Why Frontline Devices Keep Failing (and the Downtime Cost Nobody Tracks)

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I'm Brett Cooper and this is the Frontline Mobility Edge, where we discuss the latest in mobile device technologies and how they're shaping the frontline landscape business.
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Thank you for joining us.
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Let's get started.
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Well, welcome to eight this episode of the Frontline Mobility Edge.
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I'm Brett Cooper, joined today by Gary Lee from B2M.
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Gary, thank you for hopping on with me.
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My pleasure.
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Thanks for having me.
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So Gary has been um doing a lot of work in the enterprise mobility for McCall-I said the last 20 years, but you correct me, he said it was last 40, and I called out you can't you can't you can't claim when you're 10 years old doing it.
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But uh you know, I appreciate you hopping on with me today.
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But you've you've been in this industry for a very long time.
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I know we work we've worked together for over a decade and various different aspects.
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Um maybe from a framing perspective, you could talk a little bit about what you've done, what you've seen over the last few decades, and how that's led up to your current role at at BDM.
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Yeah, I'd be happy to.
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So started out many, many years ago in the software space, then sort of worked my way into telecommunications back in the day when we were making a big transition from analog to digital switching and then sort of working in the internet days when it was very, very early stage.
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I think we got one of the first browsers out of Champaign, Illinois, and played around with that.
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And I know we were definitely one of Cisco's first customers.
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So you can look at my career over the decades I've been in the technology space as really being at the forefront of major changes.
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Whether it was analog to digital, the advent of the internet, uh, the rise of enterprise mobility to move beyond, you know, very rugged devices in the warehouse that never changed to suddenly people showing up at work with their brand new iPhone saying, Hey, I want to connect this to the network.
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And through that, I've been able to run or be part of about six global startups that have been able to take advantage of all those changes.
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And the reason I bring that up is this it's sort of been the path that led me to B2M.
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Before I came here, I was a C-level executive at one of the biggest managed service providers in North America.
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Uh, we were working almost exclusively in enterprise mobility and helping companies better manage their enterprise mobile devices and apps with a big help desk center and warehouse and break fix repair and everything in between.
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But over nine years ago, I started hearing the same story over and over from enterprise customers.
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And it went like this frontlines or mobility is really important to us now.
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It's moved beyond just the warehouse and devices that never change.
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Suddenly we've got a lot more people using mobility.
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We depend on it now to run our business.
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If they're having to call you with help desk calls, by definition, they're not working.
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We're down.
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So how can you flip the model?
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How can you become more proactive and just see problems as they happen and fix them?
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Well, I thought we've been doing that forever.
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You know, whether it's called SNMP or CMEP or whatever technology you want to throw at it, there's got to be a system out there that we can just start looking at all these mobile devices and reporting on them.
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Um, that's where you and I met, actually, was I went out in the market to survey and find out who has any solution like this.
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Blue Fletch had one, uh, B2M solutions out of the UK had one.
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I looked at the market, I looked at the fact it was a massive market that hadn't been exploited.
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And the startup guy in me said, these are the kind of odds I like.
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And I jumped shipped to come here about eight years ago, and it's been a tremendous journey ever since.
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Nice.
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And and just for context, maybe you could talk a little bit about so B2M, the types of customers you work with, the types of solutioning you do with your customers or clients, and then you the outcomes you look for.
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So when somebody hires or pays for B2M, what are they bringing into the default tour?
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I mean, we're a software company through and through.
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All we do is produce software, and we really only focus on one software product.
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It's a product we call LMS, which is a mobile DEX problem to help customers figure out the health and the usage of older mobile assets.
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In terms of the customers we work with, they're all enterprise customers.
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Uh, we sell exclusively to the enterprise.
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Typically 500 employees and up is kind of our sweet spot.
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And we specifically focus on the enterprise on frontline workers.
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These are the workers who don't have an office.
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They're typically outside the four walls of the corporation, they're in the warehouse, they're in the distribution center, they're in the truck making delivery or service calls.
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You know, these are the workers ultimately producing and delivering the goods and services of the company.
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These workers typically have a mobile device in their hand.
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That is their computer.
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That is the way they get things done.
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And those are the workers we're focused on because they're the ones most dependent on mobility.
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And right now, the traditionally, the only way IT knows they have a problem with those devices is when they stop and pick up the phone and ring the help desk and say, help me.
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So we're flipping that model from being reactive to proactive and helping these enterprises better figure out the health and usage of these critical mobile assets for the frontline workers.
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Um we go to market through channel partners.
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Uh, either we sell partners or we do have partners who are integrating our software into their own services and software.
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Well, I I I have a question on the terminology.
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That's the first topic I had, the rise of mobile DEX.
