Data Management and Business Intelligence with Jimmy Holmes

This is Making Better Decisions. I’m your host, Ryan Sullivan. Decisions are where rubber meets the road for organizations. Each week, we’ll be learning from people who are on the front lines of turning raw data into better outcomes for their organizations. This show is sponsored by Canopy Analytic, helping companies make better decisions using data.

Ryan: Welcome everybody to the Making Better Decisions podcast. Today I have an extra special guest, somebody that I’m very excited to have been able to get onto the podcast. Um, he has specialized in data and BI for the past eight years, probably, probably actually a little bit longer than that.

Ryan: He’s also spent four plus years as director of data management and BI. Thanks for joining. Earlier in his career, he spent 10 years in consulting to a variety of federal and commercial clients on lots of different data oriented projects, including GIS, [00:01:00] emergency response, environmental restoration, and more traditional construction projects.

Ryan: Please welcome Director of Data Management and Business Intelligence, Jimmy Holmes.

Jimmy: Insert applause. Yeah.

Ryan: Yeah,

Jimmy: All right. Thanks for having me. Thanks for having me.

Ryan: I’m super excited to have you, man. Um, you have a brain that is, uh, full of stuff that I want to dig into a little bit more, and I think the listeners will get a lot of value out of, so I’m going to, I’m going to hop right in and ask, what is one thing you wish more people knew about using data to make better decisions?

Jimmy: You know, so I talked to my team about this today too, even just to kind of get some perspective, but, um, I think the answer I’m going to go with just to kick it off is garbage in is still garbage out and, and we can tug on that and explore it or. See where you want to take it from there.

Ryan: Yeah, yeah, absolutely. Um, Obviously, I think when someone [00:02:00] hears garbage in, garbage out, they’re like, Oh, okay. Yeah, of

course. But for me, the place where that becomes like a real hurdle for an organization is when you combine the idea of garbage in, garbage out with the realities and the price prioritization and the time prioritization of being in a real organization.

Ryan: Like, tell me a little more about that.

Jimmy: Oh man. Yeah. I mean, the only point you, you would ever, uh, dive into a data is to make money or save money, right? I mean, it’s to create value and people spend a lot of money in that pursuit. Right. But. Sometimes the underpinnings are not what everybody thought they were. Um, you know, I think it’s pretty common that various, um, various senior leaders in organizations maybe kind of get wrapped up in buzzwords.

Jimmy: And next thing you know, they want to apply those buzzwords, but the underpinnings are still fragile. Um, I see that a lot. Saw it [00:03:00] countless times in my career.

Ryan: Hmm.

Jimmy: Um, yeah, let’s all leave it at that for now.

Ryan: Yeah. Yeah, absolutely. I mean, I think one of the things I’ve seen across my consulting career is that there’s at least a surface level idea that data can help, right? Whether you’re in a for profit organization, like you mentioned, and the organization goal is, is, you know, making more revenue saving on costs, right?

Ryan: It’s around profit. If it’s like a, you know, a nonprofit, right? Okay. Well, how do we, you know, find and better serve whatever our purpose is, you know, I think that. Folks have this idea that it can help, but there’s a lot of nitty gritty that’s involved. Um, I think, you know, you see a lot of, of tools and people out there who are kind of like, [00:04:00] oh yeah, you know, analytics as a managed service, or, you know, like a lot of these just kind of, you know, and unless there’s a meaningful understanding of not just the industry, but the organization, and there’s also Uh, pretty thorough amount of effort to make sure that the data is clean and accurate, and then is also structured for analysis.

Ryan: It’s really hard to deliver on that promise. And I’ve seen a lot of people who have been kind of sold the world and then they’re like, wait a minute, I still have to do a lot of this work. So you’re someone who’s been kind of in the trenches doing that for a long time. What are some lessons as far as, you know,

things that are worth investing your time in and cleaning up and things that aren’t.

Jimmy: it’s a hard thing, right? Because you can end up. Overgoverning and introducing paralysis of analysis, right? And I think that I’ve seen that too, right? You overthink [00:05:00] it because, you know, you know, there’s traps and landmines to watch out for, but I think you almost have to gauge each situation, but but process discipline.

Jimmy: I think is a very underrated thing. Um, you know, I was just on the phone with my boss earlier today, right. And we’ll not get into specifics, but you know, when you peel back the onion, sometimes you find out that there’s not actually a process. It’s an idea of a process and it changes as the wind blows and that influences business outcomes, right.

Jimmy: Or business decisions, I should say. it’s almost like consider the situation and just take pause and think about things for a second, right? So right now I’m in a role where we’re, you know, central IT, we’re kind of responsible for data for the organization, but I’ve been involved in countless projects where you’re on the.

Jimmy: The, the outskirts of that, you know, executing and you’ve got like your little fishbowl and what applies there might not necessarily apply in a central way. Right. But you can still see it as projects grow and something that, you know, I [00:06:00] used to just be responsible for kind of gets handed off to somebody else.

Jimmy: And. Um, you know, things that I took for granted or assumptions I made, um, don’t, don’t translate right. And before you know it, you’ve got a mess on your hands. But, um, yeah, I, I’d say take the time to think about the situation and, and what makes sense. I think, you know, instead of getting sucked up, like you said, I get countless emails from, from vendors to the promise, the world and all this.

