Mining Your Own Business Podcast

Episode 14 - Keep CALM and Create Change in Your Business with Rick Hinton

Keep CALM and Create Change in Your Business with Rick Hinton

We’re kicking off the new year with Rick Hinton, founder and CEO of Valerius Consulting. Valerius provides adaptive change management services, especially for data analytics organizations.

Rick and Evan discuss what change management looks like in the analytics world and why it’s necessary for growth.

We learn about the importance of the words “trust”, “deliberate”, and “gradual” as they relate to implementing effective change.

Rick wraps up by teaching us the CALM process for change management (Communication, Alignment, Learning, & Measurement) and providing practical advice for businesses.

In this episode you will learn:

  • How change management is synonymous with continuous learning
  • Common barriers to change and how to foster an environment of trust
  • The pacing of effective change within an organization
  • The CALM process for change management and how to apply it to your business (Communication, Alignment, Learning, Measurement)

Learn more about why we created the Mining Your Own Business podcast.

About This Episode's Participants

Rick Hinton | Guest

Rick Hinton is the founder and lead consultant at Valerius Consulting, delivering analytics strategy and change management services to forward-thinking organizations.

For over two decades as a technology entrepreneur and consultant, he has worked at the intersection of advanced analytics and organizational change, helping teams design, build, and deliver solutions in personal finance, investments, prediction markets, and enterprise analytics.

Follow Rick on LinkedIn Learn More About Valerius Consulting

Evan Wimpey | Host

Evan Wimpey is the Director of Analytics Strategy at Elder Research where he works with organizations to transform deficient data into tangible business value that advances their mission.

He is uniquely suited for this challenge by pairing his professional experience in management and economics at high-functioning organizations like the Marine Corps and Goldman Sachs with his technical prowess in data science. His analytics skillset was strengthened while earning his MS in Analytics from the Institute for Advanced Analytics at NC State University.

Evan almost always has a smile on his face, which is at it’s widest when he is helping organizations use data in innovative ways to solve complex problems. He is also, in a strictly technical sense, a “professional” comedian.

Follow Evan on LinkedIn


Key Moments From This Episode

00:00 Introduction
01:16 Rick’s background and why he founded Valerius Consulting
03:05 What is change management in analytics?
05:19 Change in data analytics, past and present
10:41 Analytics team structures and communication barriers
14:18 Building trust
17:54 Too much too fast? Pacing of change
21:42 The CALM process
29:12 Conclusion

Show Transcript

Evan: Hello and welcome to the Mining Your Own Business podcast. I’m your host Evan Wimpey, and I’m excited today to introduce our guest, Rick Hinton. Rick is the founder and CEO at Valerius Consulting, which is a consulting firm that focuses on the change management aspect of data science and analytics. So that’s been a theme that’s threaded throughout a lot of episodes here. A lot of folks are interested in. Excited to have Rick on the show today to talk. Rick, welcome to the show. Thanks for joining us.

Rick: Evan, thanks for having me.

Evan: Yeah, absolutely. Hey, to get started, can you give us a little bit about your personal background? And then you’re the founder of Valerius Consulting, so talk a little bit about Valerius.

Rick: Yeah. Yeah. So my background has been in software both services and products. Going back, you know, a couple of decades at least, we’ll just leave it at that. I’ve played a ton of different roles. Everything from sales, marketing, product, project management, managing offshore development teams. And from an industry perspective, I spent a fair amount of time in financial services and consulting into financial services. So that, I think that’s where my one, my love of analytics was really born. Building portfolio management, investment management tools. And then the other thing was the variety of roles that I’ve kind of thrust myself into forced me to adapt and change. And I learned a ton just putting myself through that and with a lot of bumps and bruises along the way. And so I think that really kind of informed where I am with the consulting I’m doing now. Which is, as you mentioned, was change management around data analytics. It sounds like a very, very niche thing. And it is I tell people that and they’re like, well, what is that? But it’s really something that I’m passionate about and I think there’s gonna be a huge demand for going forward.

Evan: Yep. You’ll get no arguments outta me. I completely agree with you. One of the things that we hear the term change management and in the analytics space broadly, there’s a few of those terms that are, you know, even artificial intelligence. Big, big data. They get thrown around maybe sort of nebulous terms. Can you put your own definition to change management? What do you actually mean when you say change management?

Rick: Yeah. So I mean, I’ll give you the kind of formal definition then I’ll give you kind of the way I’m thinking about it. Beyond that, I mean, the formal definition is a process by which organizations and teams plan for and adapt to. Keyword in there is “process”. And that’s, I think that’s probably one lot we’re gonna talk about today is form treating this like a process?

