The Fleet Tech Stack Transformation Webinar by BeyondTrucks and Moss Adams x Bakertilly

Welcome to our webinar. Today we we have uh the pleasure to present another webinar in partnership with Moss Adams and Baker Tilly. So today's webinar is

going to be about the fleet tech stack transformation turning accounting systems and the TMS transitions into competitive advantage. Uh my name is

competitive advantage. Uh my name is Karina Vagner. I'm the head of marketing

Karina Vagner. I'm the head of marketing for Beyond Trucks and uh we're going to have this webinar getting presented by

Beyond Trucks and Mos Adams Baker Vic.

So let's start today uh with uh introducing our dear presenters uh to the webinar. So today we have with us

the webinar. So today we have with us Hans Gallon. Uh Hans is the CEO and

Hans Gallon. Uh Hans is the CEO and co-founder of Beyond Trucks. Beyond

Trucks is a modern TMS specially designed for fleets with a complex operations. So it's a AI ready AI and

operations. So it's a AI ready AI and it's a uh cloud uh system uh transportation management system and uh

we have also here Chris Mille uh director of Netswuite solutions and client success leader for Moss Adams and Baker Tilly. So Moss Adams Baker Tilly

Baker Tilly. So Moss Adams Baker Tilly is leading advisory firm in data and also uh tech strategies uh for

customers.

So with that said let's get on the topics that we have today to address the oral webinar theme. So starting off with

what is changing. So Hans, why don't you start let giving us kind of an overview about what is changing uh in the accounting and also the TMS landscape.

Thanks Carolina. Um good afternoon everyone. Um very glad to be here. Uh I

everyone. Um very glad to be here. Uh I

think I can start maybe with a um comment that I hear time and again from customers and our customers are large enterprise fleets who will turn to us to

simplify their processes but also make better decisions. And customers often

better decisions. And customers often come to us and say you know I don't want to manage more IT vendors. I have all these IT vendors and now I need to deal

with them. Um, and they're struggling

with them. Um, and they're struggling with it. I think they're fundamentally

with it. I think they're fundamentally struggling with it, which means there is a new problem out there that they're not used to dealing with. And that takes me

to to a a fundamental change that's happened over the last I would say probably across industry 20 years, but in the transportation sector is only

being um manifesting itself over the last I would say two years. um and

that's the move to the cloud. Uh maybe

you can go to the next slide briefly.

And so what what's traditionally been happening in the um transportation management system space is that most platforms TMS or uh also accounting

platforms were initially built for onremise deployment. So one software

onremise deployment. So one software license, one software instance uh per uh server that was hosted um on premise. Um

over the last few years, some of the big uh players in the TMS space have started to move those software licenses, those software instances to the cloud. Now,

most big enterprise systems today will say they have a cloud version.

However, that is still very very different from where the world has moved uh to otherwise uh in modern software design. And that's uh was initially

design. And that's uh was initially started only in the consumer space but then has really uh trickled down to the enterprise software space the B2B space

and that's moved to it's the move to what is known as the multi-tenant cloud um which essentially means that multiple

um enterprise users or enterprise customers share a common code base um

while their data uh is still segregated into separate um data silos that are independently encrypted and independently hold held.

So that that new architecture essentially uses one software instance for multiple companies

um across uh multiple uh databases and most modern systems that are out there today um like Fleio or you know the

modern ELDs or beyond trucks are architected at multi-tenant cloud systems. Can you go to the next slide please?

That is really important because what it has done it has made integrations much easier. So when you look at the left

easier. So when you look at the left side of the slide while in these traditional single instance software architectures whether they're in the cloud or on premise every integration

between two systems had to be built individually. So system let's say a TMS

individually. So system let's say a TMS system and integrating an EL system or TMS system integrating into a uh ERP system for every company you had to

build this individual integration. It's

very labor intensive. It's very

expensive uh and it's also hard to maintain. However, with multi-tenant

maintain. However, with multi-tenant architectures, it becomes much easier to integrate across two systems because the code is the shared code on on on both

sides. So essentially you can integrate

sides. So essentially you can integrate at the systems level build that integration once and streamline the process of connecting two systems with

each other. Sometimes there's still you

each other. Sometimes there's still you know some work involved in mapping data fields. So it is not always as simple as

fields. So it is not always as simple as uh you can just uh connect the two systems and they start speaking to each other but it has radically reduced the

effort it takes to connect two systems and then and that in itself has um uh opened the the the path to a new architecture across the entire tech

stack and we can go to the next slide.

So while systems in the past uh were these monolithic architectures that you know built different functionalities that talk to itself. Uh today what you

see is a tech stack that is built not out of one system provider but out of many different system providers that start talking to each other um through

API integrations um that connect these two uh or multiple multi-tenant systems very very efficiently um and very frequently at the core of

those integrations whether it's into an ELD into a fleet management system or a safety management suite stands stand two systems. The TMS on the one hand for operational workflows and

then for accounting um uh financial transactions, financial records, the the accounting system or the ERP. Most data

gets aggregated in a data warehouse nowadays but it is not one single system that runs everything. So that trend has really really started to sink in in the

transportation space. I think the first

transportation space. I think the first sign of it is is that people complain that experts start complaining about all the integrations to manage uh and all

the vendors to manage. But part of that problem is that they are still on old software that is architected in a way that every integration has to be customuilt uh into the old software

architecture. If they were on a modern

architecture. If they were on a modern in a modern architecture that would be much less effort and much more costefficient for them. So that takes us back to the very first slide in the very

first bullet and the biggest change that I have seen is is exactly that architectural change and I'd love to hear Chris's perspective on that and on what he's seen. Yeah, thank you Hans.

