Episode 111: Data Trends Your Fleet Should Adopt

Hi everybody, and welcome back to the Fleet Success Show. We are on episode 111, uh, and today I am joined by some colleagues, Griffin Scott and Chris Diameter. I'm Mark Canton at RTA Fleet, the fleet success company. So Griffin joins us and he's been in fleet for about 7 years. He's a fleet management analyst. With a bachelor's in data science and a focus in geoinformatics. And Christy joins us. She's also a fleet management analyst. And she has a bachelor's of science in mathematics, a couple of master's degrees because, you know, she's an underachiever, one in data analytics and one in education. Before becoming a fleet management analyst, she tried to, teach 8th graders math and decided that wasn't really for her. So I've asked these wonderful folks to join me today so we can talk a bit about different things associated with fleet management analysts, fleet management analytics, and various trends around data in the fleet industry. So, hey folks, thank you so much for joining me today. Really glad to have you on here.

Good to be here. Appreciate it.

All right. Well, let's jump into it. Okay. So we've gotten a lot of, you know, curiosity and a lot of interest recently around this topic. Folks are looking for fleet management analysts. You know, we have found that they're pretty difficult to find. So I'm going to ask you to start off with a few questions around that. I'll start with you, Kristi, actually. How do you think analytics in fleet compares to other work you've done?

Um, so my background has been mainly in fleet. However, I have the experience when I was teaching, doing analytics, as well as my master's program. So I had that background. The main big, big difference is that fleet is not just one sort of analytics that you do. If you work in a warehouse, you're just analyzing warehouse, um, orders and ports and that, that's, that sort of thing, sorry. And other things like that. You'll, as a fleet analyst, you'll analyzing parts, you're doing work orders, you're doing financial analytics, you're doing fuel utilization. It's all this one big humongous bucket of areas that you need to know how to analyze as opposed to just one small bucket you can focus in on and have all the knowledge on the small bucket.

Okay, so I think what I'm hearing you saying is you need to know a lot about a lot in order to give that data the appropriate context, right? Do you think— I mean, Griffin, would you say— what would you say about that, right? Is, you know, one of the things I talk about a lot is data has context. What's your experience tell you there?

Oh, absolutely. You know, really my first job was in the school bus industry. A lot of that was just, you know, simply routing and logistics. When I jumped over into fleet consulting, you know, it kind of opened up the entire world. All of a sudden I was doing logistics and routing, but also financial analysis, you know, right-sizing, all sorts of different things. And I really had to expand my knowledge in the fleet industry. And really, you know, the way I did that was just working with experts in the industry. I was fortunate enough to have colleagues that had you know, decades of experience working as fleet managers. And really, you know, I think it takes a certain drive to kind of go out there and learn the information, ask the questions, you know, be hungry enough to actually get the information that you need to get the context to really, you know, know what you're talking about and know what you're analyzing.

Well, let's stay on that for a second. I was going to ask you a different question, but I'm going to jump to my third question here. Because I think that, that segues well into, into one of the questions I wanted to ask you guys, which was, what would you say to a young professional who's thinking about, you know, getting into fleet analytics? You know, you just mentioned about the drive and the hunger and, you know, would you say it's a rewarding field? Would you say stay away from it? Uh, what, what tips or advice would you, you know, might, might you have for them having kind of gone through this yourselves?

Yeah, no, I, I think it's a very rewarding field. I think it's something that, you know, when you're in school and you're learning analytics, you know, there's not like a specialty for fleet analytics, really. You know, that's not something that's, that's big enough. It's kind of niche to say.

Which is ironic since every organization on the planet has a fleet for the most part, right? Isn't that— is that strange? But yeah, continue.

Oh, you're fine. So I would say don't, don't let the fact that you, you know, didn't get necessarily training in fleet analytics drive you away from looking for these types of jobs. You know, my background had nothing to do with fleet analytics. You know, it was more logistics, but it was just kind of an entrance in. So really, you know, I think apply for it, go for it. It's something that if you have enough drive, you can work with the professionals in that industry to really kind of help make you grow and become a fleet management analyst.