So that’s the formal definition. I mean, I think a way of thinking about this is really like continuous learning. So when you think about change and continuous learning, really I look at them synonymously. I mean, it’s, and I think. Honestly, I think it’s a better way to think about it and talk about it.

I think we use the term change management a lot cuz it’s a starting point for everyone to figure out what it is we’re talking about. But I think more importantly it’s what are we trying to do right? And we’re not just change for change’s sake. We’re trying to improve, we’re trying to learn, and I think that ties in really well with what people in the data science realm and analytics realm do. That’s what they do every day, is try to, you know, interpret output and make decisions and learn from. So making that continuous learning part of the way you think about change management is more or less what makes sense in this space, and I think overall, but I think specifically for the people that I interact and you interact with on a daily basis.

Evan: Yeah. Absolutely. That makes perfect sense. And I think we’ve heard it in a lot of our guests who are leaders within organizations trying to implement all of their fancy data and analytics things that they’ve done.

So, Rick, you’ve got a background in technology. You’ve seen a lot of different products and processes that all had some aspect of change. Now that you’re focused on data and analytics, is that necessarily different than other technology that have had to drive change in the past?

Rick: I think it is. I think if you look back to, let’s say, enterprise software, when it really started to take off in let’s say eighties and nineties change management then was really kind of technical training. So part of your project plan had change management at the tail end that entailed training people on how to use the software, so technical training. So that was change essentially back then. I mean, some organizations, you know, were taking it beyond that, but that’s more or less what it was. And it also made sense at the time because that’s what you’re doing, you’re implementing software that typically automated a process and people needed to understand how to use the technology to automate that process.

So you fast forward now, the technologies that we’re building go beyond that kind of just technical knowledge. I mean, it goes to critical thinking skills. Because it’s beyond just automation. It’s producing output that a lot of, you know, sometimes you don’t, you don’t even, you have no idea what’s gonna come out of the system or how to interpret it or how to make decisions based on it. So the critical thinking skills part of it is, in my opinion, is the huge difference. And that’s, it’s not a small leap to go from one to the other. Cause people can’t, I mean, you know, there was push, you know, there’s always pushback when people are forced to do something different, to learn something different because it instills fear cuz it’s unknown.
So that part hasn’t changed. But I think the change for experiencing right now is much more profound than in the past. And I think that the other thing is, you know, in getting back to kind of your initial question about what has change management and just thinking about it in terms of it’s continual, I mean, there, there you, there’s not a point at which you say, eh, you know, next quarter things aren’t gonna change. That’s, you know, it’s ridiculous. I mean, we’re literally living through a time period that is the most profound change in human. I mean, it just, that’s not a controversial statement. I mean, you look at like Chat GPT I mean that this stuff is astonishing and Dall-E and, and the other, you know, the image generation stuff. I mean, that’s really far out there. That’s not being implemented in companies right now. But, what if you pay attention, I know you do. The rate of change, like in technology and specifically AI is astonishing. So, you know, we gotta buckle up and just face the facts that this is not optional. Change is not optional. I mean, it’s just, we’re in for a heck of a ride coming up, man. And it, and it could be some really cool stuff. And I think that’s, that’s part of it. You know, what I, you know, am passionate about is, is that, you know, we have to make. Part of business process, the way you think and act and decide like the things we’re talking about today, they have to be embedded in that. So that’s, you know, that’s kind of the way I look at it, but it’s, yeah, it’s different in every way. You can imagine, man.

Evan: Certainly, I don’t think you’ll get much argument, certainly from folks that have been in the technology space and that now are in the analytics space. We’re recording this at the end of 2022. You’re probably listening to it at the beginning of 2023. And the amount of change, like the language models, the image generation models that you talked about are so different now than they were at the beginning of last year, and so it’s, it’s almost intimidating to try to keep your process change up to date with the technological change.

Rick: It really is. It really is. I mean, you, I used to pull a chart and give a presentation. I’d go to open AI and they track compute speeds. And I used to put that chart in and I’d update it and it was like, you know, from like 14 to 19 it was like 300000%. So like Moore’s Law was out the window. But now, I mean, it’s even well beyond like a year ago. And it’s like we’re, it’s interesting cuz we’re really experiencing what exponential. Like, we can’t, you know, we have, as humans, we have hard time wrapping our heads around that. But if you pay attention enough, I mean, that’s what we’re living through.

Evan: Yeah, exciting times,

Rick: It is scary, scary for some people.

