Rich Savoie: 0:03

We were able to reduce the amount, total amount of time on road by 48%. So just think about that, like 48% reduction in the amount of drive time, and a 36% reduction in the number of kilometers. And that resulted in about a 15% reduction in the number of trucks required.

Tom Raftery: 0:23

This is episode 92 of the Resilient Supply Chain Podcast, formerly known as the Sustainable Supply Chain Podcast. Good morning, good afternoon, or good evening, wherever you are in the world. I'm your host, Tom Raftery, and welcome to a brand new chapter for the show. If you've been with me for a while, you'll know that this podcast began life as the Digital Supply Chain podcast then evolved into the Sustainable Supply Chain podcast as sustainability became the beating heart of every conversation, and now the world has shifted again. Climate shocks, AI disruption, new regulation and global instability have made one thing crystal clear. A supply chain can't be sustainable unless it's resilient and it can't be resilient unless it's sustainable. So this isn't a pivot, it's a progression. The conversations, the guests, the mission, all remain the same, but the lens has sharpened. We'll still explore decarbonisation, digital transformation and ethical operations, but with a renewed focus on how resilience underpins it all. From data integrity and diversification to circular design and climate ready strategies. So welcome to the Resilient Supply Chain Podcast, same host, same curiosity, even sharper purpose. And what better way to kick things off than with a guest who lives at the intersection of optimisation, AI and sustainability. Rich Savoie, co-founder and CEO of Adiona, joining us from Sydney to talk about last mile logistics, fleet electrification, and how data-driven optimisation can cut emissions while improving efficiency. Rich, welcome to the podcast. Would you like to introduce yourself?

Rich Savoie: 2:16

I would. Thanks Tom. I really appreciate you having me on. My name is Richard Savoie. I'm a co-founder and CEO of a company called Adiona, and we're based here in Sydney, Australia. And we do optimisation for medium and large enterprise supply chain and fleets. And my background is in engineering, but my passion is in commercialising research. So I have a, a wonderful research team that are a bunch of algorithmic developers and my job is to commercialise their AI so that the supply chain world can use it to be more sustainable and efficient.

Tom Raftery: 2:48

Fantastic. And that's not a very strong Australian accent I'm hearing there, Rich.

Rich Savoie: 2:54

If I tried to do an Australian accent, you would definitely not think it was Australian. You'd probably think I was losing my mind. So, good pickup. Tom. I'm, I'm from Boston and I've been in Australia for about 15 years though.

Tom Raftery: 3:07

Oh great. What brought you there?

Rich Savoie: 3:10

My wife, she got a, an offer for a job for a one year contract. And of course that one year contract turned into two, turned into three, turned into dual citizenship, and kids now.

Tom Raftery: 3:23

Fantastic. Great. And tell me about Adiona Rich. You, you're, you're the founder and CEO, so what made you decide that you needed to set up Adiona?

Rich Savoie: 3:34

Well, a quick story, a quick bit of background that people usually find kind of interesting is my background is in medical devices. That's where I really started my career, was in electrical engineering, building cardiology and cardiovascular devices for some big companies like Medtronic. Biggest medical device company in the world. As well as some others. And when I moved here to Sydney, I started leading a small cardiology company. When I say small, about 25 people, but doing big things, exporting to 45 countries through big distributors like Boston Scientific and Johnson & Johnson. And I really fell in love with entrepreneurship and running that small business on behalf of its cardiologist, founder. And I realised that it was the right time for me to step out and do my own thing. Now not being from supply chain specifically, or at least it's definitely not from the transport side of supply chain. I'd been around manufacturing my entire career. Understood that part of it very well. But I had some other ideas around workforce optimisation. So my sister has always worked in retail and she would commute past three instances of the same grocery chain to get to the one that she worked at, simply because that's the one that had the job when she was looking. And if you think about that at scale, there's a massive inefficiency in the workforce. And I, I can go on and on and on about that, which I will spare you. But you know, at the end of the day, it was the first, attempt at building a company around an optimisation framework that I thought would bring not only societal benefits from people having to commute less, but also all the flow on effects like reduced congestion on the road network, reduced emissions due to transport. And through the validation of that business, I learned that there's actually a much bigger opportunity in supply chain and logistics. We realised, you know, that there's a a massive efficiency gap that can be closed, especially using modern AI tools. And my co-founder, who is a PhD in optimisation mathematics and computer science was really instrumental in helping us build the first framework to actually start to test it out in the market. And then it became a growing company.