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So I think you and I were joking previously when we talked about this.
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You know, DEX in the 90s was I was doing some vending machine stuff, and there was an interface called DEX, and then Samsung released a product called DEX, I think about 12 years ago for digital display.
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When you say DEX, can you articulate what that terminology means in the in your power lens?
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Sure.
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I mean, DEX is a fairly well-understood industry segment now, especially if you read any of the Gartner reports or forest reports.
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DEX stands for digital employee experience.
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DEX, digital employee experience.
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It's a set of software and really underlying processes or processes of how do we constantly evaluate and look at the experiences our employees were having with the digital technology we're putting their hands every day.
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Is it positive, negative?
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How's it impacting them?
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So it's a whole architecture that's evolved over the last years and really, really exploded during COVID when suddenly every IT leader had to send an employee home with a desktop and say, good luck.
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You know, DEX software emerged very quickly because the DEX software in those days was predominantly Windows balanced or Windows um focused and allowed them to understand the health of these mobile devices or health of these Windows devices out in the field and also immediately fix problems as they occurred.
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So DEX as an architecture is not anything new in the industry.
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It's something that's well understood.
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We've got companies doing over 100 million in revenue in this space.
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What is new is that DEX has historically dunks inside the four walls on the Windows-based machines.
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We're now taking those same concepts and those same software architectures into the frontline worker and the mobile world and extending DEX beyond the front walls to these critical workers delivering and producing goods and services.
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So hence mobile DEX.
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On that, the the you know, one of the questions people might ask is like I have Sodixite, I have Intune, I have Workspace One.
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How shouldn't those tools give me everything I need?
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Like what's the gap that that you see that's between the just base level MDM versus like the high-level analytics you provide?
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Sure.
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They're two different toolkits.
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It's like the difference between a hammer and a screwdriver.
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MDM tools are primarily about change management.
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Use the tool to make the configuration changes you need to on a daily basis, policy changes, security updates, update software, update OSs and drivers.
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These are change management tools, and they're fantastic.
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They're well designed for making changes to devices that are deployed throughout the corporation.
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They're never designed.
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I mean, the software architecture alone, they're never designed to give a real-time intelligence layer to tell you what's going on with those devices, those applications, those batteries, those network connections.
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And we see this all the time.
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We especially see it.
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The best example I can give you is you'll use an MDM to push an app update out to the field.
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So you've got an application running on all the devices, a new version's come out with some enhancements, you do all the regression testing, you feel confident it's bug-free.
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Using the MDM, you push it out to all the devices.
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The devices report back to the MDM and say, everything's good.
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I received it, I'm running it.
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And so if all you've got is that MDM console on your screen, you see a green light showing you were successful.
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When in reality, out in the field, all those devices that got the app update are now in a perpetual reboot loop or can no longer maintain a network connection, or their battery life just went from 10 hours a day to four hours a day.
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And you only begin to see this as trouble tickets start rolling in, and you go, hmm, where's the common thread here?
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Oh, all these people got an app update two days ago.
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If you have an intelligence layer like ours there, then immediately when the MDM does its job, you can begin reporting on are these devices okay?
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And in the example I gave you of reboots, we would see and in our system, we would see app update received, and then we will begin to see reboot, reboot, reboot, reboot, and it would flag.
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And so having that intelligence layer is what we do, and it's not built into the M2 MDM tools, and I don't think it ever will be, because the architectures are just completely different in how they need to report the data.
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Yeah, it definitely makes sense.
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And as you said, all those problems, it gave me a lot of anxiety of the uh of of war rooms I've been in over the last 15 years of you know, somebody pushed out an update and it it broke the network, it broke this.
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Never fun to bring the never fun to bring people down.
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Yeah, it's not a not a pleasant experience.
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No, it is not.
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I I one of the things I saw in the report, um, you know, when I looked through it, that the the stoppages from let me make sure we get this right, stoppages from 2019 to 2025 for frontline workers went from 51 to 81 percent, where they've reported it, uh, you know, a stoppage during their uh during their experience with device.
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What what caused this jump?
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Is it more that we're measuring it or seeing it?
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I feel like we have better devices, we have better networking connectivity, we have better monitoring.
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How can there be this 30% jump over five or six years?
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A couple of factors here.
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Um first of all, it's getting more complex.
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It just is.
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The devices are getting more complex.
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You know, we've now got AI being rolled onto the devices.
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That's a whole new complexity layer and a whole new layer of we're gonna constantly be updating these devices with new firmware and new patches and new this.
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At the same time, we've grown from a small number of applications to a lot more applications being loaded on the device.
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Those applications need to be updated constantly.