Evan: Very much. Okay. So, if we think about an organization that’s trying to develop this process, that’s trying to make this change part of the way that they do business, you know, a lot of the analytics leaders that we’ve talked to have talked about how their team is organized and how they interact, excuse me, with their, with their business partners. There’s, you know, in my head, there’s sort of the two versions. There’s the centralized analytics like center of excellence versus like the federated distributed analyst within business teams. Does that change the way you think about change management or change in approach to how that process is the way you structure your team?

Rick: Not, I mean, not really. I mean, the players are all the same. It’s just kind of how they’re distributed. I mean, when I talk about the players, it’s, you know, the business folks, the technical folks, and the data science and analytics folks. And the challenge has always been that they have speaking the same language. So, you know, and that fundamentally gets to the challenge. The change challenge is they don’t understand each other. Those technical folks don’t understand the business problem. The business folks don’t understand what’s technically feasible. And then neither one of ’em know what those statistical guys talking about when he comes into the room, cuz he’s speaking yet another language.

That language barrier, if you will, is a big impediment to change because what it does is minimizes communication or limits communication. And then when you have a situation where communication is diminished, it’s really hard to build trust in those types of environments and a low-trust environment is just a really bad place to try to implement change.

So, you know, so I think the federated and the centralized and federated models introduce different challenges. But like I said, the players are kind of the same. And the different challenges are the, you know, it really has to do with the maturity of the organization. If you look at, you know, a fairly mature organization is, and this is an absolute, but it, they’re gonna have a little bit more centralized analytics cuz they, you know, the first few hires they have, they want to keep ’em all together. They wanna be all together cause they can learn from each other and it’s a natural place for them to be. It’s a centralized. But as, but the real action is out in the departments and the functions and the organizations. Ultimately, you know, what they’re trying to do, particularly with the federated model, is push more capabilities out in closer to the customer, right? Because that’s where you’re gonna get the best returns if you can have better decision-making at the front end.

So, that tension between centralized and kind of federated I will grant you that does create a different kind of dynamic. And it’s really, that’s the kind of organizational structure dynamic. That, you know, is non-trivial when particularly when you get with large organizations. But I think the, you know, the underlying problem and the kind of underlying principles and approaching change are still consistent.

Evan: Okay. Yep. Spot on. I like that you mentioned trust. I think. And I was practicing data scientist, a lot of data scientists listening to the show. I think sort of the horror story of “I built this really good thing and nobody wants to use it. Nobody trusts what it is.” I would imagine there’s several places where the trust can break down. I’m curious if you’ve got, is there like a typical, a typical roadblock? Let’s say your data scientists have, have built or have the ability to have the power and the data available to build a useful tool? What’s a common place where there’s, you see that blocker, whether it’s with trust or something else?

Rick: Yeah, I mean, typically it’s, you know somebody that’s gonna build a solution. They’re too often, they’re coming from it with a perspective, their own perspective of the technical solution. Like their idea of success is “I built this really complicated thing and they’re proud of it.” Right. And they should be. And they’re enamored with this thing that they created because “I’m here to create things like this.”
Right. And then, and I’m the same way, you know. I just, I get in, I still do get enamored. I got like a million gadgets sitting in my cupboard here cuz I just, you know, I love new stuff. I love, you know, it’s just, I’m drawn to it and consistently throughout my career in a, you know, particularly when you’re on like the front lines, like sales and marketing and you’re charged with pitching or selling something and you’re kind of doing it from your own perspective. I think that happens in, you know, with technical solutions, you get enamored with the solution and then you run into the business folks and they’re like, well, I don’t know how to use that. I don’t know what that does. I don’t trust this simulation model that you’ve built. What under the hood? And, you know, how that’s received by the technical person. You know, you suck. You don’t, you know, and it just, you kind of internalize that. So that I, that’s where I’ve seen a lot of barriers.
And what’s, you know, and what’s helpful is to have is not, have those conversations at like a, you know, free lunch point of a solution where it should be like a very, very long or fairly long conversation between the two teams. And that takes time and it takes patience and a lot of company, a lot of companies and people don’t think that way. And it’s you know, and, and it related to that is, is also when you think about change, is it is incremental and it is, you know, if you, and it takes time and you have to kind of build it slowly and that gets back to the trust. You know, you don’t snap your fingers and become trustworthy and garner trust. It’s a long, it’s a long process of meeting commitments. Right. And that’s, I think, that’s a key part is, and getting back to kinda what we said earlier about making this a process, is that, you know, it’s not something you’ll launch. You know, it’s not an initiative that you kind of plug in. It’s the way you operate every day. By doing it every day you’re gonna have a heck of a lot better chance of one, understanding people that don’t sit in your department. And two, building the trust that we talked about.