Jimmy: And then the two biggest hurdles I see time and again, is like you said, they don’t know our business. And Dataprep. And huge amounts of money gets spent learning our data. And then when they get done, they’ve run out of funds. They can’t really tell you something. And they say, Well, what we’ve learned was, you know, something that, um, you know, wasn’t really of value to us in the first place.

Jimmy: That, you know, sometimes, I mean, sometimes we, you know, sometimes as the fish, we bite on that. Uh, and, and we [00:07:00] kind of get the same results. And sometimes we don’t, but. Yeah, I mean, I don’t know, you could take that in a million directions, but it’s, it’s very circumstantial too, you know, um, so,

Ryan: I think one of the things it kind of connected to points, uh, in a new way for me, so one of the big things that. I preach that you just mentioned is what, what is the goal? And like you mentioned earlier, like, let’s take a for profit business. That’s a little bit more straightforward, right? Their goal is to make more profit, to increase medium to long term shareholder value, hopefully, right?

Ryan: Hopefully it’s not short term, but like in general, right. To like increase the value and the profitability of the business to make more money. And one of the big things that I see is lots of times we think about, okay, well, that’s the business strategy. Maybe there’s like some specific ways that we’ve decided [00:08:00] to go about that. Some organizations and folks that I see kind of talking out there in the talking head of sphere, they talk a lot about all this data strategy stuff. And I think I get what they’re going for, but what that’s resulted in is a lot of people who aren’t, you know, working full time in the analytics space, thinking that data strategy and business strategy are two separate things. And here’s what the organization is doing, and then separately, like, here’s some stuff that we’re going to do with data that, like, might result in something cool, might not. Even if it’s cool, does it make money? And I try to always talk about data and all of the stuff that we use to work with it are just a set of tools to help an organization achieve its objectives, whatever those may be. And when I combine that with what you were just talking about, which is, okay, well, every, every business person in every [00:09:00] scenario knows that it’s like some sort of optimization, right? There’s like a trade off between how much time, effort, and energy should I spend on this for a return? That’s kind of also unexpected.

Ryan: And one of the things that I think might help the listeners a lot is there’s no way to know what things I should invest in or how much if I’m not directly tying the work that I’m doing to some sort of business outcome. And if we’re just doing some sort of investigation, like you mentioned, it may result in something it may not. Having a clear business strategy and being able to, as you said, tie all of the data initiatives to that is critical for knowing where and how much you should invest in some of these processes. So, one of the things that, just from knowing you for a little while, I know you’ve done a really good [00:10:00] job of, is striking that balance. Do you have any advice for anybody else on how they can, you know, in a specific situation, use the business

strategy to try and make effective decisions on what they should work on and what they shouldn’t?

Jimmy: you know, I mean, I can kind of, maybe let me come at this this way, right? So, In the most recent case, right, so the role that I’ve got now, for us, you had very clear line of sight to, to value, right? So there wasn’t going to be like a, if we do this, and if we do this, and if we do this, and if we do this, you know, here’s how we get to the bottom line.

Jimmy: It was real straightforward. Um, If we go and do this, you know, we, we free up a ton of capital immediately, you know, and that kind of seeded the group to demonstrate we, we knew what we were doing. Um, and then it let it sort of snowball forward. Right? And 1 of the other things I kind of had in mind as we were, you know, talking about maybe, um, that 1st [00:11:00] question was.

Jimmy: You know, and I, and I kind of just want to tap on this and then get back to what you just asked is, you know, when you do and you deliver that immediate value, take that value and, and reinvest it, right? Like

Ryan: Hmm.

Jimmy: don’t, don’t use it to kind of suck it out of the business and go, you know, deliver it immediately back to shareholders.

Jimmy: I know shareholders don’t want to hear that from somebody, but, but the reality is if you do that right, any startup, if you immediately start paying yourself, you, you know, you, you run yourself out of business, right? And you’ve got to strike that balance between. What do we take out and create as value?

Jimmy: And what do we use to create more value? Right. Um, but, but I think that that’s something where if you’re. If your leaders kind of decouple business strategy from data strategy, you kind of see that happen too, right? It’s okay. Well, they do this thing over here and you know, pick your, pick your department.

Jimmy: They do this thing in it, but there are cost centers, us and this and that really the business strategy is X. And, and I think that’s probably [00:12:00] for folks that maybe have seen some level of success that can kind of become sort of like a ceiling for you, unfortunately. Right. And it’s figuring out how to kind of navigate that part of the environment.

Jimmy: Right. And I think it, you know, In my opinion, that’s when, you know, there’s a little bit of politics that start to get involved in some of the things that are not just concrete, you know, um, tables and measures, right? It’s, um, it’s working with your stakeholders to say, hey, let’s think about this a little bit differently.

Ryan: Um, how can we continue to create more value, right?Yeah, absolutely. I mean, I think that, you know, when I first got started consulting, I was doing a lot more training. Of people just cause kind of where I was in my life. I was younger and I could travel and I wanted to travel. And so it was fun. And I got to, you know, to do a lot of that. And one of the big things, you know, I like to think that it was, you know, more value add and more exciting, but it was a corporate training.

Ryan: So, you know, it is what it is, but [00:13:00] I always tried to start with the, the value proposition of, you know, your goal here is to buy five minutes of your life back at a time. And. While that was very much on an individual basis when I was training groups of individuals, when you start translating that up to more strategic levels of an organization, I think it’s the same thing. It’s this idea of, hey, this good decision put you five steps out in front of where you are. Why don’t you take the value of two or three of those steps and reinvest that and making sure that the next decision is better and starting this kind of like, like you said, snowball effect where you’re moving the whole organization forward and, you know, this, this actually Gets me thinking a little bit about something else that you mentioned.