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And so those factors alone of just how do we keep our software suite in sync is a nightmare.
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And we work with customers all the time that are very good at regression testing and making sure before they send the patch out, they've thoroughly tested and everything works.
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But just because it worked in the lab doesn't mean it's going to work in the real world of the wilds.
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And so things have just gotten more complex on the device.
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Uh, the second thing that we see consistently, the 5G rollout or the rollout to 5G technology on the network side, it has not gone well.
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It has not gone well at all.
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I see this a lot in the UK, and I'm I'm there about every three weeks.
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And our customers will sit down with us and they'll look at what the network maps from the operators, the network maps from the regulators say.
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Here's 5G connectivity, and it's everywhere.
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The reality is it's in a lot of very densely populated areas, it's nowhere.
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You can't get a signal.
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And so you you raise the question by saying networks have gotten better.
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When they work, yes.
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When they don't, we don't we've gone from 5G to no G often.
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So the network layer has gotten more complex.
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The mixture of applications and updates and operating systems and firmware patches has gotten more complex.
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Your your average IT leader is dealing with a very complex beast now in mobility, and they need better tools to do it.
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So the increase in complexity increase in actual just application footprint is driving a lot of these just increases in the issues.
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Um and then so this report, so you guys, so I I mentioned it here, but the the annual state of enterprise mobility, you guys have done this for six or seven years now.
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Seven years.
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Who when you guys go out to the market, like who are you surveying?
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What does this report actually look for to are you talking at the the MDM guys, infrastructure guys, uh uh operations guys?
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What are you guys interviewing when you when you go talk to folks?
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Well, it is an annual report.
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And then first and foremost, we do commission this with a third-party market research firm.
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We have no hands in the selection of research panels.
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We certainly work up the set of questions we want to ask this year, and we work with the market survey term to get those, uh a team to get that ready.
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But when it comes to actually talking to people, we don't have our hands in the mix at all to make sure the data is clean and there's no bias in the data whatsoever.
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Um, we asked them to go out and look at companies that are a minimum of 500 employees in size.
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We just think that gives us a pretty good basis.
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And then we typically run the survey across the US, Canada, a little bit of Mexico over the years.
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And then we go after the UK, France, Italy, Germany, and Spain as our traditional markets that we're surveying, again, to bring any geographic biases that might exist in the data.
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Um, there's two sets of people we're going after.
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We're looking for IT leaders in charge of mobility.
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And so we screen on, you know, are you ultimately the person in charge of mobility?
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Are you charge of you in charge of supporting mobility?
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We want to get their view of what's going on in their department when it comes to trouble tickets, the complexity of managing mobility, you know, what are they seeing and hearing from their frontline workers, et cetera.
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So we survey them with one survey question.
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But then we also go out and we seek frontline workers who depend on a mobile device to do their job.
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We find those frontline workers in corporations of 500 employees and up, and we survey them about their daily experience of depending on that mobile device, mobile apps, mobile network connection to do their job every day.
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And then we roll those two surveys up.
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It gives us a good comparison of what IT sees or what frontline is experiencing.
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And we've been tracking the growth and the non-growth and everything in between for about seven years now.
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So on those two user groups, is there a disparity between the leadership and the frontline folks of leadership is like everything's great, and the frontline folks are like everything's terrible is there?
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Like how how big is that disparity between this group and the other and the uh people actually with hands-on devices?
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The single biggest disparity is definitely when we ask the key questions for the frontline workers of how often they have problems that keep them from working.
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And that's a key question we ask.
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Because, you know, it's one thing if you get a little glitch, no big deal.
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We specifically want to focus on those problems where I had to stop work.
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And so when we ask frontline workers how often that occurs, and we ask IT how often that occurs, we've seen over the seven years, as you pointed out, Brett, a huge rise from frontline workers.
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Things are getting worse for frontline workers out there.
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But what's really fascinating is when you look at IT and the number of tickets that IT sees, we see a rise every year, but it hasn't followed the same growth path that we've seen on what frontline workers are telling us.
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There's some there's some factors there.
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Um and we we've done some survey on this over the years.
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A lot of frontline workers just aren't reporting the problems anymore.
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They're just figuring this is a normal course of business and reboot the device and go on with life and try and get my job done.
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They're not calling the help desk anymore.
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And yet, the cost to the enterprise every time an issue occurs is still there.
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They can't deliver the package.
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They can't stand the barcode and get the delivery out the door, they can't finish production.
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There's a real cost to the company every time this happens, which is why it's critical that we get that data coming out of what the frontline workers is actually seeing, and we translate that using software to something that shows up on the screen.
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So that number in in the survey, I'm sure I got this right.
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You reported 7.4 billion was your estimate for paid downtime in 2025.