Evan: Yep, that’s a great point, Rick. It. You reminded me of a quote from Gerhard Pilcher, who’s our first guest on here. He is the CEO of Elder Research and he comments often on an organization’s ability to absorb change. And oftentimes when I think change management, I think trying to do change, trying to push it out there, try. We need to change and we’re not changing. I’m curious if you see the counter as often is that also a challenge a company or an organization is trying to change too much too fast?

Rick: Yeah, I think so, cuz it, you know, I think if you envision like this linear graph of effort and change and that’s, you know, how people conceptualize it. Where, you know, like you said, we’re gonna put forth this effort, gonna see this change in this next quarter and then we’re gonna do it again and see more change in the next quarter. And, really the way I look at it is it’s, it’s more like, you know, like a gradual curve where you’re not gonna see anything for months and everybody thinks nothing’s happening, right? And nothing’s, but what you’re doing is slowly building the foundation. And I think that’s where, I think that’s where one, this change, any effort to change fails because there’s expectations that are not in line with how stuff in one, it takes time. Right. And patience. And I think that between the linear expectation and the longer curve is really where the mismatch is.

And there’s another quote, if we’re gonna quote Gerhard, he said it the other day, we don’t mess it up. It’s like organizations need to slow down in order to speed up. I thought that was, I don’t know if he, where he got it from, but that I thought that was really good. I keep thinking about that a lot because I’m not the most naturally patient person in the world, and it’s just, you know, and you gotta take a step back and say that, you know, it’s hard because it’s like these organizations, particularly like public traded companies, have very near-term expectations about performance. There’s no question. It’s hard. And I think that’s, you know, getting back to what we said before is, is that’s why it’s like incremental, build it into a process and then, you know, see those results, those bigger results later on. But, you know, you gotta ride it out till you get there.
And I think, you know, I mean if you look at like one example that kind of did this well, I mean, Amazon would be, you know, it’s kind of a unique beast, but it’s a great example and Bezos just got brutalized for, you know, the first 10, 12 years. Just, you know, where are the earnings, where are the earnings? And he’s like, this is what we’re doing. This is what we’re doing. And that’s just a classic example of, you know, a disruptor and kind of a change agent, if you will. But he just wrote it out and he had these principles and applied them. And, you know, I think that’s a great example.

Evan: Yeah. That is a great example. I certainly can see the tension. We spoke earlier about the pace of change, the technological pace of change, and it follows a very different curve than the, they’re writing it out. They’re, the exponential growth just jumps. And it can be really tempting to, well, let’s find the newest gadget and throw the newest gadget. Let’s let ChatGPT just solve all our problems right out of the box. Awesome. Yeah, this is very good.

Rick, a lot of the folks that listen to the show are in an organization and this resonates. They’re trying to implement some change successfully. They’re trying to build trust in their analytics between their analytics players and their technical and their business people. If you could speak directly to them, I know there’s not like a one size fits all generic advice, but is there anything generally that you could say to them, folks who, who are locked on and say, Hey, we want to be more deliberate, we want to improve our change management process?

Rick: Yeah, and I think the key is the word is deliberate. So you know, we talk about, we call the CALM process, which is C A L M, which stands for Communications, Alignment, Learning, and Measurement. So that’s the process that I use for kind of building some structure around this, and there’s a structure and then there’s kind of the underlying principles that the, you know, you need to kind of keep in mind. One of which is the notion of like personal and professional development that this is what you’re doing. And that’s, you know, so that’s looking at. Looking inward, right? And how you do things, and how you interact, interact with your colleagues and your teammates. And then what kind of learning process are you’re putting yourself through. And then the other kind of overarching principle is just, you know, how measuring whether or not it’s happening. Because I think it’s, you know, just instilling some discipline into the process.