Ryan: So you, you talked about how your current role is focused on kind of centralized BI. So analytics as a function for the [00:14:00] organization, when a lot of these modern data tools came out, they were mostly being used in the beginning by. non IT folks, right? The IT folks had their big enterprise tools for analytics and BI. They tended to be big and expensive and slow. And so there were all these, you know, the cost initiatives and yada, yada, yada, all this stuff.

Ryan: And so in the very beginning, it was just kind of us in shadow IT, like getting some sort of database access and building something in, in PowerPivot or, you know, in Power BI once it had come out and, you know, some of the other tools that are out there. And. I think because of where the modern data tool revolution started, there was like a big push towards central, uh, towards self service. And over the last like five to 10 years, that has, I would say on average, bit most companies. And what we’re realizing is that there needs to be some sort of blend of, hey, for the big, really important reports, we can’t have six [00:15:00] different revenue numbers. Like these need to come from a

centralized place. One of the other things that I, I just know about you is that you’ve been instrumental in also helping to enable a lot of your users to do more of the digging in themselves.

Ryan: And you’ve. focused a lot on building data culture, which I externally assess you at being very successful at. How have you balanced and, you know, what are some of the pitfalls other people can look out for in this kind of balance between how much do you centralize? How much do you give and empower to others with self service and kind of a more mature landscape?

Jimmy: I think you do want to strike that balance for sure. And I think it’s, and we, we, we did, uh, we did a motion a few years back to try to, um, go from, we were actually the result of a merge at the time, right? And try not to get into too many specifics, right? But, But when one company is doing centralized and the [00:16:00] other one’s completely decentralized, that’s an interesting thing.

Jimmy: Cause now it’s not a pendulum swing. It’s two pendulums coming at one another. Right. And then what, what, you know, almost like that little kind of tick tock, tick tock thing, uh, what, what ends up being the result of that? Um, you know, we tried to strike what we thought was the balance a few years ago. Um, I think, you know, companies in general would benefit, I think, from an investment in some basic.

Jimmy: Um, you know, I would almost call it like guru level training or whatever, but some of that exposure finding, you know, kind of, you and I had talked about this years ago when you were teaching classes and stuff where, you know, finding those folks who you can teach them a concept, it plants a seed and then they turn it into a flower, right?

Jimmy: Finding those and getting them seated throughout the organization, I think is very, very, very important. Um, because yeah, it’s almost like thinking analytically is almost a position and not. [00:17:00] And I think in the average person’s mind across a company, you know, and some people maybe implicitly do it and you get your folks over in finance or your folks over in supply chain, HR, whatever it is, they, they might wear that role and not realize it.

Jimmy: But then if they were to realize the role, all of a sudden, you might see, you know, data stewardship kind of go up a little bit, but just. That something to kind of move in that direction as opposed to that’s IT, IT takes care of it, right? Um, but again, I think it, it is circumstantial for everybody. So, I mean, I think it’s good for your audience to know that there isn’t going to be a one shoe, you know, fits everybody sort of an approach here, but, um, you know, we were

looking and, you know, there’s some cultures where you’re full of your Excel gurus who might, you know, lend themselves to some of the Microsoft products pretty quickly, or, or, or even picking up some of their competitors, but.

Jimmy: There’s other companies where you don’t have that. You know, you might have some generational talent that’s still kind of almost even computer averse, right? I mean, I think that’s slowly kind [00:18:00] of going away, but I mean, there’s a full spectrum, right? And, um, you know, I think of other people, I know friends and family and the environments they find themselves in.

Jimmy: And it’s like, you know, people don’t realize that we all do work with data. And again, it’s not a, it’s not a title. It’s a, it’s another hat. We all kind of need to wear, you know, just no different really. I’m supposed to be, uh, you know, accountable and adherent to, you know, purchasing policies and various other policies.

Jimmy: Well, you know, there’s policies there too. And what do I need to do to kind of help, help the organization out? Right. Um, not to ramble too long on that, but man, yeah, you, we could talk forever about some of these topics.

Ryan: not, not at all, man. I thought that was really valuable. I mean, I think what I’m kind of picturing my, in my head, you kind of painted this picture for me is, and again, I, I really love how you’re talking about not just like, Hey, here’s how to do it, but like, here’s how to think about it. If your organization is different.

Ryan: So, you know, making [00:19:00] that investment in finding the folks. that have that natural knack and desire to learn more about data and empowering them and getting training for them. And then the folks whose job responsibilities and skills don’t match up with doing data work on their own, having that be centralized so that you kind of have this mentality of everybody has what they need.

Ryan: And the folks that can go out and be value add and bring their subject matter expertise from their part of the organization. We’ve hopefully identified, trained, and empowered those people. So it really depends, like you said, who’s in the organization and, you know, are we going to invest the time in finding those hidden gems and giving them the love they need so that then that takes work off of everybody else.

Ryan: And it also gives us the opportunity to harvest the, you know, department or, you know, subsection. Specific knowledge that they have that

might be hard to replicate in a centralized fashion. [00:20:00] Um, you know, one of the things from your answer that popped up to me is, you know, you’ve been doing this stuff, right?