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That is a huge number, but also as I started thinking about it and extrapolate it out, it seems like it's actually kind of low.
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Like, where do you think that number actually is, especially and I know a lot of people don't necessarily want to say that that you know they're not getting work done and you know, claim that um because they want to keep their jobs.
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But like where would you actually pin that number out if you had to guess of where it is?
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Is it 40 to 100, 100 billion in outages?
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No, I don't think it's that hot.
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Well, it depends.
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Um let's talk about how we derive that number, and then we'll we'll come back to what we think the number could be.
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The way we derive that number is in the survey data, we track how many times per week per month frontline workers say they have a problem where they can't work.
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Okay.
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So we're able to track in the data and say this is how many times this is occurring.
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Obviously, that's a sample size of the whole general population.
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So we take that number and then we look at how many frontline workers exist across the universe of all the countries we survey, and we can extrapolate how many workers experience downtime every single month.
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We then look at um an average downtime of 30 minutes, and that's one of the variables that we just select.
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Now we track, we track in our survey how long it typically takes to fix a problem.
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We chose 30 minutes for this calculation.
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So we know how many times an employee was down, they're down for 30 minutes, and then we just take the wages in each country and say, if you were down for 30 minutes and you get this much per hour as a wage, we roll up the number and we get to that$7 billion US figure.
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Why is that conservative?
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We're not including IT support cost in there.
00:17:21.279 --> 00:17:21.599
Okay.
00:17:21.920 --> 00:17:29.519
So while they're down for 30 minutes, they're probably on the phone call with or on the phone with IT, and I there's certainly a cost we all know of IT getting involved.
00:17:29.599 --> 00:17:31.680
We've got headcount, we've got overhead, we've got everything.
00:17:31.839 --> 00:17:34.079
That's not included in the$7 billion figure.
00:17:34.319 --> 00:17:36.880
Also, a lot of problems take longer than 30 minutes.
00:17:36.960 --> 00:17:41.920
Um, if it's a broken device, if it's a lost device, if someone's out in the field, they've got to come back to the office.
00:17:42.079 --> 00:17:43.839
It's gonna take an hour, hour and a half.
00:17:44.000 --> 00:17:45.680
And again, these are numbers we track.
00:17:45.920 --> 00:17:53.680
So we we feel conservatively that we could be looking at something more like 27 billion if we begin to factor some of these other things in.
00:17:53.759 --> 00:17:56.160
And that's just productivity loss.
00:17:56.240 --> 00:17:57.599
I can't stress that enough.
00:17:57.759 --> 00:17:59.920
That's only the downtime we're seeing.
00:18:00.000 --> 00:18:09.440
It's not also then looking at the cost of replacement devices, lost devices, you know, other things that are happening around this, lost revenue, having to ship a package twice.
00:18:09.680 --> 00:18:16.160
When you roll up all the numbers, yeah, Brad, we're we're looking at a huge, huge cost to enterprises, and it's a hidden cost right now.
00:18:16.319 --> 00:18:19.920
CFOs don't think this way because they've never had the data to do it.
00:18:20.000 --> 00:18:31.920
Now, I will tell you, for enterprises we're working with, we begin exposing some of this data, and they can begin to see their capital spend and ROIN spend and how are these devices being used and where are we having downtime?
00:18:32.160 --> 00:18:39.200
It really creates a great dynamic for IT operations, finance to all get involved and say, how are we going to improve this?
00:18:39.359 --> 00:18:41.599
Because there's some very real cost savings on the table.
00:18:42.000 --> 00:18:44.480
Yeah, you can't can't manage it if you can't measure it.
00:18:45.279 --> 00:18:45.519
Exactly.
00:18:45.839 --> 00:18:46.160
Exactly.
00:18:47.279 --> 00:18:52.400
Um my next topic is it's it's a different, different area, but the I'm gonna call it the OEM landscapes.
00:18:52.559 --> 00:19:03.039
You mentioned the the rugged devices, the frontline workers, these devices, and I'm gonna call the the frontline spaces majority zebra or zebra, depending on what part of the world you're from.
00:19:03.359 --> 00:19:09.279
Honeywell, which is uh as we're talking now, might be becoming Brady or part of Brady.
00:19:09.680 --> 00:19:18.880
And then um, you know, there's Data Logic, Spectrolink, Samsung, and then there's a slew, probably other 14, 15 other vendors that are specific or have different niches.
00:19:19.440 --> 00:19:41.359
How do you remain agnostic or work in this landscape where you know some of these different people, Side of Honeywell has Op Intel, there's um uh Zebra has their visible, well, it was visibility IQ, I think they're renaming it, but how do you work in this landscape where you guys have a tool that does a lot more than their native tools, but you know, you gotta sort of maintain the Switzerland mindset.