Yeah, you have to be willing to attend the webinars, ask questions. I think I bugged the experts when I was learning it every single day of like, of new questions I had. You need to be willing to ask. And there's a bunch of free webinars. There's also paid webinars and conferences you can attend and get the training that you need. But the big thing is you just need to be willing to ask because you, you can know the data. You can know— I'm sorry, you can know how to analyze data, right? But you have to be willing to learn what the data is truly telling you. It's also the vice versa is true. If you really know Fleet and you love mathematics, there is programs out there that will teach you how to do the analytics.

Okay. Which— well, I'll pause on that one for a second. But, you know, let me ask you guys this as a quick follow-up. Griffin, I know you've done some work on GIS work. Geographic— what's that acronym? Geographic Information Systems or something like that?

Yeah, GIS.

All right. And so, like, has— I mean, would you say that all that helped? Like, you know, you mentioned about the logistics and doing different things, but, you know, has that helped you? Is it applicable? Or is it like, you know, the stuff you guys did before joining, you know, moving into Fleet? Is it just kind of like starting over essentially? How would you say your experience was?

I think there's definitely areas where it is applicable. There's definitely like optimal location and analysis, you know, where's the right place to put your, your maintenance shop? Where's the right place to put your fueling stations? So I think it definitely helped me out in my journey. I don't think it's necessary really to get into it. I think it is more of a you know, certain situation, um, kind of a thing, but definitely it's helped me throughout my career and I think it's helped me stand out, honestly.

Cool. All right guys. So let's, so let's go back to then the, the, the original second question I wanted to ask you, which was, what would you say to a fleet manager or the leader of a fleet organization who are, you know, looking for a fleet management analyst or multiple fleet management analysts or, or someone to get that work done? Would you have any tips for them? What, how, you know, how do they, how do they lock into, you know, or identify someone who can really do that work? Because I'll tell you from my experience, I've seen folks get hired and maybe they're business analysts or they're, you know, or they're coming over from adjacent industries and they mean well, but they just, you know, they just can't quite get done what it is the fleet organization needs to get done. So that's tough. It's tough on fleet managers these days. What tips do you have for them?

You need to be looking for someone that has, like, the drive, as Griffin said, that is willing to spend their time learning Fleet. And it would be lovely to find a million people that are also trained with Fleet and analytics. But unfortunately, as we said, it's very niche. But you need to find someone that's willing to learn and is willing to ask questions. You don't want someone that's very timid that just wants to be on the computer all day and does not want to ask any questions. You need to have someone that's willing. And also, you need to be willing, and your members of your organization need to be willing to answer the questions too, right?

Yeah, I think it's definitely, you know, two streets. You know, of course, the person needs to be willing to learn. But I think, you know, with a good enough support system, I think you can really bring someone up. I know, for my sake, You know, I was definitely hungry, but I also had a lot of support from, from the people who mentored me. So I think it's kind of a, you know, two-way street.

Yeah. I mean, I'm imagining that if you're in a fleet organization, right, uh, and you're a leader in that organization, you're probably a lot more comfortable and confident around your fleet knowledge and your ability to coach that than around doing analytics work and your ability to coach that. So I know, I know you said earlier, hey, you could go the other way. You could know fleet and And, but I, but I, you can correct me if you think, if you disagree, but I feel like that would require a bit more formal training, right? Okay. I know Fleet.

Yeah.

I'm gonna go back and get my degree in analytics or data science or something like that. Um, you know, but, uh, but I would imagine that if they're hiring fresh and they're looking to bring somebody along, you, they need to establish that, that, that analytics aspect piece is solid and they can just kind of count on it. And they're not someone whose background is in data analytics. So how do they know that, right? Is it certain degrees, right, that they should be folks with backgrounds of certain degrees? Is there, you know, should they just give you a call and say, hey, can you give this person a test for me and tell me, do they know what to do? Like, how do they know that they have somebody, you know, uh, it's— and listen, this is a challenge whenever one's Anyway, what are your thoughts around that? How can they know that they found a decent candidate who— okay, and then once they have the data analytics established, fine, they're willing to learn about fleet and all that. How does a person— how does the fleet manager know that they have the data analytics established?

Yeah, well, you could go the route of training, those degrees in data analytics, data science. Business Analyst as well, and other ones like that. And there's also programs online that will give you certification and teach you the analytics. So if they— as well. And you see how someone— you don't want to hire someone that is, let's say, a psychologist by trade. You want to have someone that has the math background.

