Mile Marker
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Mile Marker
The Evolution of Telematics: Integrating Data for the Future of Fleet Management (Geotab)
Greg Gray, VP of Sales and Fleet Management, and Sherry Calkins, SVP of Global Strategic Accounts, both from Geotab, discuss the shift from traditional telematics to a broader focus on data intelligence, integration, and automation. They highlight the advantages of AI in simplifying fleet management and reducing costs but also mention the challenges of electrification and the need for global data standards to ensure accuracy and consistency as fleet management evolves.
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You are listening to the Mile Marker Podcast,
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where we explore trends and innovations in fleet automation
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and shared mobility, helping fleet based businesses make
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better informed decisions
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and achieve full digital transformation.
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Welcome everyone to The Mile Marker podcast.
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I am Angela Samoes, your host,
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and today our guests are Greg Gray, VP of Sales
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and Fleet Management for Geotab
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and Sherry Calkins, SVP
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of Global Strategic Accounts for Geotab as well.
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Welcome Greg and Sherry.
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Thank you. Glad to be here.
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So I think when I, when people hear telematics, I mean,
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I think they think Geotab,
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I feel like you guys are like sort of the king
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of telematics, right?
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So let's, and,
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and everybody that I've talked to so far, um,
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when we talk about what are things that are working,
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what are the big trends, you know,
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or how have things evolved?
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Telematics always comes up as something that's working.
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So let's talk about how telematics has evolved Mm-Hmm.
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Um, is evolving and where you'd like to see it go.
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Um, just, you know, just
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before our conversation you were saying, Sherry, that Yeah,
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you know, we need to evolve the term telematics even, right?
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So, so let's talk about, let's talk about that.
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Exactly. Yeah. I mean, telematics is table stakes today.
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I think it's really difficult to, you know,
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have your finger on the pulse of your fleet without having
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that data, but it's more than just telematics.
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So, when I hear Geotab being a telematics company, I kind
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of get my back up a little bit
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and say, you know, that's no longer what it is.
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It's, it's so much more.
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It's really about the data
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and the intelligence that you get from that data
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and how you can action on that.
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And even outside of the vehicles,
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and you think of telematics,
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it's really the data coming from the vehicle Mm-Hmm.
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And outside of that vehicle, you know,
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what you're doing within your back office system,
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your HR system, your work order system,
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all those things have to tie together.
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So it's all about the data, more
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so than just about telematics.
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'cause there's so many different things
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that you can integrate into,
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or even take the telematics data
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and integrate that into other systems too.
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So bringing all that together in one platform, um, you know,
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it's the challenge today.
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And that's where we're really evolved to.
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Not just the telematics, but
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again, bringing all that together.
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And, and so how are you doing that?
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Because there tons of data streams
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and then, you know, even just different data formats, right?
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And then how do you make sense of it
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and then present it in a way that, uh,
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helps customers make decisions on that data.
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Right. And then are, are, so can you talk a little about
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how you're actually bringing all those sources together?
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Yeah, I think, um, you know, it really starts with
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how we were founded and how we started.
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And it's an open platform. Mm-Hmm.
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So being able to have that open platform, having available
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APIs and an SDK that's easy to understand,
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already have half the work done for you,
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and being able to either extract the data
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and take it into other systems,
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or bring other systems into ours, um,
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I think it's the powerful, and that's powerful part of that.
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And that's where it really started.
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I also think in addition to that, it's being able
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to have these turnkey integrations as well.
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So we have a marketplace
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with over 300 different applications.
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Everything from routing systems all the way to, you know,
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VSA, you know, what's my, um, ev um, sustainability
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or suitability assessment.
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Um, so having that as well is, is really
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where I think the foundation brings everything together
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and allows that integration.
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And Greg, I know you work with a lot of different partners
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and they all do things a little differently,
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so you probably have some
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extra things you could add onto that.
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Yeah, I think in the fleet management space are the,
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you know, they sell a lot of different services,
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maintenance services, accident, uh, services.
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And so having that quality
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of data from Geotab is really important for them to leverage
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as they tr, uh,
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provide their own insights into their clients.
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But the other thing you mentioned is, you know,
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because we do collect so much information,
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it can be very confusing to people Mm-Hmm.
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If it's not organized properly.
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And I think one of the things that we've done, uh,
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most recently is created these notion of centers.
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It's like a safety center
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and a maintenance center where it's all encompassing.
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You can come in as a fleet manager, you can instantly see,
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you know, who are your riskiest drivers.
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You could look at maintenance
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and see, you know, where do I need
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to put focus my attention?
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So really not having to sift through all the information
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that, that we're collecting,
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we're actually prioritizing it based on your business rules
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and things you need, so you can just go
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and get all the information you need right off the bat.
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So I think that's a really powerful, we're mm-Hmm.
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We're getting into the visualization now of the data. Okay.
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That really helps our customers.
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And obviously, you know, I'm sure we'll talk about AI later,
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but the work we've done in AI will make it even easier
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for fleet managers to take action in the future.