And I think uh you hit a lot of the main points around that and what we see here uh in our work with our clients and and doing a lot of the advisory work around

you know technology strategy and road maps and and data strategy and you know if we really talk about uh the cloud and the um the multi-tenant situation and

and you know again in my in my intro I I specifically work with Netswuite which is uh was originally net ledger uh which was created 1998 and was the original

cloud-based accounting system uh out there um and um has just expanded upon that to be more of a full-fledged ERP and that's what really people are going

towards and and what that kind of multi-tenant cloud-based uh architecture allows you to do uh from an accounting system perspective TMS perspective or

just a holistic technology stack perspective is really allow you beyond just the um the ability to integrate easier is it's it's really uh uh

hardware agnostic, it's browser agnostic, it's device agnostic. I don't

care whether you're uh using a laptop or a phone or a watch or a tablet. As long

as you have a connection to the internet, you have access to your information, right? And this is really

information, right? And this is really what this is about, right? It's really

about the ability for you to be able to uh aggregate, consolidate, and easily consume your information. And what is information? Information is data. So

information? Information is data. So

Hans alluded to this in one of the slides around data warehousing and being able to have interconnected systems. And that's where the landscape is going towards for um just business systems in

general, right? Uh so whether we're

general, right? Uh so whether we're talking about accounting, TMS, a uh a warehouse management system, um you name it, uh the key is is to have all of our

data being able to interact so we're ultimately having a single source of truth and that uh we can what I like to call democratize our information throughout the organization, right?

We're not in these silos. who are not in these um uh compartmentalized groups to where hey, if I need a piece of information from my fleet manager, I don't have to ask them specifically for

a piece of information. I can already see it as long as I've been granted access to that information in my system.

it's in real time and and things that affect my job, say on the accounting side, let's just say I have uh some invoices to send out to customers based on some activities that happen uh within

my uh fleet. Um I'm going to be able to see that in real time based on that activity. So the inputs that those uh

activity. So the inputs that those uh users are giving on that side of the business are automatically going to be known to me and what I and giving me

guidance on what I need to do on my side on the accounting side of things, right?

Um and so that's really what we're talking about there is being able to have a seamless integrated automated system. uh we'll talk about some of the

system. uh we'll talk about some of the other uh technologies a little bit later in the presentation when we talk about uh AI and some of your other data strategies around some of that

information. We note on things around AI

information. We note on things around AI readiness uh as well and and really what we're talking about is is making it easier for me to consume the information

that's presented to me so I can make decisions faster. So,

decisions faster. So, I think to that point, it's I I find it fascinating. Before this call, I

fascinating. Before this call, I literally got off um a conversation with the uh COO of a midsized animal feed

distributor uh based out of rural Ohio and their team today has a 15 people data science team.

Yes, it is. You would think that an agricultural manufacturer distributor, you know, in in rural Ohio is not it there. But I think we have seen even the

there. But I think we have seen even the most traditional businesses today start moving to um architectures and a level

of sophistication that uh is mindboggling. No, but we also have the

mindboggling. No, but we also have the other side of that coin where we sometimes have customers who are still on uh you know printing things on green

bars and using paper forms and working on black and green screens. So um I think the the the world is still

somewhat um uh bifurcated polarized in terms of the choices that people make but it's mindboggling. Well, your point is well taken and again we have an entire team here in our firm that that's

all that they do is work with people on what does that data strategy need to look like. You know, where are you

look like. You know, where are you coming from? Uh what is your internal

coming from? Uh what is your internal ability to consume the data and be able to understand what it's telling you, right? And that's really kind of around

right? And that's really kind of around data strategy and things like data governance and being able to um put uh solid strategies in place that are going

to not just be kind of pie in the sky um you know piece of information. Oh that's

nice. But is it more any more than anecdotal, right? We need to be able to

anecdotal, right? We need to be able to actually present the information in a way that is meaningful at whatever level of sophistication your organization has.

Right? So you may have like you're describing, you know, 15 data analysts and that's their world. That's where

they live. But you're going to have just as many or if not more organizations that really don't even know where to start. And that's really where uh we

start. And that's really where uh we help a lot of our clients is identifying what that roadmap needs to look like. So

and and it's it's so so important, you know, time and again I think when we see people on old technology, people are scared to make a transition. Mhm. And

you know is it a painful transition? It

is a painful transition but it is probably the most transformational journey some of these companies can go through and sometimes customers come to us and says can you implement in 3

months and it's like you've been on this old system for 30 years. is that you would if we implement in 3 months, you

would miss out on the great opportunity to do a down to the studs renovation and make sure that your foundation is sound and you're not just, you know,

repainting your walls. Uh so it is really really I think there's so much value and opportunity in these changes that people often um ignore.

I think I'm more scared about transition than any Absolutely. And I guess this actually

Absolutely. And I guess this actually brings us to like moving forward into the presentation. So the code decoding

the presentation. So the code decoding the warning signs, Chris. Yeah. I think

Hans holding you back and then what do you do, right? Yeah. Yeah. So I think Hans was just talking about this, right?

I mean it's it's when you've been on a system for 30 years, you know, whether it's great plain suns setting or you've got multiple disperate systems and your

uh you know your IT team has expanded to an unmanageable level because you're just trying to manage your systems. You're just trying to manage your data.