Tom Raftery: 5:37

Fantastic. And you've worked with some big brands. What's the real bottleneck for them in last mile delivery today?

Rich Savoie: 5:46

Well, we spoke before I, Adiona recently brought on Australia Post as a client, which for people who aren't from Australia it's far away from everything. So it tends to be pretty isolated and that's a challenge in its own way. But it's also enormously large. The continent of Australia is about the same size as the continental US. And so we have this tyranny of distance where you have an enormous amount of territory to cover for a postal organisation and you've got this incredibly inverted mix of dense cities and completely remote regional areas. So it's a very challenging place to optimise freight and transport because of the, different conditions. And we'd, we'd already been on market and doing some work for companies like Coca-Cola, PepsiCo, Amazon DSPs all sorts of interesting companies. And Australia Post realised that they needed newer, better route optimisation, and that was really their impetus for going to market is there was some pull at the high level that they needed to reinvest in optimising their transport network, especially the road transport. And they did a global search, a global technology search, and they evaluated hands-on evaluation of 12 different platforms from around the world. And luckily they realised that the best technology was right here in their backyard in Australia. So now the, the focus is on us to then get that message out there and, and get in front of all these other large logistics companies and fleets.

Tom Raftery: 7:13

And you were the best based on what criteria?

Rich Savoie: 7:18

Well, there's obviously been a long history of optimisation technologies in supply chain. Your listeners will know lots about the types of technologies that have come before. And since the cloud computing revolution in the, late two thousands, early 2010s and whatnot, it enabled a newer breed of technology to come about and some of the problems that we're solving in the optimisation space are that traditional solutions, were very constrained by computation power. Optimisation is a very computationally heavy thing to do, and so you need big computers. You need heavy horsepower processors, and you need to be able to manipulate big data, especially for, an organisation like a postal organisation that does nearly a billion parcels a year. So that was always a limit. But cloud compute made some improvements to availability there. And then native AI development allows us to then also parallel process things in ways that weren't really feasible before after GPS became available. So we're really addressing some of the scale problems that traditional optimisation solutions would hit the wall against. Companies that were used to trying to create an optimal plan for their distribution and having to run a software solution overnight, used to be kind of the norm for, you know, if you're doing a few thousand deliveries. And now they can do that in minutes with a platform like ours. But also it's the quality, as the saying goes, garbage in and garbage out. And so access to good data sources for optimisation was very hard to get as well. If the mapping data that you might use in a, in a traditional route optimisation solution was typically a static set of maps that sits in a basement server and does not get updated very often. You know, kinda like the maps in your car right when it's telling you, asking you to pay some money to update the maps. Now we have access to global data sources with real time traffic, historical traffic profiles, and driving duration from point to point rather than just distance. So we can do so much more in terms of accurate and efficient optimisation with these new data sources than could be done before. That's another type of problem that we're solving.

Tom Raftery: 9:29

Okay, Rich last mile is the shortest part of the supply chain, but the most expensive and carbon intensive. So why is it still so hard to get that right?

Rich Savoie: 9:43

Yeah, it is. According to World Economic Forum, 53% of the total cost of transport is in that last mile piece. And you know, another kinda shocking stat is that as the grid decarbonises in a lot of countries worldwide transport has always been the second largest emitter, but it's on track to be the largest emitter by 2030. And a lot of that has to do also with e-commerce growth, right? Countries all over the world have modernised their e-commerce and now the amount of product shipments has grown extremely quickly. So even companies that are trying to do their best to be more sustainable, they're investing in things like sustainable packaging. They're investing in better reusable materials and all sorts of great initiatives to make their supply chain and transport piece more sustainable. It tends to be a pretty linear relationship between how much product you put on a truck and how many carbon molecules, you emit outta the back of that truck. So it's become a very difficult problem for them to solve, and we help them do it in a few different ways. One is simply with visibility. So by building in carbon emissions measurements, simulation and reporting, it allows a manufacturer or a transporter to know what their emissions profile looks like realistically. And that's super important, especially for a manufacturer who doesn't actually run the transport. They rely on a third party logistics or four party logistics to do it. They need to get that data back from that carrier in order to know what the emissions are. But using our platform, they can create a digital twin of it and then know effectively what the emissions are when they engage with that carrier. And that also then allows them to look at simulation. How do you then invest in cleaner vehicles? Cleaner drive trains, less vehicles where you can get away with it. Core optimisation that can bring down the amount of kilometers that you need to traverse and then bring down your emissions. And then the final piece is electric vehicle native tools. The ability to use one platform to run your traditional diesel and petrol vehicles, no problem. But then we have tools so that when they are ready to start experimenting with lower emissions vehicles like electric or hydrogen, they can do that all within the same platform.