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So that, that sort of is part of my question.
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My, my next question. So I was gonna ask, you know, what,
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um, has driven this evolution is just sort of the nature of
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how technology evolves
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and then you know, what customers are asking for
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and how, where do you see it going?
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And kind of based on what, um,
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customers have been asking for.
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I mean, in our last conversation,
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we were talking about the Amazon economy.
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Economy, right? Like an expectations, right?
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You want to know exactly where everything is at.
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You want it immediately, you want, I mean,
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so the expectations are just
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so much greater now than they were even five years ago.
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Um, so yeah. So what's been driving this evolution
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and then kind of where it's, where's it going?
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Yeah. I mean, I think it's interesting.
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Our, our CEO showed a chart at our connect conference a
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couple years ago about how customers, you know, start out
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with telematics and then over the evolution
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of understanding it, solving a specific use case,
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they move up towards operationalizing the data,
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connecting it with other systems,
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and sharing that information beyond the fleet space.
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Right. And so with that, um, you still have
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to look at the information and take action on it.
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I think in the future, what we're gonna see is,
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we've been working on AI for over 10 years,
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and so it's not new to us.
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Uh, we've been looking at patterns
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and, you know, trying to identify predictive, uh, uh,
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opportunities and maintenance and things like that.
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But I think really where, where we're gonna get
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to is the fleet manager should be able to come in,
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have AI analyzing all the information behind the scenes,
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and really giving them, you know, either taking action
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for them or saying,
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here are the things you need to do immediately.
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Mm-Hmm. And then they can just say, go do it for me. Right.
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It might be create a work order for a maintenance job,
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or place a new order for a vehicle, or, you know, right.
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Whatever the case may be. Mm-Hmm. That's
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where we'll get into allowing the fleet, especially
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for a fleet manager who's managing a
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multi-thousand unit fleet.
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That's a very comple
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and it's distributed across, you know, maybe even countries.
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It could be us, Canada, or even globally.
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Um, that's a very different, uh, type
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of management than somebody
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who has 10 vehicles in a local area.
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Right. So that's where I think it's,
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we've gotta make it more, uh, more intelligent instead
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of relying on the fleet manager to have to sift through,
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even if we make it perfect.
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Right. With the safety centers, you still want
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that next level of letting the system take action.
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Mm-Hmm. Which means you have to gain trust with the client.
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That's why we spend so much effort
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and time on making sure that our AI
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and our data quality is so high that you can trust it
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as a customer, and then you'll allow it
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to then take actions for you in the future.
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I imagine there's so different levels, kind of
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as you were saying, there's immediate action items
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or maybe just automated action items.
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So for example, or versus long term.
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So for example, um, a, a car need, you know,
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the engine light goes on.
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Well, an automated thing could be like,
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the fleet manager doesn't need to do that,
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just automatically do the, the work order,
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send the driver back to the depot,
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automatically assign him a new
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car, get him back on the road.
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Exactly. But then maybe there's some immediate action items.
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Okay. You need to, um, you know, switch out this vehicle
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for, uh, or, or,
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or place a an order for a new vehicle or something like that.
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And then maybe longer term, hey,
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in three weeks you may consider selling this vehicle,
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or, you know, having it refurbished or, or something.
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Right. So there's like different levels of action items
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that you could be taking.
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And the, the AI is helping you figure
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that out versus you having to look at everything
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and then say, okay, what do I do first?
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No, it's absolutely true. You,
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it could be monitoring pricing, so you know Right.
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When to get rid of your vehicle at auction
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and get the highest maximum price.
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Right. Right. Um, one of the things that's near
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and dear to me is route optimization.
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Mm-Hmm. So he talked about it a little
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bit, Jack did this morning.
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Um, I believe AI will be huge for routing.
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Uh, we offer that at Geotab. That's a, I used to do that.
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Uh, the company was acquired by Geotab.
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So it's, I'm passionate about it,
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but I totally see where that can,
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'cause now we get real time traffic and weather Right.
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And all those things. Right? Yeah.
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So AI could really become the brains behind the scenes.
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Um, and you would not need a dispatcher looking at every day
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at, Hey, I've gotta move this job.
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I've gotta move this job. AI could just do all
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that based on your business rules
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and the, uh, the weather conditions
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and the driver conditions and all those things.
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Super exciting. And routing too.
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Like, is your truck gonna fit on this road? Exactly.
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All of those things. Trucks, are you gonna get stuck at
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a bridge that you can't go under?
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That kind of thing. Right. Yeah.
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When you talk about the evolution too, I think about,
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you know, how you mentioned all the integration
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and the automation and cost avoidance, right?
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We think a lot about how can we squeeze another, you know,
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dollar out of savings for this fleet.
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Um, and sometimes you don't think about all the different
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people that touch a process.
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Mm-Hmm. And when you can automate that, the savings
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that you have, it's, it's so critical.
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And I think, you know, that is the evolution.
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Um, we're seeing the evolution
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of a fleet manager in general as well.