Um you're using a lot of workarounds um outside of the system, right? you're

using multiple spreadsheets and pivot tables that and links to different things that continually break um and there you're spending you have to hire somebody just to maintain the links in

your data, right? Um and then of course that's fraught with errors. It's fraught

with um multiplication of effort. Um uh

you know just uh simple things like fat fingering something into the wrong field on a on a data spreadsheet that's going to skew your entire model. you know,

those are all the things that we see constantly. These are the fears that

constantly. These are the fears that people uh have. But yeah, you hit it on the head with kind of that that uh that tribal knowledge that comes from using an old system and the fear from going

moving forward into something that's a bit more modern. And uh those are again those are things that we work with folks a lot on is the is the strategy around that. you know, just the change

that. you know, just the change management is is what one of the biggest things is around when you're going from a legacy system into a new system. But

anytime if we're really talking about the warning signs, anytime that you are um just a simple thing, I'll just take it from a simple accounting perspective.

If it takes you more than a handful of days to do a month-end close, you need to consider looking at a new system, right? Um, and and that's just a basic

right? Um, and and that's just a basic one, right? I mean, we're not even

one, right? I mean, we're not even talking about making concrete, meaningful, move the needle decisions about the business. We're just trying to get a basic financial statement, right?

So, um, you know, that that would be a major warning sign. you know, if it takes you more than a few days to close your business. If you're not if you

your business. If you're not if you let's just say you uh have multiple companies that you're running on multiple systems, but they need to all consolidate into one aggregated

financial, right? Uh and it takes you

financial, right? Uh and it takes you weeks to be able to consolidate and make sure you reconcile that information.

Your system should be able to do that for you, right? That should all be automated. You should not have to spend

automated. You should not have to spend any time doing that at all. Right? Um,

and so those are some of the warning signs that you can look for just that should just be apparent day in and month day out, month in and month out and are just very basic. But going into some of

the other things that we talk about here around um are you not necessarily even using your systems to actually understand your data? Are you using all these workarounds? Are you using

these workarounds? Are you using multiple spreadsheets? If you're doing

multiple spreadsheets? If you're doing all of that, you shouldn't be, right?

these modern modern systems should be able to do all of that work for you through automation through um some of the other um machine learning and and an AI functionality that a lot of the

systems have in place. Really again we should not be having to manage the data we should just be able to consume it and make the decisions from it. So Hans be interested to hear your thoughts on that

as well.

Yeah, one of the things we see in in um large fleets frequently is the size of the fleet. So the kind of the productive

the fleet. So the kind of the productive or in in a for higher fleet the revenue generating um staff uh in relation to

how many back office people are uh on the team. Uh and we and this is a this

the team. Uh and we and this is a this is a ratio and kind of an experience-based ratio uh that once you have

um more than one back office employee per five drivers um you probably will um

have opportunities to to streamline in the in in in your fleet. So we have we've I have seen fleets with two back office two back office employees per

driver which is mindboggling and and um I think the the today the industry average is one to one to four in a large

fleet um but we we have many of the customers who are using beyond trucks actually on one to one to five so very efficient in their back office and I think that ratio can be a good guiding

post on seeing whether whe there are opportunities or not. Um the other thing that we've seen is on this topic of um tribal knowledge is is kind of

interesting. I think modern AI offers a

interesting. I think modern AI offers a lot of opportunities to extract tribal knowledge through some of the machine learning opportunities

and um learn not only kind of replace not replacing the human but learn from the human uh in the in the operations

and codify some of that um experience and wisdom and tribal knowledge and then built it back into new operating processes. So there's actually some

processes. So there's actually some really great tools that can help that transition if um an an employee a tenure employee is about to retire and everyone

worries about that retirement process.

So there's some really great tools that we've started to use in the dispatch space uh that can be very very valuable.

Sure. And I and I would uh echo kind of your comments around that kind of uh back office employee to driver ratio as well. I mean again just from a holistic

well. I mean again just from a holistic uh technology stack perspective. I mean

you could apply that same logic to a lot of other departments as well. I mean

just think about the interaction between your procurement your procurement group and your accounts payable group right.

Um again that should be a seamless communication between those two groups.

You shouldn't have to have extra folks in a back office role to make sure that things reconcile between those two groups. Right? It should be a connected

groups. Right? It should be a connected system to where uh especially if you're trying to maintain things around separation of duties which is always a huge uh thing when you have um you know

multiple departments working in the same system. You have folks coming in and and

system. You have folks coming in and and and being able to uh do their jobs in a seamless way and not be hampered because they just don't have access to the information. Therefore, we have to hire

information. Therefore, we have to hire somebody in the back office to consolidate the information to present it to the next decision maker. Right?

So, and I think the other topic that you brought up is multiple entities. We see

um acquisitions or having multiple entities often times one of those break points where people switch out of a legacy system into a new transportation

management system. And and I think it

management system. And and I think it came with that came again with this idea that previously having one system that handles accounting and TMS two in one

was really appealing for companies that were built in the 80s 90s maybe early 2000s. But with consolidation in the

2000s. But with consolidation in the industry becoming more and more common you know M&A is becoming more and more common that large players by other smaller players then suddenly the

complexity of how handling multiple entities becoming such that having five versions of that accounting and TMS system just doesn't make any sense

anymore and that that is becoming a a really an important kind of warning sign or a trigger for for people to move on.