Tom Raftery: 12:01

I noticed on your website you've got a workbook and also a workshop to help people

Rich Savoie: 12:08

Hmm.

Tom Raftery: 12:08

move to EVs. Can you talk me through some of the things that are in that, because I didn't sign up to download it, to be, I'm completely honest, so I didn't get a look at it. But what, what can people learn from that?

Rich Savoie: 12:23

I'll send you a copy, Tom. Don't worry.

Tom Raftery: 12:25

Great.

Rich Savoie: 12:25

It runs through a number of strategies. And, and first of all is highlighting the importance of commercial vehicle electrification especially in the context of what I just talked about with transport emissions being so substantial and being so material. It's also the fact that commercial vehicles run longer than a passenger vehicle. They travel more than a, a passenger vehicle. The utilisation is huge. So actually by investing and optimising and transitioning them to EVs, there's more bang for buck there. Like the sustainability improvements you can make and the emissions avoidance and abatement you can make is really significant with commercial fleets generally. And like here in Australia articulated trucks like big rigs, semis those types of very large vehicles, class eight and whatnot are only 1% of the vehicle population, but they're responsible for 15% of the emissions. So what we talk about in the workbook and in the workshops is that when you're looking at optimising and moving to EVs, that's the right time to right-size your fleet. And there's a bit of method behind that very simple statement. Right-sizing your fleet, especially in the context of EVs, is so important because oftentimes it's looked at like a one-to-one swap. I've got a diesel delivery van that's operating in the metro area, and I'm just gonna swap it with an EV that has the best range. And I'm off to the races. That is absolutely poor strategy because it's gonna lead to the most expensive outcome and it's gonna lead to broken hearts when those vans don't necessarily live up to their diesel counterparts. And there's all sorts of problems. So expectation management is really important in there and, it's also so important to take the time to really analyze your network and say where are the right places where EVs could be dropped in as a direct replacement, but where are the other places where we might need to reorganize the network, reoptimise and ideally reduce the vehicle count so that we have more money, more capital available to invest in new vehicles. We think it's a really holistic thing that you need to step through. And another key part that you know, you'll see when I send you your copy is stakeholder management. Because oftentimes these programs while they have a lot of support at the boardroom nobody's willing to pay too high of a carbon premium. And by carbon premium, I mean, supply chain companies operate on thin margins on a good day, right? There's a lot of CapEx, a lot of opex. And so if you're trying to tell your business that we should invest in being more sustainable, but it's gonna cost us 40% more per consignment. It's not gonna happen. There's just no way. So that idea of bringing people at different points and different stakeholders in so that they understand that this can be financially efficient, it can lead to better financial outcomes, as well as the sustainability outcomes is so critical to getting the support that you need to actually then go and do the implementation.

Tom Raftery: 15:28

And you gotta think as well, it depends a lot on the cost of the different fuels for vehicles. If I'm saying that because you need to get, you need to justify the ROI to move to EVs as well. And in just talking about my own case locally here in Spain, my cheap rate for electricity is 8 cent per kilowatt hour. My battery in my vehicle is quite large. It's an 80 kilowatt hour battery. So to fill the tank of that car is six euro 40, and the range of the car is around 530 kilometers, so the economics of that are quite good. Especially considering that a similar sized vehicle would be paying around one Euro 50 for a liter of diesel, and let's say it gets, I don't know, make the maths easy, five liters per hundred kilometers, suddenly you're looking at seven 50 per a hundred kilometers. No, that's wrong. no, that's right.