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They're becoming more of the data analyst, if you will.
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And Greg, you hit on it too.
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Um, you know, the days of having to download Excel reports,
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you know, and looking at those to find, you know,
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those little pieces of
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where you can move the needle a little more.
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Um, AI is changing all that. Right.
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You know, in an instant, it can tell you where to look,
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where to, you know, focus on,
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Uh, it's funny you mentioned downloading spreadsheets,
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and I immediately think of the movie office
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space and the TPS reports.
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Can you imagine if they had AI
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and gosh, didn't have to look at TPS reports.
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Um, so how has electrification of vehicles
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affected this whole process and,
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and, you know, incoming data, right?
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Because now electric vehicles have
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so much more data that they're collecting.
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Um, and so how has that, how does
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that play into the bigger picture?
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Yeah, I think it's been a, you know,
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it's still an evolution, right?
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Mm-Hmm. Um, fleets I think are still challenged with it.
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And how to, you know, move your Fleet Electric.
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Um, I think everyone's testing different pockets in
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different ways of being able to introduce
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electric vehicles into the fleet.
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Um, testing at least one, you know, mm-hmm. If not many.
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Um, and, and data's certainly critical for that.
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I mean, you certainly can't have an electric vehicle in your
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fleet if you're not able to have access to that data.
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Know how it's being charged, where it's being charged,
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and how it's applicable to your fleet.
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Um, one thing that we offer, um, is an ev, um,
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VSAE EV suitability assessment.
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So what it does, it takes your real world information,
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the data today, and how that vehicle's being operated.
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And then it assesses all of the, you know, routing,
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how you're using it, the weight in the vehicle,
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all these different, um, data points
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and tells you specifically what vehicles,
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electric vehicles will work in your fleet for
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how you're optimizing that fleet today.
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Um, and that's only gonna continue to get better.
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And especially as we get more EVs out there on the road, um,
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you know, it's gonna broaden,
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I think the fleet's opportunity to go electric.
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I think we're still, you know, quite a ways off when you
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talk about infrastructure.
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Mm-Hmm. Um, you know, even, you know,
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today it was brought up in one of the sessions about fires,
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you know, so there's some concerns with people parking the,
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the vehicles in their garages at home.
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Um, so we have all that we have to contend with as well.
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But, um, I, I do see us moving that direction.
305
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But then there's other forms of, um, you know,
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sustainable vehicles too, that I think everyone's
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so focused on EVs today.
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I, I really wanna see us broaden
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and look at other ways that we can reduce that The hydrogen
310
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Too. Hydrogen. Yeah. So vehicles. Yeah. Exactly.
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Mm-Hmm.
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And I would even say on the routing side, you can,
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with routing, you can reduce CO2 emissions
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with your ice fleet while you're making that transition.
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I think we've seen a, a pretty good adoption in pharma
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of EVs because they're mainly using passenger mm-Hmm.
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Vehicles. So part of the challenge
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besides infrastructure is just,
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are there enough commercial vehicles that are EV
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and then we know that there's battery technology
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that's gonna continue to improve.
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So I think some companies are hesitating a little bit
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because with people like Toyota coming out
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with statements like, Hey, I'm gonna have this new battery
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technology, it's gonna triple the distance you can go,
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they're like, okay, I don't wanna invest a lot
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of money in a fleet when maybe next year I can buy one
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that's gonna go three times as long,
329
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and then I don't have as much infrastructure
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concerns as I may have now.
331
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So a lot of moving parts to Sherry's point.
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So for us, we always, we, we provide the tool so
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that a fleet manager can easily assess which vehicles could
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be trans, you know, transferred to EVs,
335
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and then we have offer the routing tools to, to support the,
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the current fleet to help reduce their emissions.
337
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So I think we and others in the industry,
338
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the FMCs all all have programs
339
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to help their customers do the SI similar thing.
340
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Um, but I do think it's just gonna
341
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take some time to Sherry's point.
342
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Mm-Hmm. It's gonna evolve. It's not gonna be overnight.
343
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They're all gonna be here. Uh,
344
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it's gonna take a couple of years. I think
345
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I, I probably think it more than a couple years.
346
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Right? Yeah. I mean, everybody has such high hopes that,
347
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you know, oh, we're gonna be all electric, you know,
348
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in 10 years or,
349
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and it's just we need to, you know, take a step back
350
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and be a little bit more realistic about how things evolve
351
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and you work out the kinks
352
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and, you know, you perfect the process and,
353
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and the technology continues to get better.
354
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And, and it's the same thing
355
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with autonomous vehicles, right?
356
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Uh, I mean, I might be 90 by the time we have an,
357
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an all autonomous society, even in some of the cities.
358
00:13:55.485 --> 00:13:57.845
Right. Um, so Sherry, you mentioned, uh,
359
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one of the sessions you attended.
360
00:13:58.905 --> 00:14:00.925
So we are here at ala, uh, we haven't mentioned that
361
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yet, uh, recording this.