using that time and again I would agree and moving forward and again related to when systems holding

can you elaborate a little bit more about legacy systems structure lack of integrations and limited AI capabilities? Yeah, and I think that

capabilities? Yeah, and I think that this just echoes a lot of what we've been talking about up to this point, right? Um, you know, your legacy system

right? Um, you know, your legacy system structure, as Hans called out in some of the previous slides, is going to be very much siloed, right? So, you're going to have certain pieces of your system that only do certain things and they don't

really communicate without a very customized integration between these different systems. He just pointed out again the um situation we see this happen quite frequently is when you're

combining multiple organizations under one roof. um and they're all coming to

one roof. um and they're all coming to this perspective from a different system, right? And if you're using these

system, right? And if you're using these systems that are, you know, 30 years old, um it's going to be an almost impossibility to connect those systems in a meaningful way, right? At least

it's not uh it's not going to be uh fiscally responsible to do it anyway, right? So um so that's I mean from a

right? So um so that's I mean from a legacy system structure that's what we're normally going to see is going to see very siloed um systems that do very specific things

right uh that have really a limited or almost no capability to communicate uh with any new systems or even amongst themselves. Um so that that leads right

themselves. Um so that that leads right into the second bullet point here is the lack of integration capability. So again

uh with uh what we see mo works greatest especially from an ERP perspective is what we would refer to as a open API infrastructure. Right? So what that

infrastructure. Right? So what that really means for a modern system is API is that application interface uh capability. So uh what we would

capability. So uh what we would recommend is that your core systems are have the ability to connect with anything right as long as that system

can be connected to. And that's the main question I always ask to clients or prospective clients that I'm talking to is okay, you're telling me you're using

XYZ system for whatever process, right?

Um, and they always ask me, well, can that be integrated to Netswuite? And I

say, well, yes, as long as that system can be integrated to, but when we go back to the previous bullet and they're using some of these legacy system structures, it they just don't make it a

possibility. So, the problem is not on

possibility. So, the problem is not on our end, right? is the problem is on the on the legacy system end, right? And

then you know the last bullet here is around limited AI capabilities. That is

the major buzzword these days is what does AI actually even mean to people?

And but really again um the the greatest strength that we're seeing in modern systems from an AI standpoint is again the ability to present meaningful

information to me faster. Right? So,

we're leveraging AI to consume the data in a faster way, not to make the decisions, but to maybe make recommendations around what the data is

telling us, so that maybe the AI will be able to call out something that we didn't initially see, right? Maybe a

trend, maybe a forecast that maybe um, you know, go against what we initially thought about was happening with our business, right? Um, again, if you're

business, right? Um, again, if you're not experiencing that with your current systems, then again, that is a warning sign, right? Uh, because that's

sign, right? Uh, because that's something that's available to you and you should be leveraging, especially if you're looking to scale and grow towards the future. So, Hans, what are your what

the future. So, Hans, what are your what are your additional thoughts there?

Yeah, I think what we've seen on your point on what is fiscally responsible, we've seen actually a lot of opportunity in looking at the tech stack for our

customers looking at the tax stack more holistically and moving away from the traditional con conception of okay this is what a TMS does or this is what's an

ERP does but actually assess what is the most costefficient way to um assemble a couple of these capabilities. So one of the things that

capabilities. So one of the things that we see is that in fleets frequently anything that happens from the moment a load gets assigned to a driver till the

data comes back um um into the system for payroll calculations or billing cap bill calculations that kind of that middle piece um which we call delivery

execution is literally the driver delivering the commodities to the customers. Any data that gets collected

customers. Any data that gets collected in that piece traditionally has been has been uh collected with a multiple bolt-on solutions. There may be one for

bolt-on solutions. There may be one for driver workflows. There may be one for

driver workflows. There may be one for imaging. There's one for image indexing.

imaging. There's one for image indexing.

There's one for invoice generation. And

in that space in the old architecture that was all kind of built into that onremise system. But in today's

onremise system. But in today's semicloud, semi onremise world, these integrations become super super ownorous. So often when we look at the

ownorous. So often when we look at the spending that our customers make on these workflow pieces in the delivery uh segment, that could make up one/ird or

half of a modern transportation management systems annual fee. So, and

and again, not only is it the systems that you need or the bolt-on solutions you need to buy, but it's the integration service provider who needs to stitch them all together because they're architected in a way that is

just not modern. And so, I think there is because people have stayed on legacy system for a long time, there is this

almost cancerous growth on top of them of additional things. And unfortunately

um there's a I call it a little cottage industry of integration service provider who make money off the failures of the old systems to function in a modern way right it actually perpetuate perpetuates

the problem and um critical thinking is really important on the customer side that what we found and and having advisers like yourself

you know um punch holes into establish um um operating practice is super super critical Oh, I I would agree. I mean,

we're always going to approach things from a leading practice perspective and make you tell us why that won't work for you, right? Um, you know, if we have

you, right? Um, you know, if we have hundreds of people that doing this that that do what you do, right? Um, then why won't it work for you, right? Um and

then the other piece of this I is also as you touch on just what is the the pain uh level of pain of not doing something

about this causing right so whether that be financial pain um the fact that I can't make decisions as quickly as I need to make them which can lead to financial pain um and that's really what

drives ultimately a lot of people to automating and connecting you know in more mo in a more modern way right is the pain becomes greater than maybe uh

the initial investment that they look at because that's what a lot of people see.

they say, "Okay, yeah, it's going to cost me x amount to make this transition, but they're not looking beyond." That's why, you know, the

beyond." That's why, you know, the critical thinking uh portion that you brought up is super important because, you know, that's something we work with our clients a lot is what is should be your return on investment from this,

right? And what is that time frame?

right? And what is that time frame?

What's the break even point, right, with uh making the investment in your technology, right? And those are all

technology, right? And those are all questions that should be answered before you even go down the path of of making that decision. Right. So yeah, I think

that decision. Right. So yeah, I think that these ROI calculations is a really interesting one and I'm curious to have your thoughts on that too. Chris is I think on the AI front that's

particularly tricky. Um I think there's

particularly tricky. Um I think there's a lot of uh promises and hype that typically comes today with a lot of the AI applications.

