other one is performance evaluation, when there should be and I know, this is where you go, typically, regular ongoing communications about what's expected between the manager and the associate and the employee. So that one can help the other, you know, one might have different might, one might have challenges, and the other might have solutions. One might have roadblocks, and the other might be able to pave the way. And it may not necessarily be the manager who paves the way for the employee, it might be the other way around. So having those regular conversations, and then documenting them and measuring them, I think this is where you're gonna go. Those are great things. But to me, there's a little bit when you get too regular, you get a little bit of artificial noise built in, because it becomes too routine, right? It becomes too familiar. And it becomes a checkbox, doesn't it?

Yeah, well, I think part of the problem is, is we're smooshing two things together, we're smooshing the get more performance with the performance measurements. If you go back to that what's measured gets measured, not what's measured, gets done, there, what's measured part, the performance measurement, part of that is a whole different process with different intended outcomes than the how we get more of it. So this conversation piece, you're right, David, I mean, you know this, because you know, our work that we do, that really frequent connections, really frequent moments of attention between particularly team leaders and team members are what moves the needle on performance and engagement. It's not the only thing, by the way, but it is the most powerful thing that we found. Great. Put that in a box, put a bow on it. That's the performance movement, performance acceleration, however, you want to phrase that. And the totally other side of the kind of world at work equation, if you will, is performance measurement. And we don't measure or I would say, at least our clients don't do this. We don't measure performance. To get more of it, we measure performance to know where it is to be able to see into the talent landscape, if you will, the organization. And we use that data to inform downstream talent decisions. So we don't measure the conversations. Those are between a team leader and a team member. Like HR in our world, we don't we don't go look and see what people are talking about or what that data looks like. We don't do any of that. That's a team leader, team member thing. And then fully on the other side of the fence on the other side of that wall is oh, let's go get some data. So we can see into the talent. Are there people that need help? Are there people that need support? And have organizations choose to use that data to inform downstream talent decisions like potential, you know, variable compensation, for example? Great, you can do that, too. However, understand that that data is not you know, it's not necessarily accountable in the world of knowledge workers. Like it's not a precise number, but it does give us some guidance around how team leaders are experiencing their team members performance.

We're practitioners though, Amy, we love data. And we love to try and measure things because we want to be able to help. We want to make better decisions using that data, right? So what, what, what's going on with this equation? What's wrong with the equation? What do we have to do to make the data better? Or the measurements better of the data of the transactions to make this more useful for us to make better decisions?

Well, weirdly, it's not making it more complicated. I think we've had history, if you will, that we can't we know something's wrong and so we make it more complicated. We add more complex models, competency models, all kinds of things that we try to get a number out of. And weirdly, it's not that that's the opposite. It's counterproductive. What we do and what our with our clients and what we recommend and what they what they do. That's why they we work with them, is actually kind of simplifying it. So if you think about what are the critical few things we need to know about employee performance? What are the critical few things and a great way to kind of peel this back, David is to ask team leaders, managers, the question of Do you know who your best people are? And of course they do, right? I mean, you you've been a leader, you've led people, you know who your best people were in your team? Everybody does? It's like, of course they go? Of course I do. And if you ask them why you typically get a very, very long pause. It's like, I don't know, you just you just know. And when you again, when you ask why. And let them pause and ponder for a minute, you get the same answer virtually every single time. And I've done this 1000s of times, it's how we did some of the original work and kind of checked our original assumptions around how do we measure people performance at work? And the answer is they get high quality work done when you them to get it done. So quality and productivity. And the second thing is we this thing we call, we call it teamyniess, because we didn't know what else to call it. So that that kind of softer behavior thing, we tried to capture it with competency models, but that didn't quite work and rating people against it. That doesn't quite work. So when you smush, all that kind of softer stuff together, we just call it teamyness because we didn't know what to call it. And that's it. It's those two things, can somebody get high quality work done? And I'm gonna use kind of an Amy term and say, Are they reasonable to work with? Like, that's it. And if you don't overcomplicate it, and don't over engineer that, it gives you some really interesting, incredibly useful data. Now you can ask people, team leaders, the people who know someone's work best to rate that you can say a scale of one to five, that works quite nicely. We love a five point scale. And you can get quantitative data from that. You have to be careful, because you have to understand that we're kind of trying to count the uncountable, if you will. And in the world of knowledge workers, we don't often have countables. 041b061a72

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