362
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Um, have there been any big aha moments
363
00:14:05.875 --> 00:14:07.005
here so far at the show?
364
00:14:07.065 --> 00:14:10.445
Or what, what were you any kind of hopes, uh,
365
00:14:10.665 --> 00:14:12.965
you were looking to get out of the show this week?
366
00:14:13.125 --> 00:14:15.445
I know it's a big networking show, so people come,
367
00:14:15.805 --> 00:14:17.685
I think a lot for the connection and the conversation.
368
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Um, so yeah.
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Any, any big revelations
370
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or, um, any, any advice for people that have come, like,
371
00:14:24.645 --> 00:14:28.365
Hey, I think, I hope you go away from Afla, uh, knowing this
372
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or taking this action item?
373
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Yeah, actually it was the session that I just came from.
374
00:14:32.565 --> 00:14:34.525
Okay. Um, it was a panel of fleet managers,
375
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all fleet managers on the stage.
376
00:14:36.245 --> 00:14:37.565
Actually Holman was on there as well.
377
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And they were really talking about, um, you know, having
378
00:14:41.265 --> 00:14:45.005
to champion within your organization with the C-suite
379
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and how important it is to get their buy-in.
380
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Um, you know, they even mentioned about telematics
381
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and um, you know, sometimes there's a lot
382
00:14:53.245 --> 00:14:54.845
of pushback from the leadership on that,
383
00:14:54.845 --> 00:14:56.005
even though it's the right thing to do.
384
00:14:56.065 --> 00:14:57.765
We know to keep your drivers safer Right.
385
00:14:57.825 --> 00:14:59.645
And, um, optimize your fleet
386
00:14:59.675 --> 00:15:01.365
that this data's really critical.
387
00:15:01.865 --> 00:15:05.125
Um, and I think for me, the big takeaway, the big aha in
388
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that is how to effectively communicate with the c-suite
389
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and what's important to them.
390
00:15:11.025 --> 00:15:12.965
Um, what may be important to the fleet manager
391
00:15:12.985 --> 00:15:14.445
and what they wanna get across isn't
392
00:15:14.445 --> 00:15:15.525
always important to that c-suite.
393
00:15:15.585 --> 00:15:17.325
So really understanding procurement, you need
394
00:15:17.325 --> 00:15:19.965
to speak their language when you're talking with the CEO.
395
00:15:20.265 --> 00:15:22.645
You know, read that earnings report, know what's important
396
00:15:22.645 --> 00:15:24.525
to them, know where you know his, his focus is
397
00:15:24.525 --> 00:15:26.725
or her focus is, and really speak to them on that
398
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to get that buy-in.
399
00:15:28.365 --> 00:15:30.165
I thought that was a really interesting Mm-Hmm.
400
00:15:30.245 --> 00:15:31.365
Um, session that they had. So
401
00:15:31.365 --> 00:15:33.845
How, how are, is implementing telematics going
402
00:15:33.845 --> 00:15:35.085
to improve the bottom line?
403
00:15:35.085 --> 00:15:37.565
Exactly. It's, it always comes down to that, right? Yeah.
404
00:15:38.065 --> 00:15:40.285
Um, and, and did they talk about here's
405
00:15:40.285 --> 00:15:43.365
how I convinced my c-suite to invest in this area
406
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to give us the tools that we need.
407
00:15:44.925 --> 00:15:46.365
I mean, 'cause I think that's, fleet
408
00:15:46.365 --> 00:15:47.565
managers are always looking for that.
409
00:15:47.565 --> 00:15:48.605
Like, what do, what do I say?
410
00:15:48.995 --> 00:15:50.285
Yeah, there was a really good example.
411
00:15:50.625 --> 00:15:52.525
Um, one of the individuals gave,
412
00:15:52.825 --> 00:15:56.205
and when they were going to implement, um, the telematics,
413
00:15:56.315 --> 00:15:59.085
they gave the devices to all their procurement team
414
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and the procurement leader to get their buy-in
415
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to show where the savings are.
416
00:16:02.485 --> 00:16:04.605
And it turns out their procurement leader was the worst
417
00:16:04.605 --> 00:16:06.565
driver, um, out of all of them,
418
00:16:06.705 --> 00:16:08.485
but had the biggest potential of savings.
419
00:16:08.705 --> 00:16:11.365
So he was, um, he certainly leaned into that
420
00:16:11.455 --> 00:16:12.685
after he saw the data. Yeah.
421
00:16:12.785 --> 00:16:14.125
How very, very interesting. Yeah.
422
00:16:14.695 --> 00:16:16.485
Where do, where do you think the pushback comes from?
423
00:16:16.545 --> 00:16:18.405
Is it really mostly cost driven?
424
00:16:18.705 --> 00:16:21.885
You know, like just if we're not gonna see some sort
425
00:16:21.885 --> 00:16:23.365
of ROI immediately,
426
00:16:23.625 --> 00:16:25.805
or if I don't understand the ROI, is it,
427
00:16:25.825 --> 00:16:27.085
is it truly cost driven?