But I think at least on our end what we see often is once once they get implemented and you realize that the the data is not available or they can't be

properly built into a workflow um the kind of the ROI gets eroded. uh we have instances where people buy AI bolt-on solutions where the integration cost

essentially just kind of eliminates any type of ROI because because they are not their main system of record is not multi-tenant

a multi-tenant system. So here's what you see on the ability. Well, I mean, when we're working with ROI, we're trying to justify recommendation, right?

Really is what it comes down to. Is if

we're trying to get people out of the old way of thinking and, you know, hey, this, you know, the level of effort that we're talking about here is is too great, right? It's too much for me to

great, right? It's too much for me to take on. The change management is going

take on. The change management is going to be too much. But as you start going through and this something that we'll touch on on the next slide is kind of how we go through the phases of helping

people through this process is really um is really about that current state assessment as we see here and defining what those business process requirements

are. And as you start going through that

are. And as you start going through that and as you start actually showing um the users okay so right now you're doing uh you're handling this process in

this way and it has this many steps and this many people are involved and it takes this much time right it's very easy to calculate an ROI when we say okay we're going to automate that entire

process from A to Z right and so not not only do you not going back to kind of the back office ratio that we're talking about before not only are you not going to have to have five people doing this.

You might not even have to have one person doing this process anymore, right? And those things, we see that all

right? And those things, we see that all the time is we're just going through just a basic demonstration of some of the automation tools that are available.

Let's just see the light bulb start going on, right? Saying, "Oh, wait. You

mean I don't have to spend 20 hours a week reconciling this piece of data with that piece of data anymore?" Right? Um,

and that's I think it's pretty easy to start defining the ROI at that point because now and we're not necessarily looking to to take people's jobs away.

What we're really trying to do is allow people to make a more meaningful contribution to the organization, right?

Why have people that have are really smart people just do busy work all the time, right? Why allow them to innovate

time, right? Why allow them to innovate and come up with new ideas and uh, you know, you never know where a great idea is going to come from, right? You know,

I have uh a lot of people that work on my personal team here at at at Baker Tilly Moss Adams and and uh you know, I tell them all the time, I'm not going to be the one with all the good ideas. So,

I'm relying on them to come up with them, but I can't saddle them with a bunch of busy work or that's all they're going to be concerned about, right? Is

that so in order for me to enable and harness the knowledge that I have on my team, I have to make their lives easier.

And part of that is going to be, you know, this this um moving into getting into more modern systems. And that's really, you know, if we talk about the

step-by-step approach here to really looking at u making a decision around what direction we go, you really have to do that current state assessment. Um

understanding where you're coming from, what the limitations are. And I always frame this in a question when I first start having a conversation with someone about their services. In a perfect world, what would this look like to you?

Right? If you could make all the choices and there was no um financial limitations and no resource limitations, what would this look like? And so you just and when I'm asking that question, I'm just trying to get a perspective,

right? Is well, it would be really great

right? Is well, it would be really great if we could, you know, uh do our month end close by the end by by the start of the next month. Okay. Well, I know where they're coming from then and I know that

we can do a lot better than that, right?

So, that's why you want to always do that current state assessment and then, you know, obviously you move into those uh requirements definitions and um you know, Hans, I'm sure you guys have a very similar process when you're

starting to engage with clients on a new project. So, uh interested to hear, you

project. So, uh interested to hear, you know, kind of what you you're doing there, especially when you move into that current state assessment and the future requirements definitions. Yeah,

and we have we have uh different approaches depending on the horizon of the customer. Um, more often than not, I

the customer. Um, more often than not, I think one of my favorite uh questions is if you go 10 years out,

so to 2035 and um you think you just lost your biggest customer to a competitor, what

capabilities did your competitor have that you didn't? Mhm. And then in turn, what do you need to do today to to

develop towards those capabilities? And

I I think that is a very um kind of future-based approach, a very pragmatic approach to have people put their economic thinking cap on and say, "Hey,

you know, our, you know, competitor was 15 or 20 or 30% more costefficient because XYZ and they could do that because ABC." So for us to get into that

because ABC." So for us to get into that direction we need to take these steps.

So it is it is an um a visioning exercise but it's very very pragmatic and we have seen that work um if you have future focused customers really

really well in backing into a new systems architecture and a new tech stack uh and the capabilities not only that they want to have with technology

but the capabilities that they need to build as an organization uh and in their teams and who to hire and what how to hire. So it's a it's a very holistic

hire. So it's a it's a very holistic approach that we see work with um uh customers who are very future focused but it could also be simply a you know

zerobased approach of like to similar to what you just described Chris is like um you know if you didn't have any technology today how would you build your tech stack uh what capabilities do

you want to have today? Um so it's uh it depends a little bit on the customer but we find both approaches um valuable. I

think the most important thing is zerobased. You don't want to just build

zerobased. You don't want to just build on top of a dysfunctional system and that already fails you and you're just putting band-aids on top of it because

with AI and in in at the horizon I think um it is existential that people do complete bigger renovation projects than

just putting lipstick on a pig, right?