Ryan: Not just data and analytics, but data and analytics with some of the modern tools for a while. Like you recognized the value add of some of these tools versus some of the old BI and analytics things that were, you know, out and available 10 years ago. Or so years ago. What was it that caused you to see that?

Ryan: Like, how did you sniff out that there was kind of a revolution coming?

Jimmy: Oh man. Um, interesting question. I would probably say I was a beneficiary of just my career path in general. Right? So I had seen so many different clients and use cases, right? That my career kind of became more about a focus of what ultimately would be transferable skills.

Jimmy: Right? And. [00:21:00] And you, you see these things as they come out and I’m the type of person, you know, anytime you learn a new trick or new this or new that or whatever, I kind of sort of go back and almost replay my life and say, would this have been, you know, any different? Right. And what I’ll say, I think, you know, not to get specific about tools, but most 365 nowadays.

Jimmy: Right. So, you know, I mean, PowerPivot, right? And things I was doing at the time that lent themselves to it. It was sort of like, Oh my gosh, if I would have had this. And again, it was just this project, this project, this project. And you were like, okay, there’s something here. This isn’t just, okay, this is useful to me right now.

Jimmy: Right. And then the same thing with Power Query, but I mean, you know, we’re picking, I’m picking a product in reality. It’s, it’s, um, It’s a tool that’s very well built, but it’s a, it’s really indicative of a, of a process and an application to say, get this closer to the end users, right? Um, again, and just replaying that over countless projects and saying, if I’d had that, the [00:22:00] countless hours writing VBA at night or doing these other things to try to make data stand on its head or do what I needed to do, right?

Jimmy: You say, okay. That would have changed the, you know, the, the, the course of my life. It lived nothing else that would have freed back up countless of the, you know, non paid work hours,

Ryan: Yeah.

Jimmy: you know, um, but I, I think it was that, right, it wasn’t anything earth shattering. And at the time it was introduced, right.

Jimmy: The, the tools that I’m using most of the time now, right. They, they were introduced in Excel and I think it was a brilliant strategy at the time. It, obviously we know it, what it morphed into. Um, And, and I think that, you know, um, you know, to the extent that, uh, I’m not really here to endorse Microsoft, but Microsoft sort of delivered on that promise.

Jimmy: I think they’ve done a good job. It was, it was a brilliant strategy in my mind because, you know, again, it was always sort of these folks in it that you’d talk to, they’re trying to use a language with which you have no familiarity whatsoever. And, and, you know, I think the other thing that [00:23:00] was important to kind of let me know was when I could jump on to try to self help and learn.

Ryan: Hmm.

Jimmy: I’m learning in, in English, not learning in even more technical terms that I’ve got to go look up, you know, and, and kind of creating like a fractal sort of pair, you know, pattern for research, right? Like, well, what is this, but what is this, what is this? Um, yeah, I mean, I think it was that just going back and replaying it and saying, okay, this is my aha moment, right?

Jimmy: Like I could have used this, Countless times and been of more value to myself, more value to my company. And again, I was a consultant before more valiant, valuable to the customer, you know, um, man, yeah, you look back and things where, okay, we used to get information updates once a week could have been daily

Ryan: Yeah.

Jimmy: the better decisions that might’ve been made and all that stuff.

Jimmy: But anyway, not to, not to ramble on there, but yeah, it was one of those kinds of things that was playing back my life. With through the lens of, you know, something new that you’d been exposed to. [00:24:00] Right.

Jimmy: And obviously your course when you taught it, obviously, you know,

Ryan: okay. Thank you. Thank you. But you know, it is, I mean, I think a certain amount of this happens with early adoption of, of a

also kind of started my journey mostly using Microsoft tools. And the main reason for that was, was Excel. Like you said, I think, you know, I was working at a telecom company at the time, and I just kind of stumbled.

Ryan: Upon it, you know, I was doing, I was kind of in a, in a data oriented field, which made sense for me. I mean, I went to school for math, like it kind of, you know, but it was more finance actually, it was an FP& A team. And, um, you know what started it? You’ll probably get a laugh out of this. I was just trying to make a pivot table.

Ryan: Off of something that had more than a million rows.

Jimmy: I remember this.

Ryan: that’s how I found PowerPivot back in the day. It was, I was just like, I had more than a million records of [00:25:00] data. Cause there’s like, you know, telecom it’s like, well, how many phone calls were there, a lot of phone calls, you know? Um, and I was just Googling how to get more than a million rows into Excel.

Ryan: And they were like, Oh, you can just like open up this window. And I was like, What, what window? And then like you open it up and there’s like all of these like suites of tools, like built right into Excel. And I was like, what is this? Right. And it was, you know, there were a couple other people in the organization that were, you know, doing it too.

Ryan: I was very lucky to just kind of be in the right place at the right time. But you’re absolutely right. It just kind of opened my eyes to the. You know, just from a simple little mistake. And once I saw it, I was like, holy cow, this stuff is extremely powerful. And you’re right. Then I think one of the, the biggest things that differentiate it, because there were loads of tools out there that were powerful, the differentiator was that this one had a very [00:26:00] natural kind of grow up story within it.

Ryan: So I could come in and be like a. Mediocre Excel user. And then the stuff that I was learning used mostly the same functions. There were definitely some new concepts for sure, but it provided me a series of baby steps as opposed to just like rock climbing up a cliff and then, Hey, you’re here now. speaking of large quantities of data, your industry has just swaths.