428
00:16:27.965 --> 00:16:29.805
I don't feel it is. I think a lot
429
00:16:29.805 --> 00:16:31.325
of it is a misunderstanding, right?
430
00:16:31.595 --> 00:16:33.845
Some people really think it's Big Brother. Mm-Hmm.
431
00:16:33.845 --> 00:16:35.965
Um, I'm being tracked where I'm at.
432
00:16:36.065 --> 00:16:37.205
You know, you look at Europe,
433
00:16:37.235 --> 00:16:39.245
they have workers' councils over there that are very,
434
00:16:39.705 --> 00:16:41.325
you know, against having that type
435
00:16:41.325 --> 00:16:43.365
of tracking per se, in the vehicle.
436
00:16:43.905 --> 00:16:45.805
Uh, but the reality is nobody's sitting
437
00:16:45.805 --> 00:16:47.325
behind a desk watching you drive.
438
00:16:47.325 --> 00:16:49.245
Right? No. You know, and where you're going, no.
439
00:16:49.425 --> 00:16:52.445
Um, you know, you need to drive, you know, according
440
00:16:52.445 --> 00:16:53.685
to your company policies.
441
00:16:53.685 --> 00:16:55.045
And if you're doing that, the
442
00:16:55.245 --> 00:16:56.285
telematics shouldn't make a difference.
443
00:16:56.285 --> 00:16:57.725
Where you're going, how long you're there
444
00:16:57.725 --> 00:16:58.765
shouldn't make a difference.
445
00:16:59.425 --> 00:17:01.925
Um, so I really think it's about a misunderstanding of,
446
00:17:01.985 --> 00:17:04.525
of really the use of that data
447
00:17:04.545 --> 00:17:06.405
and that, that particular technology.
448
00:17:06.925 --> 00:17:08.245
I do think ROI has a play,
449
00:17:08.245 --> 00:17:10.925
but gosh, there's so much ROI that comes from telematics
450
00:17:10.995 --> 00:17:12.605
that that shouldn't even be,
451
00:17:12.665 --> 00:17:14.285
you know, a naysayer at that point.
452
00:17:14.405 --> 00:17:15.845
I think everyone knows there's value from that,
453
00:17:15.845 --> 00:17:17.645
but it's really about the tracking Mm-Hmm.
454
00:17:17.725 --> 00:17:19.885
I think and the privacy that comes with that.
455
00:17:20.265 --> 00:17:23.005
Got it. So that's a misconception.
456
00:17:23.035 --> 00:17:26.165
When it comes to the use of telematics for driver safety,
457
00:17:26.745 --> 00:17:29.045
are there any other misconceptions about
458
00:17:29.185 --> 00:17:30.485
how telematics is used,
459
00:17:30.545 --> 00:17:32.525
or, I feel like we need a new word,
460
00:17:32.905 --> 00:17:34.365
you know, telematics and beyond.
461
00:17:34.915 --> 00:17:38.285
Yeah. How, are there any other misconceptions in other areas
462
00:17:38.555 --> 00:17:40.405
that, uh, you feel are important to address?
463
00:17:40.645 --> 00:17:42.165
I mean, I really, I think it, it,
464
00:17:42.225 --> 00:17:44.165
the drivers themselves Mm-Hmm.
465
00:17:44.285 --> 00:17:45.645
Um, especially if it's new for them,
466
00:17:46.155 --> 00:17:47.965
they may not feel the system is fair.
467
00:17:48.065 --> 00:17:50.045
You know, the, the historical way is
468
00:17:50.045 --> 00:17:52.485
that you measure drivers as you have a scorecard.
469
00:17:52.995 --> 00:17:55.085
Many, many telematics companies do that.
470
00:17:55.385 --> 00:17:56.485
It is a bit subjective
471
00:17:56.685 --> 00:17:58.245
'cause the fleet manager can determine
472
00:17:58.315 --> 00:18:00.085
what the rules are of the scorecard.
473
00:18:00.465 --> 00:18:03.565
And so I think what you've seen from Geotab, um, over time
474
00:18:03.565 --> 00:18:05.805
and we've released, is we're looking
475
00:18:05.805 --> 00:18:06.845
at things a little bit differently.
476
00:18:07.025 --> 00:18:10.365
We have enough data now worldwide on different vehicle types
477
00:18:10.465 --> 00:18:12.645
and vocations, how those vehicles are being used
478
00:18:13.035 --> 00:18:14.725
that really we're focused more on
479
00:18:15.385 --> 00:18:17.685
who are your riskiest drivers, right?
480
00:18:17.745 --> 00:18:21.525
So being able to predict within a million miles driven which
481
00:18:21.525 --> 00:18:22.805
of these drivers is more likely
482
00:18:22.805 --> 00:18:24.325
to get in an accident than another.
483
00:18:24.905 --> 00:18:27.325
And we're also introducing some new and,
484
00:18:27.425 --> 00:18:28.525
and cool programs
485
00:18:28.525 --> 00:18:31.645
that will be more driver focused on incenting them
486
00:18:31.825 --> 00:18:32.925
to be better drivers.