Right.

Yeah.

So mathematics, data analytics, data science, economics, finance, something where they've had to use Excel a lot. Is that fair to say? Yes. And/or similar tools and things of that nature. Is that right?

Mm-hmm.

All right. So let's shift gears here a little bit and talk about some data management practices here that, you know, you guys think are important for fleets to adopt that will really help them as far as on this journey of being able to leverage data in their organization, right? Because it's, it's, it's that, that's clearly a trend, right? I mean, organizations are just expecting of their leaders, and fleet management is no different, um, you know, to be able to leverage data, to be able to know that folks are making good decisions, that folks are managing things well, that performance is adequate or better and using data to, to tell that story, to, to, you know, to prove that. And certainly the spotlight on fleet has increased now in recent years with, with some of the EV stuff and that maybe wasn't there before. So let's talk a little bit about that there. What do you, what do you think the key pieces to managing data in a fleet organization are?

Well, I think the biggest piece is you need a plan. You need to know What data you're going to be tracking and why is the biggest thing. You need to have clear objectives that you want to reach with your data. You need to have clear knowledge of who's going to be responsible for the data. You need people that is— their responsibilities be, oh, you're entering the data, you're looking it over, and you're validating the data. You're making sure there's no fat fingering in the data entries.

Yeah, that's a good point. Validation routines, I feel like, are the big— people just skip that, and it hurts a lot. I mean, what are your thoughts on that, Griffin? I mean, I feel like it's one of those things that, you know, to Christie's point, if you know who's responsible for it, then it kind of can become part of their everyday or their every week. But if you don't have that identified and you're trying to only clean up the data once it's 3 years old, that's— That's, that's tough. Any thoughts on that?

Yeah, I think, you know, having someone responsible for it is, you know, extremely helpful. I also think another avenue of it is, if you're able to get kind of all of your systems in place to talk to each other and kind of do that automatically, it can help a lot. You know, having a kind of almost a central repository or all the data, you know, can be extremely helpful and make your life a lot easier instead of having someone sitting there typing in work orders every day. You know, it kind of reduces that chance of, you know, fat fingering, as we said earlier.

Right.

Really making those errors.

Okay.

But still, even with an automatic system, you need to have someone sitting there making sure it's working. Right? And not, you know, eventually pulling it up 3 years later to take a look to see if, you know, what you got was good. So I do think you still need to have, you know, active management of it. But make your life easy, connect your systems together. Most, most software have APIs that, you know, essentially let systems talk to each other and kind of just import that data automatically.

Okay. So I'm hearing another step that you added in there, which is, uh, try to minimize human entry, right? The more that you can come in an automated way or coming, you know, entering directly from a system. Basically what you're talking about is integrations, right? Figuring out which program is going to be sort of the core of your fleet management practice, which is typically the fleet management information system. And then have the other systems kind of feed into that essentially. Am I putting words in your mouth or does that sound about right? What are— let's pause on that. What are some sources of data then? What— where, you know, obviously telematics is the big one these days.

Um, your fueling cards or the fueling tanks systems, or another big piece, especially with EV, carbon emissions. It's a big topic. Yep.

HR programs, maybe training.

Yeah, your accounting system, really, and anything that has to do with anything that touches fleet, honestly.

Okay. All right, what are some— well, let's actually, let's finish off. So did we count off all the key pieces of this plan, Christy, that you talk about? Is there any other pieces there that we need to cover? Let's see.

We talked about the objectives, knowing what you're going to track and why. And also, what are you going to do with the data? Once you have it, are you just going to keep collecting all this data or are you going to actually have analysis that's going to take place at certain intervals, reports that you might need to write? Your leadership might need a report every few months on how fleet's doing. You need the data to help back you up.

So what are the key indicators? What are the key performance indicators that you're going to be reporting on and why, right?

Yeah.

Okay. What about training? Yeah. You know, I feel like that's another piece that kind of often gets overlooked, right? So you can only— if the data is bad, right, garbage in, garbage out. When we're talking about data validation routines, you know, if everything that gets entered is garbage, data validation routines, they just get flooded. It just becomes more than they can reasonably manage, right? So the idea is to be catching exceptions, not constantly being correcting and editing things, right? So, so I would imagine training is a fairly big piece of it too, right? Making sure people know how to use the systems they're working in, make sure they're collecting it, knowing what's reasonable, uh, those sorts of things. Um, seems like a, a lacking thing, right? And what do you think? What do you think about analytics by committee? Does that make sense?