Ryan: One of the things that has been very cool from, you know, talking to you and knowing you for a little while is this, I think in no small credit to you, but

you know, your organization at large has definitely adopted. You know, that data culture we talked about. And so you have, you know, with the IOT revolution, just [00:27:00] like massive quantities of records, right? When you, you know, when I think a lot about it, like as soon as we start involving, you know, lots of sensors and these sensors can sometimes be flashing multiple times a second, right?

Ryan: It just gives you the ability to have a lot, a lot of information, but it’s a double edged sword because now you’ve got a lot, a lot of information. So. As, you know, the, the data culture has grown and the amount of data have grown, what are some of the growing pains there as far as, you know, getting more people turned on with it?

Ryan: Like, how do you, you know, all of that stuff?

Jimmy: Man. So I’ll answer that two ways, right? So we’ll, we’ll get back to the IOT thing, but I think the, the other side of the sword to comment about, like you said, sort of that low barrier to entry and you’re not climbing a, you know, a rock wall, but you’re, you’re growing with a product, the, the other side of that is it is a low barrier to entry.

Jimmy: So [00:28:00] people can come in and they can really kind of make a mess. And that’s something that, you know, every company, um, Every company that, you know, goes to try to decentralize in some way, shape, or form will have to figure out how to mitigate for that. Right on, on the IOT side of things. Yeah, it, it’s its own challenge.

Jimmy: Um, you know, we’re, we’re gathering again. We have to limit what we do. Right? I mean, there’s just what’s feasible and what, what do we believe has value and things like that. Right? But, um, you know, we’re collecting on the order of, you know, 7, 10 billion records per month, um, to try to make sense of. And the, the tools you have to use for storage are different than the tools you would use if you’re just dealing with, you know, homegrown applications and, you know, things like that.

Jimmy: Um, but man, the growing pains. Yeah. The datasets are massive and, and they do fit, but what, what you start to find, we’ve definitely gone through this bit and, uh, you know, [00:29:00] You provide that we’ve democratized data. That was another fun buzzword for, you know, a few years. And you, you put that in the hands of other folks, but then there is, there is still a set of, I’ll say, best practices and working with stuff.

Jimmy: Right. And, and your average citizen data analyst who doesn’t go nerd out, probably like guys like Ryan and Jimmy, right. Learn new tricks, say, Hey, there’s gotta be a better way, you know, challenge themselves to save those five minutes, but they just kind of brute force their way. You hear it all, you know, my computer’s not big enough.

Jimmy: It’s not strong enough. I need my own cloud resources, this, that, whatever. And in a lot of cases, what, what you really need is just to look over your own work and say, can I, You know, can I build a better mousetrap, um, without, you know, spending days, weeks,

Ryan: Yeah.

Jimmy: right? Um, we, we’ve definitely gone through that sort of growing pain.

Jimmy: I mean, people, you know, and not to get into too many specifics, but you know, you open up these [00:30:00] files to try to help and you see where there’s been, you know, 15 cascading merges on tables that are just monstrosities in the first place. And you’re like, that data never even needed to be merged, right? That could have been related, but again, you’ve democratized it a bit.

Jimmy: And that’s that skill gap shows itself, right? And then you have to kind of make these decisions and say, okay, well, do I educate them a little bit on making a model? Do I just get them out of this pinch? You know, what do you do? There have been countless, countless things like that, you know? Um, again, that’s the drawback.

Jimmy: And that’s why I think companies sometimes want to centralize a bit because some cultures don’t want those headaches, you know?

Ryan: Yeah. 100%. Yeah. It’s the balancing act.

Jimmy: Yeah, and you stymie creativity though, right? If you go in the other direction. So, creativity and velocity, frankly. So, yeah, I don’t know. It’s an interesting challenge. I wish I could say we’ve mastered it, but, uh, yeah, the battlefield’s always changing too.

Ryan: Yeah. I mean, one thing on that front, right? Like as [00:31:00] you know, the data culture has grown as the amount of data has grown, whether you’re out there doing training or you’re doing things for folks in a centralized environment, right? You need, you need resources. And one of the things that I

assess you to be as like an Excellent team builder and for anybody that’s out there listening that is saying, Hey, like I want to make better decisions using data.

Ryan: I know that, you know, we’re going to have to start with some sort of like guru. If I don’t already have that, maybe, you know, the listener is that person themself. What are some of the lessons that you learned from being, you know, a data and analytics? How can someone else build a good data team?

Jimmy: I think the most obvious answer is don’t just focus on skill, um, that people walk into the door with, especially, right? I think team chemistry is [00:32:00] extremely underrated, extremely. And that, you know, you can have people that can put that bullet point on the resume that they’re a team player, but, but we all have our personalities and this and that, and you know, the best, the best data junkie in the world who never wants to interact with another human being is probably not going to be. Highly effective on a team, right? I mean, that’s, that presents a challenge, right? So I don’t know. I look for characteristics. It’s sort of, you know, one of those books I probably read years ago, you know, find, find the right people to get on the bus and then, and then go drive it. but from like a personality standpoint and aptitude standpoint, um, You know, get to know the, the human and not just the skill, right?

Jimmy: again, I could talk for hours about that, right? We’ve got a limited podcast, but I mean, I, I try to do that. I try to make every time I interview folks, I try to make it a blend of Q and A about what they’ve said about themselves. Um, a little bit of, you know, uh, demonstrative of competencies, you know, however we kind of get to [00:33:00] that, but then I want to get to know you as a person, right?