487
00:18:33.025 --> 00:18:34.725
Mm-Hmm. Right. So it's not about Big Brother,
488
00:18:34.875 --> 00:18:38.005
it's just about helping them improve to be a better driver,
489
00:18:38.585 --> 00:18:41.205
um, against a set of variables
490
00:18:41.205 --> 00:18:42.565
that they can actually control
491
00:18:42.625 --> 00:18:45.325
and feel like, okay, I, I feel good about this.
492
00:18:45.325 --> 00:18:46.845
Right. I feel like it's not, I'm not,
493
00:18:46.865 --> 00:18:48.045
the system isn't rigged.
494
00:18:48.255 --> 00:18:49.485
We're not out to get me. Right.
495
00:18:49.485 --> 00:18:50.485
You're not looking over my shoulder.
496
00:18:50.665 --> 00:18:52.605
So I, we're, we're doing, we've done a ton
497
00:18:52.605 --> 00:18:55.965
of research over the past several years on really shifting
498
00:18:56.075 --> 00:19:00.325
away from just a pure scorecard to more of looking at risk.
499
00:19:00.325 --> 00:19:01.685
Mm-Hmm. And how risk affects,
500
00:19:01.965 --> 00:19:03.605
'cause that's where the ROI is.
501
00:19:03.605 --> 00:19:06.285
Right. An accident costs a massive amount of money. Right.
502
00:19:06.285 --> 00:19:09.325
Especially if it's a large brand name company. Right.
503
00:19:09.325 --> 00:19:11.925
They're gonna get sued, um, if there's a bad accident.
504
00:19:11.925 --> 00:19:13.285
Right. So anything we can do there
505
00:19:13.285 --> 00:19:15.205
to control those accidents, um,
506
00:19:15.385 --> 00:19:18.725
the avoidable ones especially, uh, is going to easily pay
507
00:19:18.725 --> 00:19:20.605
for any, any system that you would implement.
508
00:19:20.815 --> 00:19:25.805
Right. So looking ahead three years, maybe five years,
509
00:19:26.455 --> 00:19:29.965
where would you like to see the fleet industry as a whole,
510
00:19:30.465 --> 00:19:32.445
you know, the, the future of fleet, if you will?
511
00:19:34.045 --> 00:19:35.805
I have, um, a good answer for that.
512
00:19:36.045 --> 00:19:37.525
I think where I'd like to start, um,
513
00:19:37.585 --> 00:19:40.805
for me it's really global standards for the,
514
00:19:41.065 --> 00:19:42.245
the data coming off the vehicle.
515
00:19:42.985 --> 00:19:45.485
Um, you know, we're seeing this convergence right now from
516
00:19:45.485 --> 00:19:48.005
aftermarket telematics device like our Go nine
517
00:19:48.145 --> 00:19:50.365
and then using OEM embedded technology.
518
00:19:50.745 --> 00:19:53.605
So we offer both. So you have solution, you have choice.
519
00:19:54.185 --> 00:19:56.645
Um, but the problem with that is it's great, right?
520
00:19:56.785 --> 00:19:58.645
You don't have to do aftermarket installs.
521
00:19:58.665 --> 00:20:00.485
You can get it straight from the manufacturer.
522
00:20:01.185 --> 00:20:02.845
Um, but the data's all different
523
00:20:03.065 --> 00:20:05.645
and everyone provides it in a different format.
524
00:20:05.955 --> 00:20:07.765
It's a different frequency, different fidelity,
525
00:20:07.945 --> 00:20:09.125
And then you have to figure out Yeah.
526
00:20:09.145 --> 00:20:11.245
How do you work with that data? Yeah, yeah.
527
00:20:11.245 --> 00:20:12.805
Or you, you know, you lack certain things
528
00:20:12.945 --> 00:20:14.125
and um, you know,
529
00:20:14.125 --> 00:20:15.885
aside from the pricing and all that as well Mm-Hmm.
530
00:20:15.965 --> 00:20:17.085
But just really global standards.
531
00:20:17.345 --> 00:20:20.125
So Geotab is working really hard with a lot
532
00:20:20.125 --> 00:20:21.405
of other industries out there.
533
00:20:21.745 --> 00:20:23.245
Um, even the OEMs are involved
534
00:20:23.245 --> 00:20:25.245
with an organization called CO vesa Mm-Hmm.
535
00:20:25.345 --> 00:20:27.405
And they're really focused on global standards.
536
00:20:27.405 --> 00:20:29.725
And for me, I think, you know, that's critical.
537
00:20:29.785 --> 00:20:30.965
We need those standards.
538
00:20:31.065 --> 00:20:33.165
We need regulation as well when it comes to privacy,
539
00:20:33.315 --> 00:20:35.725
when it comes to AI and things along that lines.
540
00:20:36.025 --> 00:20:38.525
But I really think it starts with standards.