00:19:41.680 --> 00:19:42.160
Yeah.
00:19:42.559 --> 00:19:43.200
It's challenging.
00:19:43.359 --> 00:19:43.920
I mean, it is.
00:19:44.000 --> 00:19:48.799
We we we certainly want to work with everyone in the industry, and so far we've been able to do that successfully.
00:19:48.960 --> 00:19:52.319
It's a it's a big problem, as I said earlier in the conversation today.
00:19:52.400 --> 00:19:57.279
And so everyone, I think, can get their slice of the pie, and there's plenty of pie out there right now.
00:19:57.440 --> 00:20:02.880
And so we have been successful working with all the OEMs, including those who have a competing product.
00:20:03.119 --> 00:20:11.359
I think at the end of the day, though, the voice of the customer is going to be what ultimately saw decides who's going to win and who's going to lose in the industry.
00:20:11.680 --> 00:20:13.519
The voice of the customer to me is very clear.
00:20:13.680 --> 00:20:15.440
It's what I heard nine years ago.
00:20:15.680 --> 00:20:18.240
I need visibility over my mobile assets.
00:20:18.400 --> 00:20:22.000
And I need that visibility regardless of what OEM I choose.
00:20:22.240 --> 00:20:28.960
And so what we see and hear very clearly is the customer saying, I want choice in what OEM I want to use.
00:20:29.200 --> 00:20:36.160
It might be Honeywell front-of-house retail and zebra in the warehouse in the DC, might be GTAC on the forklifts.
00:20:36.240 --> 00:20:46.720
I mean, they they want freedom of choice based on the technology that's best for the application that serves, but they want a platform that gives them the visibility across all those different OEMs.
00:20:46.960 --> 00:20:48.640
That's what we're bringing to the market.
00:20:48.799 --> 00:20:53.279
And the best example I can I can give to you of how this market's shifting is Honeywell.
00:20:53.519 --> 00:21:01.119
Honeywell has historically, in their operational intelligence product, it has historically been a product built to only support Honeywell devices.
00:21:01.279 --> 00:21:10.400
They've recently made the decision and they just announced um announced it at NRF back in January, but I was out at Phoenix a couple of weeks ago for their sales kickoff.
00:21:10.640 --> 00:21:23.279
They are announcing their op and making available their new agnostic operational intelligence platform, where Honeywell's operational intelligence platform now will support Honeywell and all the other major OEMs.
00:21:23.440 --> 00:21:24.960
They partnered with us to do that.
00:21:25.119 --> 00:21:26.720
I think it's a fantastic move.
00:21:26.799 --> 00:21:32.400
And I think it shows that Honeywell is listening to their customers who were saying, we want a platform that supports our choices.
00:21:32.640 --> 00:21:33.680
If it's you, great.
00:21:33.839 --> 00:21:36.240
But if we want to deploy Zebra down here, we're going to do that.
00:21:36.319 --> 00:21:39.359
And Honeywell, I think, to their wisdom has said, we get that.
00:21:39.519 --> 00:21:42.880
And so we're going to open up our platform to be more open to the industry here.
00:21:43.200 --> 00:21:44.079
Yeah, I love that.
00:21:44.720 --> 00:21:50.480
In fact, you called out that there is a different use case that every device is ideal for.
00:21:50.640 --> 00:21:52.079
There's no one device fits all.
00:21:52.559 --> 00:21:53.440
It's just not going to happen out there.
00:21:53.759 --> 00:21:55.279
And it changes, it changes in two years.
00:21:55.359 --> 00:21:57.519
You know, not every device is on the same refresh cycle.
00:21:57.599 --> 00:22:02.079
And so if my warehouse is about to go End of life and refresh two years from now.
00:22:02.160 --> 00:22:06.240
A lot's happened on technology in five years, and I need to have freedom of choice.
00:22:06.480 --> 00:22:07.680
Customers get that.
00:22:07.759 --> 00:22:11.359
And that's where the market is, and that's where we play, and we're going to continue to play.
00:22:11.440 --> 00:22:13.920
And it's it's been a successful strategy for us so far.
00:22:14.240 --> 00:22:15.359
Yeah, it's it's a good one.
00:22:15.519 --> 00:22:21.920
Um the next question I had or next topic was the the survey you had uh when I went through, let me explain the numbers right.
00:22:22.000 --> 00:22:30.400
The retail was about this year was 35%, transportation logistics 29%, manufacturing 27%, healthcare 20%, and there was a couple other in there.
00:22:30.640 --> 00:22:35.920
Do you see any meaningful difference in the issues experienced across those verticals?