And and that's why some we will we will very often before we even start talking about a technological tool or set of tools, we'll just go through a business

process assessment. Right? Here's what

process assessment. Right? Here's what

has to happen. Here's how you maintain your competitive advantage against your competitors. What absolutely is a

competitors. What absolutely is a must-have in your systems? Right? You

know, there's always going to be a handful of nice to haves. You know, we can help prioritize what that looks like, but what are the absolute musthaves? And then even kind of going

musthaves? And then even kind of going back to your comment around kind of that zero basis, we always also like to leverage what they really like about their current systems, right? You know,

what what are things that you know you actually do like, right? Um because

we're not necessarily going to stay with that, but at least we can do something that's relatively similar, right? Um but

it's also going to allow you a lot more capability. But um again it's it's all

capability. But um again it's it's all about um what's causing you pain versus what's c what is your definition of success right so when we start going

through this uh and and and that what is what really leads us into um helping folks with that vendor identification right identifying the capabilities based on what's causing you

pain today how do you define success right um and um what are the tools that are going to allow you to achieve achieve those things, right? And so

that's one thing that uh we do quite frequently is work with clients on that on that system selection process, right?

Uh or tools essentially is walk through through that path with them and say, "Okay, again, we got to def we got to assess your current state, define those requirements, and then who are going to

be the best um um suitors for uh achieving whatever that definition of success looks like." So that's that's how really how we go about it.

Yeah. I think the the the in that vendor identification process, one of the things that we also found interesting is that I think there are business model

differences between traditional software and modern software that um prohibit some of the older vendors to to

um change or they make them very very reluctant to actually change because it's so costly for them to to move away into a new architecture. Um, and one of

the things that we sometimes, you know, as a newer vendor, um, encou encourage our c potential new customers to do is that, you know, when you work with a an

accounting system or a TMS system which are mission critical for your business.

Um, and if you want to take into consideration newer players, you may need more than a two or 3 months just kind of competitive bidding process. You

actually do want to get to know these different players a little deeper. Um,

you know, it's easy to choose between an Oracle and SAP because we all know they're trustworthy organizations, but right, you know, in some segments of the

market, you know, the old systems may not have the wherewithal of an Oracle or SAP to innovate and improve and change and they may actually be um no longer

around in 10 or 15 years if they don't make very very deep changes to their organization. So considering new players

organization. So considering new players and building an organizational process to um embrace new players is actually not that easy especially if it's mission

critical systems where you know we all so often we hear is like no one has ever been fired for using IBM. I think that's what people always that may not get you to where you need

to be in in in a future context. So

that's one of the interesting parts.

Yeah. So exactly. Yeah. on this context.

Uh Chris starting with you uh to find the right suit uh suitable systems or tools. What are the features that

tools. What are the features that matters in a modern accounting system and then hs with you in a modern TMS?

Yeah. And it's a lot of stuff that we've been talking about. I would say first and foremost is interconnectivity, right? Um and uh again I will say this

right? Um and uh again I will say this I'm sound like a broken record but all of this is about data right so you have to be able to aggregate consolidate and

consume your data quickly in a meaningful way you know when we're talking about um the transportation logistics industry obviously it would be

very helpful to have a fleet ccentric GL so we can process our AP and AR in in the most meaningful way possible. That's

one thing we work with clients a lot on is and this is an opportunity when you're going from a legacy system to a new system is the restructuring of your GL, right? Is is there an opportunity

GL, right? Is is there an opportunity there? Uh again, kind of breaking it

there? Uh again, kind of breaking it down to the foundation as we talked about before and really saying, hey, is there a leading practice uh GL that we want to implement moving forward? How do

we map our old accounts to our new accounts? you know how do we do that

accounts? you know how do we do that data migration in the right way right um but I think that's definitely going to be a mustave and this is going to be true of any kind of industry uh centric

implementation of a of an accounting system or ERP is having a GL that's structured and makes sense and not just your GL but the other financial segmentation right do we allow how do we

allow the user or the consumer of the information to be able to segment their financial data uh in a meaningful way, right? Uh do we have the proper segments

right? Uh do we have the proper segments set up? Um do we can we go beyond kind

set up? Um do we can we go beyond kind of the standard uh okay, we've got our company, we've got our expense departments, we've got our profit centers, right? Can we go beyond that?

centers, right? Can we go beyond that?

What other things from a financial analysis standpoint do we want to be able to segment out and how easy is this for for us to do that? Uh one of the things that we see is that we don't want

to do that in the general ledger. We're

moving away from things that require us to create these gigantic account strings that represent all the segmentation. So

then you have this general ledger that's 5,000 accounts long. No, most of our implementations are two to 300 accounts max, right? So we want to have system

max, right? So we want to have system that allows us to have a very natural chart of accounts but be able to segment our data in other ways, right? Uh be

able to do consolidations and and uh and the automation around that if we had multiple company situation. But that all leads to the real- time financial visibility, right? Um how automated can

visibility, right? Um how automated can the system be that allows us to consume the data and then we have everything tied together from inventory,

procurement, payroll that translates all into the reporting. I know many many times when I'm starting a conversation with folks around this subject, it's

it's we really start at the end and work backwards. Show me your current

backwards. Show me your current reporting. what are you using today and

reporting. what are you using today and how uh do we get that information?

Right? And then what I'm going to show them is okay, here's what it could look like for you and let me just show you how easily it is to drill back into the

um the the basic transaction, right? So,

if I'm ever doing any investigation, I'm trying to understand what happened during a current uh a current uh given period financially, it's just just a few clicks and I can just click right

through from the output of what I'm looking at and I have a question about something. Everything's connected. So I

something. Everything's connected. So I

can go right back and it doesn't matter whether it's an inventory based transaction, a payrollbased transaction, uh an AP transaction, I have the same paths that I can go down and

everything's interconnected so that um you know when I'm seeing something on a report that may not make sense to me at its face, I can easily drill back in and say, "Oh, now it makes sense to me why

that happened or hey, there was a mistake here, right? um this is something that I can quickly rectify and then make my uh my reporting uh meaningful to me. So Hans, what are you

what are you seeing there from a TMS perspective? Well, I think there's some

perspective? Well, I think there's some really interesting analogies and uh some some thoughts that you sparked in explaining um what you see on the accounting side.