Should everyone be doing it or No, you need key people that their duties are, um, to analyze the data. You might want to have like some— certain people might be able to enter the data in the system, other people might only be able to view the data because you don't— because they don't need to enter it, they just need to be able to see what's in the system. And you need key people that their duty is to analyze the data.

That makes sense to me. So, uh, who dedicated resources essentially for doing these kinds of analyses and that sort of a thing. All right. So let's switch gears slightly. Like, what are the key tools? You know, like, tell us the tools of your trade, right? Mechanics are using wrenches and air guns and lifts and all kinds of different things, diagnostic tools and whatnot. What is the fleet management analyst— what's in their toolbox?

Yeah. The key piece, I would say, is Excel. Excel is still king. It's— most organizations have Microsoft. Excel is still king even though it's old. Excel has been around since, I think, the 1980s.

Who knows? Yeah, I got some folks listening in like, oh my God, these people are so young. Sorry, folks, in advance. Griffin, do you agree with that? Is Excel still king?

Absolutely. I think, you know, there's so much you can do with it, and I think it's the basis of a lot of people who do analytics. You know, it's just kind of home almost for a lot of them.

Yeah, no, you can learn it in school, right?

Yeah. Yeah, I learned it in middle school to high school, I think, right? But really, you know, there are other things you can use, other things like business information intelligence, essentially, so BI. So products like Power BI, Tableau, all those sorts of things. That's really— I think that's kind of the advanced level. That's once you've connected all of your systems together and you have data flowing freely and that you can basically put on top of all of that, a BI system that will basically allow you to kind of create those reports. So I think, you know, Excel is the base level. You can, you basically can do mostly anything in Excel. So if you're not ready for that next step, you know, Excel is probably where you want to start, right?

You know, I would argue that another key tool is, is actually fleet management information system itself, right?

Yes.

Yeah.

It's going to have, you know, hopefully our system certainly does. It's going to have analytics built into it at a certain level, right? So you don't need to reinvent the wheel on everything. You know, like you said, obviously there might be some custom things or some other things you might want to do to pull it out and do it in Excel. Or if you want to tie it with data from other sources, you know, then, then, then you're really talking about pulling that data out. But at the same time, a key— I think a key tool is, you know, having a system that allows you to get at that data and get, you know, and get it what you need. And as well as doesn't make you reinvent the wheel for sort of low-hanging fruit stuff, right? That has some key pieces there for you to use, you know, immediately, I think might be a key piece, you know. But, okay. But yet, and yet there are some things that, you know, like I've seen in certain telematics systems where it's kind of like an automatic, automated analysis. And when you read, you know, sort of the knowledge base on it and understand what it's doing, it may not always be doing exactly what you want it to do or you intend to do. And so, right, have you guys run into that? So I think that might be a tip too, like read the knowledge base, understand what it is your report or your graphic is actually doing, because it might use very similar words and not actually be doing, you know, the same thing that, you know, that you want it to do. You know, like, I think about utilization, and I came across a telematics program. I won't say the program, but this program, if you use— let's say the asset was being used at 11:01, it showed as it was being utilized during the 11 o'clock hour. So if you weren't careful, it could show as being used during 2 hours, right? As opposed to being used for 3 minutes. And so that's the kind of thing I think we need to, you know, be mindful of. Understanding the fleet management information software tool and how those reports work. And I think it's critical. Same is true with your telematics, you know, so that you understand truly what the canned reports are telling you. And understanding that knowledge base, I think, is a key piece.

All right. Yeah, 100%. Yeah.