00:22:36.400 --> 00:22:40.079
No, we've we've cross-tabbed this thing like crazy looking for that.
00:22:40.400 --> 00:22:41.119
Can't find it.
00:22:41.279 --> 00:22:44.720
I've done cross-tab analysis even by company size, by this, by that.
00:22:44.960 --> 00:22:48.640
It's it's kind of crazy in this data how everything trends in the same direction.
00:22:48.799 --> 00:22:58.720
The top three issues we see in the data are consistently network performance, app stability, device stability, and batteries not laughing the entire shift.
00:22:58.960 --> 00:23:03.279
It's kind of scary how those numbers don't move around a whole lot, depending on what industry you're in.
00:23:03.440 --> 00:23:08.640
So I think we're dealing with a technology problem more so than a what vertical do I work in problem.
00:23:08.799 --> 00:23:10.880
And I think the data spells that out pretty clearly.
00:23:11.359 --> 00:23:20.880
If you had to guess the correlation of battery issues against app versus network issues, would you say one is is more problematic to the battery than the others?
00:23:21.039 --> 00:23:26.720
I I know there's, you know, when your device is roaming, you end up consuming more battery, but also I've seen really poorly written apps.
00:23:26.880 --> 00:23:31.119
Do you see one versus the other that's worse, or are they both equally bad at various places?
00:23:31.519 --> 00:23:33.039
It they can both be equally bad.
00:23:33.119 --> 00:23:34.640
And they they can both be equally bad.
00:23:34.799 --> 00:23:48.240
So we probably see more application issues than network issues just because the operators are attuned to this and do a pretty good job of trying to fix their network versus a lot of there's a lot of really bad apps being written out there and um where there's a memory leak or anything else.
00:23:48.319 --> 00:23:50.799
And so opportunity for you guys there at Blue Fletch.
00:23:50.960 --> 00:23:57.759
But no, we see a lot of battery drainage, especially after an app update or an OS update, suddenly things just begin going crazy on battery life.
00:23:57.839 --> 00:24:00.000
And, you know, customers are wondering what to do.
00:24:00.160 --> 00:24:08.559
I mean, before before we got involved with our software, we had a lot of customers who their first recourse, anytime someone said they had a battery issue, was just give them a new battery.
00:24:08.799 --> 00:24:13.920
Well, that's really expensive cost-wise and horrible for the environment.
00:24:14.160 --> 00:24:20.240
And so now with our software, the first thing they can do is say, okay, there's a battery having an issue, but is the battery still healthy?
00:24:20.400 --> 00:24:24.720
And if it shows the battery is healthy, then I go to, all right, let's triage it further.
00:24:24.960 --> 00:24:28.480
What could be causing this battery to not perform like it did last week?
00:24:28.720 --> 00:24:32.319
What changes have happened, or where where was the user using the device?
00:24:32.480 --> 00:24:35.200
How do we dig deeper and figure out what the root cause is here?
00:24:35.839 --> 00:24:37.039
It's it's there somewhere.
00:24:37.119 --> 00:24:38.480
It's probably a bad application.
00:24:38.640 --> 00:24:47.599
Especially I imagine we'll see a lot more of this with uh with people vibe vibe coding in the uh the the rate they are over the next year where they're not actually sure of what they're putting onto devices.
00:24:47.680 --> 00:24:55.599
And that was that leads into the next topic I had for you, which is how is AI changing the mobility DEX landscape and device management?
00:24:55.680 --> 00:25:02.160
How do you see that changing over the last 12, 16 months and then any big things this year you see happening?
00:25:02.640 --> 00:25:05.039
12 to 16 months in AI, that's a lifetime.
00:25:05.119 --> 00:25:06.480
I'm I'm worried about last week.
00:25:06.880 --> 00:25:07.039
I know.
00:25:07.119 --> 00:25:10.880
I feel like we're about five five iterations, five iterations of quad this month, it feels like.
00:25:11.200 --> 00:25:11.519
Yeah.
00:25:11.759 --> 00:25:18.480
I I think the two biggest trends that we're seeing right now is on the device side, on the physical mobile device.
00:25:18.640 --> 00:25:22.480
There's there's no doubt we're seeing um edge processing moving into the device.
00:25:22.640 --> 00:25:24.640
We're seeing AI built into the device.
00:25:24.880 --> 00:25:26.480
We're tip of the iceberg on that.
00:25:26.640 --> 00:25:35.759
Um I certainly have sat down and had some interesting discussions on where things like um AI built into the chipset for reading barcodes, scanning packages.
00:25:35.920 --> 00:25:42.640
I mean, there's there's just some incredible thinking going on at the hardware level of how AI is gonna be built into the hardware.