541
00:20:38.885 --> 00:20:40.685
'cause we need to make sure we're able to get the data
542
00:20:40.705 --> 00:20:42.765
that's needed off those vehicles,
543
00:20:42.765 --> 00:20:45.525
and that we have high fidelity, that we have,
544
00:20:45.525 --> 00:20:46.605
you know, in the right format.
545
00:20:47.065 --> 00:20:49.645
So they're able to, to evolve, to continue to grow
546
00:20:49.825 --> 00:20:51.925
and, you know, use this data as they do today,
547
00:20:51.985 --> 00:20:53.245
but actually get better too.
548
00:20:53.305 --> 00:20:55.045
So global standards for me is the big one.
549
00:20:55.185 --> 00:20:57.845
That's awesome. I, I think for me, it's more about just
550
00:20:57.845 --> 00:20:59.005
where I see it going
551
00:20:59.225 --> 00:21:02.085
and it's, it's, as a fleet manager, you need to be prepared
552
00:21:02.105 --> 00:21:04.485
for different forms of transportation.
553
00:21:05.065 --> 00:21:07.645
So I think, you know, we, we see in Europe, there's lots
554
00:21:07.645 --> 00:21:09.445
of low emission areas now,
555
00:21:09.585 --> 00:21:12.005
and like you have to have an EV to go in a certain area.
556
00:21:12.005 --> 00:21:13.725
Mm-Hmm. Like Amsterdam in particular,
557
00:21:13.755 --> 00:21:16.325
that you can't go into certain areas unless you have an ev.
558
00:21:16.665 --> 00:21:19.085
So I think, um, having an open mind
559
00:21:19.085 --> 00:21:21.805
and doing a lot of research on what are the different modes
560
00:21:21.805 --> 00:21:23.885
of transportation that I can get my products
561
00:21:23.885 --> 00:21:26.245
and services to outside of a standard vehicle
562
00:21:26.245 --> 00:21:27.485
that I might be using today.
563
00:21:27.815 --> 00:21:30.125
Maybe even car, like sharing a vehicle, right.
564
00:21:30.485 --> 00:21:33.285
Mobility's a service. So all those tech, they're gonna have
565
00:21:33.285 --> 00:21:35.645
to be a little more savvy around technology Mm-Hmm.
566
00:21:35.825 --> 00:21:37.485
Um, than they are today.
567
00:21:37.635 --> 00:21:40.845
It's not just, and hopefully I, I think FMCs are evolving
568
00:21:40.845 --> 00:21:43.845
to help their larger clients with these other modes
569
00:21:43.845 --> 00:21:45.885
of transportation, short term rentals,
570
00:21:46.345 --> 00:21:47.685
car sharing, those types of things.
571
00:21:47.705 --> 00:21:50.725
So definitely you're seeing some of that now in Europe,
572
00:21:50.825 --> 00:21:52.845
and I think we'll see more of that over here in the states
573
00:21:52.865 --> 00:21:55.005
as we start to get a little more adoption of,
574
00:21:55.385 --> 00:21:56.405
of those types of things here.
575
00:21:57.365 --> 00:22:00.325
I think both really excellent points on, on the,
576
00:22:00.385 --> 00:22:02.765
the data, um, standards.
577
00:22:03.195 --> 00:22:05.045
It's so true, right? Because you also,
578
00:22:05.425 --> 00:22:08.285
if you're importing different formats of data, you're having
579
00:22:08.385 --> 00:22:12.245
to, um, sort of change it in a way, right?
580
00:22:12.245 --> 00:22:14.045
You know, because you have to or interpret it if
581
00:22:14.045 --> 00:22:14.725
You will. Normalizing,
582
00:22:14.725 --> 00:22:15.725
Normalize it. And
583
00:22:15.725 --> 00:22:17.365
so then do you lose fidelity?
584
00:22:17.595 --> 00:22:19.365
Like you said, you lose integrity of the data
585
00:22:19.825 --> 00:22:21.965
and then if you're relying so much on the data,
586
00:22:22.305 --> 00:22:24.885
but it's lost integrity in the transformation process,
587
00:22:25.015 --> 00:22:26.805
maybe the data isn't so accurate anymore.
588
00:22:26.805 --> 00:22:29.605
Right? And so if you're relying on this data to make
589
00:22:30.165 --> 00:22:34.085
business decisions, you need it to be, uh, as, as good
590
00:22:34.085 --> 00:22:35.525
as when it first was recorded.
591
00:22:35.625 --> 00:22:37.405
So it's, it's a great point. And
592
00:22:37.405 --> 00:22:40.405
Consistent and, and what we're finding too, um, you know,
593
00:22:40.405 --> 00:22:43.645
from model year to model year, um, firewalls, you know,
594
00:22:43.645 --> 00:22:44.805
come into play, et cetera.
595
00:22:44.805 --> 00:22:46.565
So some of the data that you used to be able to get,
596
00:22:46.665 --> 00:22:49.205
you know, pretty freely from the OBD two port is starting
597
00:22:49.205 --> 00:22:51.005
to be restricted even off the can.