So um I think you know other than the the topics that we've mentioned multi-tenency integrations extensibility I think one of the interesting things

that we have seen is how data makes its way into the system is changing whereas in the past everything was about

manually uh recording data into a system in an operating system like beyond trucks or a modern transportation management system um a lot of data is created because people actually run

their business and beyond trucks. So

it's happened it is generated as they complete operational processes. So

that's a big change that we see um that of course you know removes manual data entry but what's more powerful is that

suddenly you run your your business in a new technology that can streamline automate improve uh a lot of your processes and can also inject or surface

data to you in in the course of the operations that can help you make adjustments in this in in in in the moment. Uh that's particularly valuable

moment. Uh that's particularly valuable for like fast-paced tasks like dispatching for instance where you you you are it's almost like I always compare it to, you know, you you're in

that uh shopping cart in your Amazon account and you just realize you have a $600 purchase in there and suddenly Amazon says, "Hey, spread this over 12

payments." So it's at that at that

payments." So it's at that at that critical critical decision point where suddenly injecting options, injecting recommendations or sometimes just injecting information can actually make

a real difference in what what decision you make. So that we see that as a big

you make. So that we see that as a big uh important capability is to allow the user to run their business in in in a new operating system rather than just

run their business in real life and then hire someone to key in data. Yeah. Yeah,

I think the second thing that you highlighted which is actually fascinating um when you describe the kind of a modern chart of accounts how it becomes

more reductive and that is fewer um uh fewer accounts uh but then still through the analytical capabilities that uh potentially AI gives right surfacing

more information but also just an analytical database gives you that you're spending less time on categorizing information ahead of time

but leverage um you know natural language processing for instance for um helping you categorize u data or structure data that previously was uh

could only be structured through a lot of manual effort. So there's a lot of opportunities uh that we see uh in how

I think the the modern systems enable the operator um and collect data along the way and help able to sort of process this information rather than just being

a system. Yeah, I couldn't agree more. I

a system. Yeah, I couldn't agree more. I

mean what we would normally see is as we are performing tasks that's what's having the financial impact, right? And

so by the end of a given period, that's what allows us to be able to do a month end close in just a handful of dates because we're not having to do these massive reconciliations

around the actual process versus the data that was keyed in, right? It's

actually happening as it's happening, which lends to all that real-time uh visibility that we've been talking about. And then uh something that you

about. And then uh something that you you noted on too is leveraging newer AI technologies to be able to um to um give

insight as to where something should be categorized, right? Um and we see that a

categorized, right? Um and we see that a lot in what we call predictive analytics, right? is, you know, what we

analytics, right? is, you know, what we may have thought was happening or should be happening with our um, you know, whether it's our financial information or sales or whatever we're talking

about, um, may not actually be appropriate, right? So, uh, we're going

appropriate, right? So, uh, we're going to leverage some of the AI tools out there to give us some of that guidance and and point out where we may have variances and what we had maybe

forecasted around a piece of financial information and what's actually happening uh, and how that should affect our forecast. Right. So, yep. Yeah, we

our forecast. Right. So, yep. Yeah, we

have one great example on that. Um, so

we have a customer that had 400 drivers, very specialized fleet and I always love they I always loved their Friday routine in the accounts receivable and accounts

payable department. um where they

payable department. um where they essentially at 10 to noon they went through the process of rating which means the system would apply pay rates

to the activities that were completed uh during the week prior and the accounts receivable and accounts payable ladies would literally click a button and get rate and then they went on a three-hour

lunch break because the system computationally took so long to do that and you know you know let alone that there was probably an exception cue that

had to be sent back to the dispatch team of couple hundred items every week that then didn't make it into this pay cycle or into this uh billing cycle. And so

what we've seen with our technology is as literally activities get completed loads can get rated or activities can

get rated real time. Exceptions can be managed real time and by the time it comes to the lunch break unfortunately the Friday lunch break has now been

reduced to an hour and um the team is much more efficient. Yeah. Yeah. We're

not We're not You know, everybody loves a three-hour lunch break, but I'm sure that the business would prefer an hour, right? Not exactly. Yeah.

right? Not exactly. Yeah.

Wonderful, Carolina. Wonderful. Uh that brings us

Carolina. Wonderful. Uh that brings us to the Q&A uh part of uh of of the

session. So uh for the ones that have

session. So uh for the ones that have joined like after we have started so uh you can post uh your questions on the in

the chat or in the Q&A uh button that you have on the top of the screen. Uh

I'm also getting questions from other uh media or other channels here and I'm going to start I mean since I don't see any um posted on the chat I'm going to

start with one that I got from uh another uh channel. So maybe this one going and I guess this goes to Carz uh

to begin with the with the the explanation. So what is a realistic

explanation. So what is a realistic timeline for transitioning from a system like for example great planes to another

like ERP or the TMS stack and how should the should we sequence the implementation ERP first TMS first simultaneously?

what what would be your your recommendation?

Yeah. So I think it just uh I think the short answer is it depends right um so we see all forms and flavors of what happens here. I mean it depends on the

happens here. I mean it depends on the complexity of the organization and really as we mentioned before where are you coming from right if you're a very forward thinking technology organization

it may be a little bit easier in some respects to adopt new technology if you're kind of stuck in the old ways of doing things. uh you're going to have a

doing things. uh you're going to have a lot of change management which is almost going to be as important as the technology change right so um you know I would say a realistic timeline that we

would normally give our clients is in the four to six month time range uh of a full adoption of a new ERP system and that's really going to start off and include with some of the things we've

talked about already is really what we call a business process requirements session right and or host host of sessions. Um regularly our team will

sessions. Um regularly our team will come on site uh understand have interviews with your key process owners.