Jimmy: You know, and it’s not just ask the hobbies to check the box. It’s. You know, ask the hobbies to get to know them. And I mean, fit is so important. It’s so important, you know. You look, you know, the best teams in, in the NFL don’t have nothing but quarterbacks, right? Like you have to assemble those roles and all that sort of thing.

Jimmy: And, um, you’ve got to think about that. It’s not just skills,

Ryan: I mean, I don’t know that I’m as qualified as you to say, but I think. You know, it rings true to me in my experience. I have, you know, obviously you have to like screen out people that don’t have the technical aptitude. That’s just kind of table stakes. But once you have people that you can assess have those, you know, technical capabilities, or at least they have the technical chops to

learn the capabilities, because those are kind of equivalent You know, there’s this whole other [00:34:00] slew of things that When they get overlooked many times, those are the situations that I’m, I’m brought into cleanup. you know, some of the things that I’ve found in that area are number one, the like data thinking that, you know, just like the person that has that data mindset is actually, these people are hidden everywhere. You know, I have met people who come from every part of the business. You know, you can be like a data and numbers nerd like me, and I’ve gone to college for math, and it was kind of an obvious next step for me.

Ryan: But most of the people that I’ve met, it wasn’t that they were, some of the best that I’ve met were kind of like business people first, and they worked somewhere within the business and they were just relentlessly focused on. on making the business better. And, you know, I think cultural fit is a slightly separate point from this, but like [00:35:00] excitement and enthusiasm for learning and not just like, Oh, I know how to write in 15 languages.

Ryan: Right. But like impact based learning is just You know, I will take an ounce of that over like a pound of, you know, super technical aptitude. Cause that, that person will go out and learn anything they need to.

Jimmy: I mean, you know, not to, I’ll tell this for, you know, maybe to kind of be a bit more relatable to the audience, but you know, I think of when I really kind of had a point of inflection in my own career, right? I was working, we were authorized to work seven twelves, okay, which is pretty demanding. All right.

Jimmy: So that’s seven days a week, 12 hours a day for people who never heard of that. Um, I was putting in about 90 to a hundred. I was youthful and I, you know, endless energy at the time. So it wasn’t as big of a deal, but, but there was a lot of, Yeah. So, you know, you sort of, you sort of clash swords on the project, you know, 7 to 7 were the hours.

Jimmy: [00:36:00] 7 to 7 you went after it, but then after that you had all these other ancillary functions you had to do and they were all around, you know, analyzing, making, you know, basically prepping for the next day. And, you know, I’ll never forget the, the, the gang would come in. It was, it was like a field type project and the gang would come in and drop off their, we were using papers at the time, right?

Jimmy: We weren’t even digital, love it. Um, so, you know, and I was chief key in grunt and then also the person that had to make sense of it and all that sort of

stuff, and they drop off at seven, they’d go get dinner and I’d be done at 10 o’clock, right? And you’ve missed, you’ve missed, you know, again, you’re, you’re not at home.

Jimmy: You’re not cooking, you’re in a hotel. You know, you’re like, you know, the necessity sort of drove it for me, but it was, I want to eat dinner, you know, so, so I’m going to stay right. But I mean, that was the reality of it. Right. And it was. Stay till 1030 and try to save myself five minutes and then tomorrow I’m going to take that five minutes and research something for a little bit more and, and again, it’s sort of [00:37:00] snowball it and, and at the time I was just trying to eat dinner, like literally, but then it, it, it turns into, if you’re, you know, again, I, I’m blessed, cursed with a voracious appetite for learning, um, you know, but again, that, that not only made that project more sustainable for me, but.

Jimmy: I mean, it, it altered the trajectory of my career, you know, so, so not only for the current leaders of today, but for people who may not be leading it, you know, how do I get to that next step? It’s like, you know, be devoted to learning and, and applying, you know, those two things I think go hand in hand. And, you know, the, um, the chips tend to sort themselves if you let that happen.

Ryan: Yeah.

Jimmy: so,

Ryan: Yeah. There’s one thing that you touched on there that I think like you and I both know what you’re talking about, but just for the

Jimmy: oh yeah, sorry.

Ryan: I want to say, you know, that seven to seven that you were doing, that was pretty much [00:38:00] full of like data entry and manual data management, right?

Jimmy: It was, there was a healthy slice of that pie chart for sure. There was other stuff too. It was, you know, on the phone half of those days, firefighting. Again, we weren’t digital at the time, so people were calling in saying, what was this, where was that last, you know, kind of.

Ryan: Yeah.

Jimmy: But yeah, absolutely. It was, it was, we were authorized to work 12 a day.

Jimmy: I was probably working 15 and there was definitely a full business day devoted to handling data, right? Whether it was entry or, or analyzing or whatever, a full business day, but some other stuff kind of piled on every day. So, you know, um, again, you know, but again, necessity, necessity is the mother of innovation.

Jimmy: Isn’t that how that, that quote goes? Not that I’d build anything innovative, but it, it, it is. Moved me along, you know, um,

Ryan: Yeah.

Jimmy: it just paying it forward.