Rich Savoie: 16:38

Five and so

Tom Raftery: 16:40

kilometers times five is 40 something Euros,

Rich Savoie: 16:44

37 50. Yeah.

Tom Raftery: 16:46

you know, so it's in that case, the economics work quite well on the operating costs, but that's not the same everywhere is it?

Rich Savoie: 16:55

Exactly right. So that breakdown of spend and the electricity cost is gonna be very different depending on whether you're already in an area that's using a sustainable or renewable grid. It's gonna be dependent on load time. So when you charge. For commercial operations, there's a lot of investment in algorithms to arbitrage those prices. Which we, we we're kind of aligned with, but it's not something that we do directly. And to your point, like you, you really need to pick the right vehicle and understand when and where to charge it in order to get that good ROI.

Tom Raftery: 17:31

Yeah, and of course if fuel costs are lower as well, for petrol or diesel, that makes the economics more difficult to justify. And then maintenance costs as well on EVs are typically 50% of the maintenance costs of petrol or diesel. So it's another factor you gotta work in as well.

Rich Savoie: 17:48

Yeah, there's a few trade offs too, you know, when you start to stack it up. There's also, you know, like, the interesting thing that I highlight to fleets sometimes, especially in the context of it being very hard to recruit for drivers and hard to recruit in supply chain generally, and manufacturing. So, you know, there's massive labor shortage globally in, in those industries. So one of the things that I, I always remind people is that if you look at the stack of costs going into your total cost of ownership of a vehicle, at the top isn't fuel. At the top isn't insurance. At the top isn't maintenance, it's labor. It's the person that's driving the vehicle that actually drives the majority of the cost of that electric vehicle. And so again, if you can optimise to the point where you can get rid of vehicles and do more with less, that's how you're gonna actually save a lot more in proportion to the other costs.

Tom Raftery: 18:39

What about the move to the likes of micro mobility and cargo bikes and things like that? Is that something you're seeing happening as well and something that you can help manage?

Rich Savoie: 18:49

Yeah, I, I love cargo bikes. In fact, we started the first, and by started, I mean we enabled the company here in Australia called Parcel Point to set up a cargo bike network that was based out of convenience stores, news agencies.

Tom Raftery: 19:04

Hmm.

Rich Savoie: 19:04

It was a really cool model where they have a line hall with residential parcels mainly. They partner with the shops and, and, and there's a few different models of this worldwide, you know, where they partner with bodegas in Manhattan to do this and convenience stores in, in lots of places. So they go and they fill out the inventory of parcels, and then if the person doesn't collect that parcel from that location within 24 hours. The shop owner gets kind of cranky, doesn't want stale inventory sitting around that nobody's gonna come and get taking up space in their store. So then they dispatch a cargo bike rider to then take a bundle, put them on the cargo bike, and then go off into the local area and and deliver them. And our algorithms power that end to end. Meaning that knowing what the parcel volume was gonna be for the next day, they could figure out exactly what blocks of 10 ish parcels, you know, a, a block being big enough to go on a cargo bike tray would be bundled together and then put into satchels, and then delivered as pre-made satchels to the convenience stores. Now, of course, customer comes and picks up a parcel. Cool. You just take it outta that block and it means that there's less in there for the cargo bike rider. But that's cool. And then pre-made routes for all those cargo bike riders as well. So you get this really dynamic bike based routing model that was really, really fun to build. And we're starting to see more take up of globally, slowly.

Tom Raftery: 20:28

Very nice. Very nice. And. If we look at trends then around emissions reporting, which is becoming mandatory in more, in more markets, where do you see companies tripping up there and where do you see is the biggest opportunity?