598
00:22:51.005 --> 00:22:52.125
It's starting to be restricted.
599
00:22:52.145 --> 00:22:55.725
So we really need the OEMs, um, everyone in the industry
600
00:22:55.725 --> 00:22:58.565
to come to together and really, you know, figure this out.
601
00:22:58.565 --> 00:22:59.925
Mm-Hmm. Collectively. Mm-Hmm.
602
00:23:00.005 --> 00:23:00.965
And I think the only way to do that
603
00:23:00.965 --> 00:23:02.365
is really through those standards. Standards,
604
00:23:02.365 --> 00:23:03.365
Yeah. Mm-Hmm. That's great.
605
00:23:03.365 --> 00:23:05.725
And then to your point, um, Greg,
606
00:23:05.735 --> 00:23:09.405
about, um, the different forms of, of transportation
607
00:23:09.545 --> 00:23:11.285
and how people are moving differently, right?
608
00:23:11.625 --> 00:23:14.285
Not just as consumers, but you know, in fleets
609
00:23:14.545 --> 00:23:16.485
and drivers, they,
610
00:23:16.485 --> 00:23:19.285
maybe they're not gonna be using a, an actual vehicle.
611
00:23:19.295 --> 00:23:21.205
Maybe it'll be a different type
612
00:23:21.205 --> 00:23:23.245
of modality. Who know, who knows, right?
613
00:23:23.565 --> 00:23:25.565
I mean, I live near a college in Dallas,
614
00:23:25.905 --> 00:23:28.805
and I walk that campus frequently with my dog,
615
00:23:29.505 --> 00:23:32.565
and there's these little mini robots that deliver food
616
00:23:32.565 --> 00:23:33.565
to the kids in the dorm.
617
00:23:34.025 --> 00:23:35.965
And we, my dog chases 'em all over the place,
618
00:23:36.245 --> 00:23:37.725
but they're literally, I, I, you know,
619
00:23:37.905 --> 00:23:39.245
in the beginning I saw one
620
00:23:39.245 --> 00:23:41.685
or two, now I see them, there's at least 15
621
00:23:41.685 --> 00:23:43.645
or 20 running around every morning when I'm out there.
622
00:23:43.865 --> 00:23:46.005
Wow. Who, who knew, right?
623
00:23:46.165 --> 00:23:48.725
I mean, it's, as they say, if you wanna know
624
00:23:48.725 --> 00:23:50.165
what the future looks like, you just watch what,
625
00:23:50.165 --> 00:23:51.285
you know, a um, yeah.
626
00:23:51.445 --> 00:23:53.765
A movie, you know, or like the futuristic movies
627
00:23:53.825 --> 00:23:55.125
and eventually it'll happen.
628
00:23:55.265 --> 00:23:57.285
And I feel like it totally has happened. Well,
629
00:23:57.285 --> 00:23:58.805
And I'm just thinking too, Greg, that point,
630
00:23:58.955 --> 00:24:01.445
like somebody has to manage all those little robotic
631
00:24:01.515 --> 00:24:02.515
Yeah, exactly. Movers.
632
00:24:02.515 --> 00:24:03.405
Exactly. Exactly.
633
00:24:03.635 --> 00:24:05.205
Yeah. It's another challenge for fleet.
634
00:24:05.455 --> 00:24:06.965
Right. Well, and then, you know,
635
00:24:06.965 --> 00:24:09.285
in a hundred years when there's flying cars, right,
636
00:24:09.905 --> 00:24:11.285
You'll Really have a big challenge.
637
00:24:12.155 --> 00:24:14.045
Well, this has been a really lovely conversation.
638
00:24:14.305 --> 00:24:17.285
Um, lots to, to think about, lots to solve,
639
00:24:17.345 --> 00:24:18.365
but it's very exciting.
640
00:24:18.625 --> 00:24:20.125
Um, lots of possibility.
641
00:24:20.385 --> 00:24:23.205
And it's really kind of cool to see
642
00:24:23.205 --> 00:24:24.925
where things have been going. Right.
643
00:24:25.145 --> 00:24:26.925
It really is exciting times and yeah.
644
00:24:26.925 --> 00:24:28.965
Gonna get more exciting, I think, in the few years.
645
00:24:29.275 --> 00:24:31.045
Very cool. Well, thank you so much for joining us.
646
00:24:31.045 --> 00:24:32.925
This has been a really great conversation. Thanks for
647
00:24:32.925 --> 00:24:33.805
Having us. Thank you. Thank you.
648
00:24:34.465 --> 00:24:36.165
Thanks for listening to The Mile Marker podcast.
649
00:24:36.625 --> 00:24:38.925
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650
00:24:39.015 --> 00:24:40.725
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651
00:24:41.065 --> 00:24:43.765
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652
00:24:43.765 --> 00:24:45.685
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653
00:24:46.145 --> 00:24:48.525
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654
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655
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