Is that something you've run into? Yep. Yep. All right. Let's talk about a little bit here about proactive and reactive, you know, practices and analytics. You know, I feel like a lot of the world, especially in fleet, is, is looking backwards, right? It's what was our total cost of ownership this year? What was our PM compliance? You know, those sorts of things. And yet I feel like maybe there's an opportunity to really expand the future looking, right? Which I don't know, in my mind that's ultimately what analytics is, right? Like when you think about the big data phenomena, Amazon or whoever is trying to predict, you know, what you're going to buy in a grocery store tomorrow based on— so it's using past data to to try to reasonably guess or estimate something that some future occurrence that is yet to take place. And it strikes me that's where the true power of analytics lives, right? I mean, what are your thoughts on that? How do we help fleets get to, you know, to there a little bit more?

Yeah, there is a growing field of predictive analytics. The big thing is you need to have the data to be able to do it. For example, you can use your utilization data and you can predict based off of past trends. You need historic data of what is your future utilization going to be to predict when is the time to do your PM so that way it's not late. You can schedule it on the books and that way the driver knows, oh, next week I need to take it in for PM, not, hey, mechanic, can you fit me in for PM because I'm way past due?

Right. And it doesn't stop with PMs, right? Like, in theory, if you're tracking the data properly, you can predict when a part is gonna fail or when a system is gonna fail, right? A major component or engine. And, and that could be really valuable, right? Because you avoid the breakdown on the side of the road, especially, for some organizations that are doing, like, site stuff. You know, what are some other things? Do you have any examples or some things that you've worked on that you've thought were interesting in that, you know, sort of in this area, in this realm?

Yeah, I think really even just to piggyback off what you were just talking about, Mark, you can use that kind of information really to kind of predict, you know, when's the right time to replace your vehicle. Um, you know, really utilizing kind of historical data and just certain vehicle types, um, you can know, hey, you know, the 7th year is probably the best time for me to replace this vehicle where it's before major breakdowns start to start to happen where you're having to invest a bunch of money into the vehicle to keep it running. It's also a good time to sell it.

Right.

Just, you know, as a used vehicle. Right. So, you know, these days—

the residual values is what you're saying. Yeah, right.

Yeah, exactly. Yeah, exactly.

And another key piece is you can also do it for your parts room. If you know you have proper parts that you want to keep track of, you can know based off of my past history, I use this many parts a month. So I need to reorder it now so that way I don't have— I don't have an empty shelf when it's needed. I also don't have too much on my shelf. Well, my entire shelf is just, let's say, spark plugs, right?

Yeah, but I'm really interested in— I feel like I know there's some organizations out there doing this, but I do feel like it's, it's likely the overwhelming minority. But I feel like that's sort of the next frontier is, you know, right now we have, you know, everyone's familiar with the idea of planned work or scheduled work. Some folks, when you call it deferred maintenance, it's a four-letter word, right? But the idea is instead of knowing I got to replace these brakes because I saw them recently and hey, it's got to, it's gonna, you know, can we predict when those, that brake replacement is going to be based on certain utilization and that sort of thing? The other thing, as a former transportation guy myself, You know, that I feel is really underutilized in fleet is, you know, rotating assignment. You know, managing utilization actively just doesn't seem to happen nearly as often as it should. You know, hey, this person's putting on, you know, 150,000 miles a year and this other person who has the exact same asset is putting on 20,000 miles a year. You know, we can sort of see that and, you know, we can use that to reassign assets, make sure that utilization is even so that it matches the depreciation curve and you don't have this asset that's got way too many miles for its age or way too few miles for its age, right? In which case you, you throw your finances upside down, which again, something that I think we see, uh, a lot of. So yeah, predictive, predictive versus reactive. I think most of the world is on board, has been doing the reactive stuff for some time. How can we get in front now and do more to help keep costs down in fleet by leveraging that predictive piece?

All right.

Well, any closing thoughts, guys, that you have on any of the topics that we've had today? You know, how to hire a fleet management analyst, big trends in that, anything we didn't cover that you want to point out? Hmm.

Nothing I can think of. It's been a great conversation.

All right. Will you come back and do it again? Sure.

Yeah, sure.

All right. So more to come from fleet management analyst extraordinaire down the road. In the meantime, folks, if you're interested in the Fleet Success Playbook, you can get that on our website, fleetsuccessplaybook.com, or you can email us for a free copy of the book and include your address at podcast@rtafleet.com. This is Mark Canton at RTA Fleet, the fleet success company, speaking on behalf of Griffin and Christy. We'll see you next time. Take care.

Thank you guys.

Thanks.