Rich Savoie: 20:45

It's really interesting because for people who aren't familiar with the scope concepts of emissions, the scope one, two, and three, and that's a pretty internationally harmonised framework now that people think about emissions in. Scope one being the emissions that you create yourself. So if I'm a manufacturer that also does my own transport, all the vehicles that I own are gonna make emissions and I own those as scope one. Scope two tends to be the electricity that you consume. So for all of your sites, you're not emitting that carbon directly you're emitting it through your electricity company, wherever they're making the electricity. So that's your scope two. Scope three is pretty much everything else, all the indirect emissions that you might be responsible for, which is really important if you are a manufacturer that's using a 3PL to do your deliveries on your behalf. Oftentimes what we find is that there's this big knowledge gap between a very large manufacturer who is on the hook for mandatory reporting to their local government, domestic government, and a smaller carrier who isn't necessarily on the hook to do any reporting at all, and so they're not really measuring their emissions. They're not really tracking that, especially at like a per consignment or a per pallet level. And so now this, their customer is getting a bit salty because they need to get that data to then do their mandatory reporting. And if they don't, the shareholders are gonna be very upset when they get a fine out over it. So you can see that it's a very quickly moving market that's, that's growing and maturing very quickly. But what we see is the ability to bridge that gap is possible through these simulation and modeling techniques where the, you know, the manufacturer can at least get an idea of what that carrier is doing, and then give them the guidance to say, okay, here's the exact data that I need. I've kind of shown it to you. I've shown you exactly what you need to provide me. There's no ambiguity to it. And we kinda help them to all do that.

Tom Raftery: 22:39

Nice. Okay. AI and machine learning are the flavor of the day or the year or the last couple of years. They're often powering this new wave of routing. What's changed in the last five years that's made this tech so much more effective? I mean, you're not using LLMs, right?

Rich Savoie: 23:00

No, we, we don't use LLMs, In fact, as I think I mentioned, my co-founder is a PhD in optimisation mathematics, and machine learning. We started using AI that he'd been using in his research early on, but it was more around hardcore optimisation and clustering. But then we started investing in building deep learning models that could normalise the data. So, effectively something that modern LLMs are very, very good at, and in fact better than what we developed. So it's an interesting world where now I think a lot of companies that, are quite skilled in AI have to choose. Well, what do we build and what do we buy? And we've had to be more shrewd about that as well. And I think that there is a massive opportunity for AI, especially when you look at agentic AI, vibe coding. For organisations to start to build things to use themselves and not necessarily rely on external solutions, external vendors. So if, if I'm a big supply chain company right now, and all I need is a a CRM for my team of sales reps to go out and, and manage their work. I'll probably build that myself. I don't need to spend money on that. And it's so possible with AI. But then if there's other things in my business that are much more deep regulated niche finance being a great option, like I'm not gonna go and build my own payroll system using AI. It's too risky. And the solution providers have spent their entire life's work building something that's compliant and and reliable. Right. There's this really interesting shakeup of how the solutions market is gonna play out, because we can use AI for all sorts of other cool things in supply chain that people can't replicate because it requires access to data. And it sounds almost like the same thing we were talking about 10, 15 years ago, where data is so valuable and it's the key. Well, it turns out that in an AI world that's still true. You know, we're building AI that, has a closed loop feedback so that everything that happens in the field, every proof of delivery event, every geofence break that logs where the vehicle is at. Every change, an allocator or a dispatcher makes to a route plan. All of that is fed back into our system. And then we use AI to hyper fine tune the routing for each individual client in each individual area. You cannot create a general purpose LLM style neural net that can do that effectively with a huge diversity of the stuff that different supply chain and delivery operations do. But in specialist hands like ours, you can create these really hyper-specific models that do allow you to get a massive benefit out of AI, but it's really specialised per organisation.

Tom Raftery: 25:43

Right. I had a chap on the podcast, Dr. Eric Garcell of months back talking about quantum computing. And it was his contention on that episode that one of the big use cases for quantum computing is optimisation. That it's way, way better than AI for that kind of thing, particularly. Is that something you're looking at as well, the move towards quantum computing?