Um if you um have a a a warehouse that you're managing, we want to understand what the movement of that warehouse actually looks like. you know, where are

we going to need uh even hardware technology that's um you know, RFbased verse RFID verse um verse tablets verse,

you know, uh what's what's going to be the ruggedness requirement of of your barcode scanners, you know, all those different types of things, right? um

that we're going to want to understand and then we can base those recommendations and then through that process and that can take a series of

weeks to go through that um um and and then it comes down to um it really comes down to uh the go forward plan from

there right and then the go forward plan requires several things or it requires okay what's the recommendation from a licensing standpoint so if you're purchasing uh you know an Oraclebased

product, right? You're going to need to

product, right? You're going to need to make sure you're purchasing the proper modules and the proper types of licensing for your users. And that's all comes out of, you know, our our business

process assessment, right? Who's going

to be needing access to what pieces of functionality and then that goes into, okay, that's going to give us guidance into what actually needs to be configured in the system. What need what

do we need to do targeted training for versus more of a holistic training, you know? So it's going to give us guidance

know? So it's going to give us guidance through the whole process, but I would say just as a short answer, you're looking at anywhere from four to six months process um reasonably uh

depending upon the complexity of your organization as well as where you're coming from uh from kind of a technology savviness standpoint. So perfect. Thank

savviness standpoint. So perfect. Thank

you so much for that. Anything you'd

like to add, Hans? No, I would say TMS implementations, especially if the fleet is larger, would take six months at the very least. Um, sometimes can take up to

very least. Um, sometimes can take up to 12 months depending on the number of integrations that need to be considered.

Um, and I would confirm or double click on everything that Chris said in terms of making sure requirements are properly documented and researched. of um it's a

transformation that you shouldn't embrace as a transformation that makes your business better. It's like you know going on to going to a I don't know detox

treatment. You don't want to cut cut

treatment. You don't want to cut cut short on the orange juice or whatever spinach juice that you're drinking because it makes you actually better even if you don't like the taste of it.

Absolutely. And I guess we have time for one more question. Uh Hans that will go to you. Can you elaborate on what AI

to you. Can you elaborate on what AI readiness means practically for fleet operations? What specific AI

operations? What specific AI capabilities should be looking should we be looking for in new systems and how do we ensure our investment will adapt to

the future technological advances.

Yeah, my recommendation was would be to first of all um don't be overly focused on the ability to build um features

today or offer features. methods really

is considering how a system is built to facilitate exhaustive data collection and then how that system can communicate

and how fast that system can communicate data to a data warehouse or other applications and then thirdly if there were any AI features how these AI

features can be embedded in the actual system workflow so it's not really about um kind of the the sparkles of the system, but is really about is this

system capable of facilitating what work what work means in a fleet of the future or in an operation of the future and how

um advanced decision making advanced analytics can improve um uh decisions uh in the in in a in a process. So it is it

is more abstract thinking. It is more architectural. It's more foundational.

architectural. It's more foundational.

Uh but it is absolutely critical for anyone to get productivity gains. Uh my

favorite example of that is the change uh that um um the textile industry went through in uh mostly in the United

Kingdom when they cut over from u coal power or steam engines to electricity.

The productivity gain didn't come from a cost difference in the cost of and coal versus electricity. It actually came

versus electricity. It actually came from the restructuring of the manufacturing or the the the the textile

plants or the the the shop floors because suddenly so much space was opened up and all processes and workflows could be restructured. So the

benefit of that technology change often times comes through the more the deeper changes or adjacent changes complimentary changes that companies can make rather than just kind of the the

the off the surface benefit of that technology. So one of the things that I

technology. So one of the things that I encourage everyone to think a little deeper about.

Absolutely. Thank you very much. Chris,

do you like to add anything to this? No,

I think uh Hans hit it succinctly there.

I mean, a lot of the um um uh ancillary benefits to making these technology changes might not even be self-evident right away, right? Uh but these are the kind of things that you know we can

certainly uh work with folks on and help them realize uh you know one thing that you know we see quite often that we work with folks on is is you know hey you uh

haven't really been able to capture your uh maybe your research and development uh costs and and then what those expenses are in a proper way. So now you can't take advantage of those R&D tax

credits, right? Well, all of a sudden

credits, right? Well, all of a sudden your new system allows you to do that and so now you can actually have that return that can maybe help pay for that

new system. So um so anyway, that's just

new system. So um so anyway, that's just an an anecdotal example of some things we see there. So absolutely, thank you very much. So we actually have passed

very much. So we actually have passed the top of the hour. Uh but uh I guess it was a very interesting explanation and good conversation I guess uh with

everyone. Uh thank you very much. Thank

everyone. Uh thank you very much. Thank

you Chris. Thank you Hans uh for your time for sharing all of this knowledge with all of us. Thank you everyone for participating uh in today's session. Uh

the recording of this of this webinar will be available in our uh YouTube channel. We're going to send the links

channel. We're going to send the links uh with the material and also with the recording so you can access any time.

And again, if there are any remainer uh questions or doubts or if you want to just chat and clarify about anything else, just please reach out to our uh

speakers today and reach out to us and we're going to be more than happy to address any concerns uh or any comments that you may have. Thank you very much.

Have a good rest of your day and stay tuned for the next one. Thank you.