Ryan: That’s exactly. You know, like being, you know, being kind to your future self. [00:39:00] Um, you know, I think that the, when we talk about buying five minutes back of your, your life, right, what, What I really think of when I hear that is, you know, it’s now 2024. If you are doing something that is both manual and repetitive, a computer should be doing that. And that’s the big target. You know, if I can take some time, even though, you know, oh gosh, it might like push me over or whatever, you know, like if I take that time and I automate some portion of that, that’s the value. Right, it’s not working 5 days today so I get 5, you know, 5 minutes today so I get 5 minutes tomorrow.

Ryan: It’s spending a half hour today but then I get 5 minutes per day forever back. And that, you know, like, it’s that manual repetitive stuff that I just want to kill with a vengeance.

Jimmy: Yeah, absolutely. And there’s so much of that, right. Just to touch on that for 10

Ryan: Yeah, of course, of

Jimmy: so much value that I see [00:40:00] that’s still absolutely locked up in companies and no amount of central IT is going to get around that, in my opinion, where just the automation, forget business intelligence and analytics, but just Automation tools that everybody has that the average person doesn’t realize it.

Jimmy: I gave a course earlier this week to a couple of folks. They’re in a pinch. They’re thinking about hiring. I’m sure that other people are going to be able to relate to this. They’re going to hire if they can’t solve it. And, you know, opened up again, not to tout a product, but opened up Excel and said, Hey, here’s a button here.

Jimmy: If you ever clicked on this before. Know what’s it to, and then, you know, ran them through a couple of, a couple of scenarios that I thought would kind of just give them that aha moment. And sure enough, and this is what I love, I, you know, I used to tutor for a while too. And I always loved finding that student that had the, you could see the light bulb and you knew that what, what they just got exposed to was going to kind of move their life in a different direction.

Jimmy: Um, and, and had one of those early, I just got goosebumps. Uh, [00:41:00] Had, um, had that happen earlier this week though, where you say this is worth a YouTube video or two and, and it will, it will change, you know, is it going to lead to BI for the company? Maybe not, but you know, maybe now you can get your kids to soccer practice every day instead of slaving away at your desk, right.

Jimmy: Or whatever it means to, to any one person. So man, yeah, I mean, huge value locked up that. It’s just sitting right there, you

Ryan: Yeah. Yeah. I, I have to agree with that as, as a feels crazy to say this, but like long time trainer and consultant consultant. Now, the biggest payoff for me is like, sure. Like, there, there are loads of projects, right? Like, uh, That have, you know, been, you know, 10 plus million dollars in impact. I’m, you know, I, I sure.

Ryan: Great. Lots of value created. Hooray. You know, a career well spent financially for folks. But the thing that, like, gets me the most jacked. is when you [00:42:00] see the pain leave someone’s eyes. When like you, cause I know, cause I did it when I was at that phone company, I was just like manually clickety clacking away on the keyboard. And then when you see them realize, oh my gosh, there’s a better way. It’s, you know, it’s, there’s, there’s no better hit out

Jimmy: Yeah. Yeah, man.

Ryan: you know, if I can pivot just slightly, like, You happen to be the owner of a use case that I think is fairly unique out of the people that, you know, I’ve talked to so far on the podcast.

Ryan: And that is, you know, just because of some of the business realities of your company and industry, there are times where you have to provide decision making capabilities to people that are in remote locations. And that presents all sorts of interesting [00:43:00] challenges. And I was wondering if you could talk just a little bit about that.

Ryan: Um, so that if there’s anybody else that has that specific problem, they might be able to pick something up.

Jimmy: You know, the, uh, I’ll go with whatever starts in mind and we’ll see where my brain leads me. Like you said, the chock full of crazy ideas. I, I think, I got forced to really think about this and it was years ago now, but it was with this particular company, right? So for the, you know, I guess the audience, right?

Jimmy: The, like you said, it’s remote location. So you start to get into these situations where The internet that we kind of know and love either at our office or at our, at our home, whatever it is, is not to be found in the same, uh, same form or fashion. So working around that and its impact, not only on what you do, but how you advise, right?

Jimmy: And I remember, you know, years ago when we started our journey with business intelligence at the current organization, it was a big deal to go from once a month reports to every day. And as soon as we did that, the business was like, Can I get them multiple times a [00:44:00] day? And you’re like, Whoa, hold on a minute.

Jimmy: You know? Um, and, and, but the, the point of convergence for the average person though, is real time, right? That’s whatever that means to different folks, but real time. And we work in an environment where that’s not always the case. And you can actually ill advise the business with real time analytics. Um, because you actually don’t have sufficient information to make, The best decision, you know, you’re waiting again, we’re in the IOT space, right?

Jimmy: So if I’ve got IOT data buffering somewhere and, and I say, Hey, looks like whatever, and we send somebody on a plane to go look at this, or we. We’ve just ill advised the business, right? So, you know, that, that’s a big one for

us, but you know, that the, the buzzwords of real time and some of the other buzzwords, they don’t always make the most sense, you know?

Jimmy: And, and, and, and you do need to think about that, you know, um, could I, Ill advised someone trying to meet [00:45:00] what they believe is their need. But, you know, it’s almost like sometimes you need to, you need to, you know, we talked about the hat of, um, you know, kind of being a data steward or whatever, but sort of that hat of, I’m not just an IT person.

Jimmy: I kind of need to put on my advisor hat and say, trust me here. This is, It’s not going to sound good, but this is, you know, for your own, um, for your own good, you know, happy to explain it, whatever. But, um, we go through that quite a bit. Um, you know, and again, it’s, it’s interesting too, cause when you get into these remote locations, a lot of, a lot of stuff’s popping up and it’s very cloud oriented.