00:25:42.880 --> 00:25:50.240
That's going to change a lot because before where that device had to send a lot of data up to the cloud, the cloud would process it and make sense of it.
00:25:50.400 --> 00:25:55.519
We're not gonna have more making sense of it down at the device level, and therefore the role of the cloud is gonna be different.
00:25:55.680 --> 00:25:56.640
That's a big shift.
00:25:56.799 --> 00:25:57.599
That's a big shift.
00:25:57.680 --> 00:26:07.519
Whether it's gonna be peer-to-peer communications going on within within the network, within the enterprise, and the cloud's not being talked to as much, I don't know where it's gonna wind up, but that's a big shift.
00:26:07.759 --> 00:26:13.119
The second one is in my world, we we process a lot of data every day, as you can imagine.
00:26:13.279 --> 00:26:20.400
Uh, if we're tracking for one customer, you know, tens of thousands of devices, we're looking at network performance, battery performance, applications.
00:26:20.559 --> 00:26:27.440
So we're constantly producing a lot of data, putting it up into the cloud, we're processing that data, we're looking for trends, we're looking for anomalies.
00:26:28.079 --> 00:26:30.480
AI is going to help that as well and change that as well.
00:26:30.640 --> 00:26:32.880
And it's what I call the needle in the haystack problem.
00:26:33.039 --> 00:26:35.200
And we've we've seen this a lot with customers.
00:26:35.359 --> 00:26:42.240
It's kind of fun when you can show up at a customer's door and say, Hey, by the way, did you know this is going on in your network?
00:26:42.400 --> 00:26:49.119
And it's that proverbial light bulb moment, and they look at you and go, that's why we're having the software bug we're having.
00:26:49.359 --> 00:27:11.839
And so being able to find those things that a human, you know, God bless them, they'll just struggle for the next year to ever make sense of all the trouble tickets and find that underlying hint using AI and really good software, you can find those clues and go, oh, because we're having network timing issues on Verizon's network in this part of the country, this is why we've got the software bug manifesting.
00:27:12.079 --> 00:27:24.240
It's those kind of moments that AI is only going to make more and more real that make it a lot of fun to be doing what we're doing and helps IT and operations finally figure out those big nasty problems they've never been able to figure out.
00:27:24.559 --> 00:27:27.440
Yeah, it definitely makes finding finding those needles a ton faster.
00:27:27.519 --> 00:27:29.759
So I I love it for that purpose.
00:27:29.920 --> 00:27:57.680
Um on the sort of forward-looking viewpoint, when you think of, let's go three years from now, the 2029 state of mobility report you guys put out, if I had to put my uh Calci bets or my uh uh polymarket bets on what's gonna happen, uh if you had like three things you're pretty confident we'll see in the next three years, what would they be, and then what would be some interesting outliers that you would probably have less likely for us to see in the in the mobility and mobility management landscape.
00:27:58.079 --> 00:28:05.680
I think we're still gonna be seeing network and app device stability as the top issues that that we're fighting with, but we're keeping these frontline devices up and working.
00:28:05.839 --> 00:28:11.680
It it hasn't changed in the seven years we've been doing this survey, and given the trend line we're on, I don't think it's gonna change.
00:28:11.759 --> 00:28:18.480
And so I think those are gonna continue to be the problems we need to focus on as an industry and figure out how we get better at solving those.
00:28:18.640 --> 00:28:38.160
I'm I'm hoping, and this is this is a real hope of mine in that time frame, given given the emphasis in the industry on decks and given more and more people moving into mobile decks, I'm hoping by that timeline we're gonna start asking more survey questions about hey, are you using the tool to really dig into your mobile analytics and understand what's going on?
00:28:38.400 --> 00:28:40.000
And if so, let's look at the impact.
00:28:40.079 --> 00:28:43.279
And so I hope we're we're very soon gonna start having two data sets.
00:28:43.519 --> 00:28:52.079
Those that have shifted away from the very traditional known way of supporting mobility of waiting for trouble tickets to show up versus those that are using tools to be proactive and see problems.
00:28:52.240 --> 00:29:00.240
And I'm hoping in that time frame you're talking about, we're gonna start producing a survey that also does comparisons to say, if you're doing this, these are results you get.
00:29:00.400 --> 00:29:02.000
If you're still doing this, guess what?
00:29:02.160 --> 00:29:06.319
Your number of trouble tickets are still going up, number of outages are still trending up.
00:29:06.480 --> 00:29:13.279
I think that's gonna be the tipping point in this industry where we can walk in with that kind of data and have people go, it's not just anecdotal.
00:29:13.359 --> 00:29:14.880
It's not a salesperson talking.