So let me back up a little bit and go through the CALM. So, C for communications is kind of the baseline. And the one thing with, the communications piece, and it, you know, on the surface it sounds, you know, everybody talked to, it’s like, I know communications. Yeah, I got the PowerPoint. I talked to everybody. They’re good. They’re not good. I mean, they’re, what happens is, and, and we’ve all done this, is we communicate out and we assume that people understand what we’re talking about.
And a lot of times we don’t even question and ask for any feedback. So one is, is it, A lot of times it’s PowerPoint and, and one thing I would push back on people is as a best practice is start writing things down. Start writing. I mean, cuz there’s so much hit, you know, you can, you can hide so many faults within PowerPoint where you can just gloss over so many things. So forget PowerPoint, sit down and write, you know, three or four, five-page executive summary of this thing you’re trying to do. Whether it’s implementing a solution, reorg your, whatever you, you know, you see as a central challenge. And the thing you’re getting at is why. it, what happens is, and this is in the umbrella of communications, is people do not clearly set the context for the change and what they want to do. And they don’t take the time to do it. And sitting down and writing is, is hard work and, but it. But once you do it, you’ll, you’ll start to understand where their flaws in your thinking. It’s also a better way to get feedback. So I would, I would highly recommend that people make that a best practice as part of their communications.
So that’s one piece. The other is just consistent over time and clarity and concise. Get rid of the corporate speak, get rid of the jargon. You know, communicate like you’re talking to an eighth grader or whatever grade you want to choose. But it’s, that’s the other thing is, and that’s hard too, right? I mean that’s, you know, we all fall into our traps of just kind of talking in jargon and then that doesn’t help you do the translation across stakeholder groups. Because you’re just talking to yourself and you’re just talking to your team. You know, and so the, that, so that must be the two big pieces on communication. And then I guess the other thing about communication is you, you almost can’t over-communicate. You really, you really can’t. I mean, yeah, conceivably you could, but it, nobody does. So I would, you know, keep that as a mantra whether it’s your own team or, or you know a business unit or whatever kind of organizational kind of element you’re in.

And then the Alignment part. So the communication is, think of it almost, you know, that’s the broadcasting, right? That’s like the one-to-many. The alignment is the more one-to-one. So that’s getting in a team meeting that’s getting in you know, a workshop that’s going doing like town halls. That’s where you’re really, and the idea there is you’re listening a hell of a lot, heck of a lot more than you’re communicating. So that’s where you’re trying to understand what am I missing? And that takes, you know, the other element of, from a leader’s perspective is humility. You know, you walk into the room, I don’t know everything, and I don’t have all the answers. And I can’t presuppose that I know, you know, all the issues you guys are facing. So that’s the mindset you gotta have walking in. And so the alignment part is lots of listening. And lots of paying attention and lots of capturing feedback and playing that, and then building that feedback into your communications. This is what I heard. So that’s the alignment piece.

The Learning piece is really about being very deliberate about what your expectations are of people. Because that’s, you know, when you think about what happens to change and where does it get off track is you’re not specific enough. It’s like, what do you want people to do? What are, what are you expecting of me? So the learning part is, here’s what I expect, and by the way, here’s a program by which I’m gonna help you get there. So make the organization making an investment in you as an individual to, and the, so the learning piece, I mean there’s two elements that are relevant to our space, which is one is skillset. I mean, you know, you need subject matter expertise, technical knowledge. So that’s, that’s a baseline, right? The other is the mindsets. So skill sets and mindsets are really around the learning piece and what’s critical. And then the mindsets get back to you know, get those critical thinking skills right.
How do you get outside of your routine in the way you think about problem? So that’s the mindset part. So that’s a whole different, you know, track of learning. And then the measurement part is the last one, which is, you know, since we’re we’re in the realm of analytics and data science, it’s like, well, let’s treat, like we talked about, treating like a legitimate process.

Well, let’s treat it like we would treat any other thing that we would build, which is measure the heck out of it. You know, measure, you know, look at leading indicators and lagging indicators, like leading indicators would be “are we really doing these activities that we said we would do as part of this change plan?” And the lagging indicators are “what are we seeing in terms of behavioral change?” So one client we’re working with is using Qualtrics for employee sentiment. Measurements and so they’re building the change metrics into kind of what they’re already doing around employee sentiment. So that’s you know, that’s a really interesting and, and welcome development. It’s very heartening to see that kind of level of discipline applied into it. So that’s it. Communications, Alignment, Learning, and Measurement is kind of the way we approach it.

Evan: Okay, awesome. Love putting a process around it. Love that you close with measurement. Just like, you gotta monitor your models once you put ’em in production, you gotta monitor your change process once you, once you build it out. Rick, thanks so much for coming on the time for taking your time to come on the show today.

I’ll leave a link in show notes for Valerius Consulting. Is there any other thing that I should pinpoint or that we should point to folks?

Rick: No, I think that’s fine. There are a few blogs on Elder Research’s blog that I would recommend you reading around change management that I co-authored with Lisa Targonski. So take a look at those and I think that’ll be helpful.

Evan: Perfect. Rick, thanks so much. I will link those in the show notes. Rick, thanks for coming on the show today.

Rick: Thanks for having me, Evan.

Evan: All right, take care everyone. See you next time.

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