Jimmy: And that lends itself to, you know, you’re in your role today. You probably have a better sense of the number, but I would say a significant portion of businesses or percentage, right? Um, cloud based doesn’t always work though, right? You have these, these remote instances where you almost, you know, whether it’s edge computing or this or that is, is sort of the reality you have to think about and, you know, I, I’m not going to go too far down that path because again, we’ve got our [00:46:00] business constraints and you know, what we have and haven’t invested in, but.

Jimmy: Um, but that’s something to be mindful of because more and more is going towards the cloud and that works for a lot of us, but it doesn’t work for all of us, right? Or all of our use cases.

Ryan: I mean, uh, the, the second one is, you know, like obvious wisdom. Even though like some people are like, not cloud, you know, like, yeah, absolutely. Right. Like it, it depends on the use case and picking, you know, the best tool, right. Like, you know, driving nails with the side of a screwdriver is not a good idea.

Ryan: Um, you know, the, the other one, and you’re right, like, I totally wasn’t, you know, expecting to get into it, but I, I love is that idea of, you know, Realize again, like this harkens back to like, you know, being an advisor. means understanding the business. It means that data and those tools are just. You know, things to help us achieve our business goals, right?

if somebody, [00:47:00] you know, I think there’s a lot of, again, with the, the transition back towards, you know, centralized BI and as data and analytics and the tools have gotten more mature and people are trying, you know, kind of finding places within the organizations to execute those functions. I definitely encounter, you know, a lot.

Ryan: Of thinking where it’s like, okay, well, this is, like you mentioned, this is a cost center, you know, you guys should, you know, primarily be order takers. We’re going to set up a ticketing system and then people at, you know, yada, yada, yada. And like, you know, again, it’s, it’s a balancing act. I’m not going to be black and white or prescriptive.

Ryan: Like that may work for some organizations and that may be the most effective way. But when I have seen analytics be most impactful, it’s when the people that see the data have that data knack. are empowered to advise. Um, and it is kind of almost this like internal consulting role. It requires [00:48:00] a certain degree of business acumen back to like looking for non technical skills when you’re building those teams.

Ryan: Um, that is, you know, such a good point, right? That like, obviously like, sure, you can get some stuff done. With the order taking mentality, no doubt. And it’s better than having nothing. But if you can kind of gradually empower some of those people to be advisors to the business, like you said, you can solve some really, really cool edge cases. Um, now for an even bigger pivot, I want to, like you said, I mean, I could talk to you about this stuff for hours and hours and hours, but I want to give everybody a chance to get. to know Jimmy a little bit. So tell me a little bit of your background, you know, what do you like to do outside of work? What, what is fun, um, for you?

Ryan: Yeah.

Jimmy: Oh gosh. Um, yeah, so I don’t like you. I have lots of hobbies and I spread myself too thin across all of them. Um, yeah, I mean, I, I don’t [00:49:00] know, I’d say any more. Um, just getting out in nature and hiking has probably been, you know, relatively inexpensive and You know, all that sort of stuff. But yeah, I mean, grew up, uh, an avid golfer.

Jimmy: Um, still enjoy doing that, but my body’s aging and, uh, you know, kind of feel like the Tin Man and Wizard of Oz some mornings you

Ryan: You still beat me by 10 or more every time we play.

Jimmy: um, yeah, you know, enjoy golf. But you know, the, the thing too, my brain never shuts off the thing about golf as an example. I think maybe this will kind of shed some light on who I am. It’s like. Golf is not just a game you play, right? It, I love, it’s a game of life, right? And integrity matters. And, um, I mean, there, there’s so much more to it than just hitting a little white ball.

Jimmy: And it’s also, but it’s the kind of sport too, where for those that consider it a sport, you’ve got plenty of time to think. And, and that’s also interesting and, you know, all that. But, um, no, I enjoyed that scuba diving, like we were talking about right before the podcast, [00:50:00] you know, but again, that’s circumstantial anymore, but yeah, it used to.

Jimmy: You should do that quite a bit, um, and, uh, reading, learning, you know, stuff like that, and then time for family and, and all that, but I mean, I don’t know, normal stuff, normal stuff.

Ryan: I love it, man. I absolutely love it.

Jimmy: So, Jimmy, I can’t thank you enough. This was like every single thing that you said I could have talked about for an hour. This was like such like a dense amount of knowledge and value. Um, I am so pumped that I was able to make it work with time to get you on.

Ryan: I can’t thank you enough.

Jimmy: Yeah. Thanks Ryan.

Ryan: All right. Um, I also want to thank the audience. If you learn something, undoubtedly, Please make sure to, uh, subscribe to the podcast or give us a rating, uh, hopefully a five star rating and be sure to tell somebody else. Jimmy, thanks again so much for coming on. And this has been another exciting episode of Making Better Decisions.

Jimmy: Thank you, sir.

That’s [00:51:00] a wrap for today’s episode of making better decisions for show notes and more visit, making better decisions dot live a special thank you to our sponsor canopy analytic canopy. Analytic is a boutique consultancy focused on business intelligence and data engineering. They help companies make better decisions using data for more information, visit canopy analytic.

com. There’s a better way. Let’s find it together and make better decisions. Thank you so much for listening. We’ll catch you next week.