00:29:15.119 --> 00:29:15.839
This is real.
00:29:16.000 --> 00:29:18.160
And that's certainly something we're driving towards.
00:29:18.559 --> 00:29:19.920
That's gonna be really interesting.
00:29:20.079 --> 00:29:21.680
And then I guess some outliers.
00:29:21.759 --> 00:29:25.440
Um, any thoughts on I'm always interested in robotics.
00:29:25.519 --> 00:29:34.960
Like, where do you see that with robots becoming more of the you know human in the loop versus human just managing those types of things?
00:29:35.119 --> 00:29:40.240
Do you see that changing on the warehouse and logistics transportation space in the next three or four years?
00:29:40.640 --> 00:29:40.960
I do.
00:29:41.119 --> 00:29:50.400
And we've certainly had a lot of inquiries on our company going, hey, could we also include, you know, non-human devices in in our analytics package?
00:29:50.480 --> 00:29:51.680
And we get a lot of requests on that.
00:29:51.759 --> 00:29:54.960
We've had a lot of interesting conversations because it's the same problem.
00:29:55.119 --> 00:30:05.279
If I've got a robot doing a job and that robot's gonna be connecting to the network, that robot is running apps, where's the monitoring layer and the analytics layer and the intelligence layer on that?
00:30:05.440 --> 00:30:06.559
Hopefully it's built in.
00:30:06.640 --> 00:30:10.400
Yeah, I think we kind of forgot that layer when we grew mobility so quickly.
00:30:10.559 --> 00:30:14.240
But if it's not built in, that's certainly an open opportunity to take a look at.
00:30:14.559 --> 00:30:19.279
Yeah, I think those feedback loops definitely make the the robotics game work a lot better if you have it.
00:30:19.519 --> 00:30:21.839
Um quick, quick close here.
00:30:21.920 --> 00:30:23.680
So key key items here.
00:30:23.839 --> 00:30:31.440
Um really people should be thinking about the experience of the users and the the call, the hidden cost of the downtime.
00:30:31.599 --> 00:30:41.440
So it's there's a lot of money there between I think your 7.4 billion and 100 billion, some somewhere in there, it could be could be a lot that is being missed by folks.
00:30:41.680 --> 00:30:47.279
I think the second thing is really just being able to monitor in order to be able to manage those better.
00:30:47.359 --> 00:30:52.880
I think whether it's the the experience of the end users, your help desk costs, your device costs, drive that down.
00:30:53.039 --> 00:30:58.880
Um your point on the networking, I I just assumed like network is getting better and better, it feels like it's getting better.
00:30:58.960 --> 00:31:06.880
But as you said it, I realize that I've seen a ton of those issues you articulated in the last two years, and they feel like they keep popping up, even though we have better and better technology.
00:31:07.039 --> 00:31:08.160
So a lot out there.
00:31:08.319 --> 00:31:14.640
Um Gary, if if folks wanted to find more about B2M or to how to engage with your team, where could they go?
00:31:15.119 --> 00:31:22.400
This place is our website, B, the number two, M is in Mary, so business to mobile, b2msolutions.com.
00:31:22.559 --> 00:31:25.279
On our website, you'll find a good definition of mobile decks.
00:31:25.440 --> 00:31:30.480
You'll find the research project that we talked about here under the state of mobility tab, and you can learn more about our products.
00:31:30.559 --> 00:31:32.640
And if you've got interest, just reach out to us.
00:31:32.960 --> 00:31:33.279
Awesome.
00:31:33.440 --> 00:31:34.160
Appreciate you having it.
00:31:34.240 --> 00:31:35.359
And it is, it is a really good read.
00:31:35.440 --> 00:31:37.440
So definitely, if you get a chance, go glance at it.
00:31:37.599 --> 00:31:40.880
It's yeah, it's got a lot of dense content, I'll call it.
00:31:40.960 --> 00:31:44.559
So uh it's good to get through and definitely reach out to Gary and his team if you have any questions.
00:31:44.720 --> 00:31:46.640
Gary, thank you for hopping on with us today.
00:31:46.799 --> 00:31:47.359
Appreciate it.
00:31:47.599 --> 00:31:48.160
Thanks, Brent.
00:31:48.240 --> 00:31:49.599
It's good to see you again.
00:31:49.920 --> 00:31:52.480
Thank you for tuning in to Frontline Mobility Edge.
00:31:52.640 --> 00:31:56.240
If you enjoyed this episode, make sure to subscribe for more content every month.
00:31:56.400 --> 00:32:01.039
If you'd like to learn more about Blue Fletch, check out the link in the description or visit us at bluefletch.com.
00:32:01.200 --> 00:32:02.400
See you next time.