Rich Savoie: 26:12

Yeah, I'm, I'm gonna age myself a little bit, Tom. I actually did my undergrad capstone thesis project on quantum computing back in 2001, and it felt like it was just around the corner. And we're now nearly, officially 25 years later. And it's definitely, advanced a lot, but it's far from being a, a household dinner table conversation. Right. But I think Eric is very wise to, point out optimisation because you know, the top three things I think that people talk about routinely when it comes to quantum and the applicability of quantum computing in real practical situations is cryptography. The fact that it can potentially solve and or encode encryption very, very quickly compared to a standard computer. Navigation so, Australia's a mining country. We have these amazing magnetic maps of the entire country with the magnetic field, and you can actually use quantum transceivers to navigate without GPS based on the magnetic signature of the earth. And I'm talking like hyper fine navigation. So it's really cool. And then optimisation. And optimisation is because, you know, as I mentioned the compute power for traditional computers to do optimisation is really intense. There's so many different permutations and options that you have to solve through to find which one's most efficient. Quantum has the ability to do that in a much more parallelised way, based on the nature of, of having three states instead of two. So in theory, it's gonna be the panacea for optimisation, but what we see in practically is that the hardware has not evolved to a level of stability to allow us to solve optimisation problems at scale to make, a real, because the, the biggest advancements are, are things where you start looking at big, big numbers. That's where you're gonna get the best benefit out of quantum. But we will have an announcement hopefully soon in the next few months, maybe to circle back to you about a partnership that we're working on that will allow us to pilot some of the first quantum routing technology in the world.

Tom Raftery: 28:16

Oh wow. Interesting. Definitely get back to me when you, when you make that announcement, I'd be fascinated. How then do you balance the likes of machine-driven efficiency with the day-to-day realities of the human drivers, customer needs, unpredictable traffic, et cetera, et cetera.

Rich Savoie: 28:39

It's part of our North Star goal that we, we've always wanted to create this triple win where businesses can be more financially efficient, we can reduce emissions, and then we can develop what we call humanistic AI. And that humanistic AI is to never take your focus off of making sure that you're improving the actual day-to-day life of the workforce, so these people that are on the front lines and warehouses and, and delivery drivers. And you're also providing value to the end customers, the, the, the people receiving it, whether it's a residential parcel drop, or whether it's a cafe getting a delivery of milk. You wanna make sure that the experience improves rather than it gets worse because of the technology. And I think that's something that's been a really good guiding light for us. Because we do take really, seriously the risk impact of any change or any, any feature that we deploy. Yes, this is gonna make this one user happy because they can do this one thing, but what is the flow on effect? Is it gonna make it harder for the driver to do their job? Is it gonna make it you know, the, the ETA less predictable or, or what have you? So that's something that's really important. The, the other thing, you know, to answer your question is that all of our best ideas typically come from our customers. The ones I like to talk about is for high density parcel couriers in a, city you wanna park the minimum number of times and then do as much work on foot as possible with a two wheel dolly or with a satchel or whatever. And most software solutions for some reason have still missed the brief on that. And they route them point to point, to point, to point, to point, to point to point. And we said, well, you know, this is what humanistic AI should do. How do we build a model that actually looks for minimal parking locations, maximum density on foot, and then prioritises those so that you get the best blend of efficiency and doing exactly what the human the courier wants to do. And I think that's something that's, gonna keep AI relevant in our lives as something that augments us rather than replaces or annoys us.

Tom Raftery: 30:41

Yeah, no, that makes sense. You're based in Australia, but you're obviously looking into Europe and the Americas. What's the biggest difference in how these markets approach last mile sustainability?

Rich Savoie: 30:54

Well, Europe has always been on the forefront. They've created a lot of the frameworks that we use to do emissions calculations and reporting globally. The first carbon emissions measurement APIs for fleets came out of Europe. And, and I think there's always been a great focus on it there. So the bar is very high and every country has its own kind of specialty and, and own way of approaching those frameworks. And that makes it a very complicated market. It requires basically a country by country approach to look at these things from what we've seen. Then you, you look at places like North America where there's not a significant difference between how the technology stack and the regulatory stack operates between Canada and the US. Yes, there are differences, but at the end of the day, they're not as material as the ones in Europe. And then, you know, another market that we're investing in is Southeast Asia because you have this massive growth in e-commerce and delivery operations generally, and you've got a rapidly maturing road network and data infrastructure network that makes it a great place to make a really big impact really fast.

Tom Raftery: 32:05

And which regulatory, or market shifts will most accelerate sustainable last mile adoption in the next three to five years, do you think?

Rich Savoie: 32:16

It depends on a few things, but I think from a sustainability perspective, electrifying the fleets is the the best thing that we can do, and we certainly got a lot of traction on that and you know, Europe has done very well and, and you look at places like Norway where EVs are like 97% of new sales. You know, that that's Europe is leading the way by far there. But in other markets like Australia it's just been very slow to get traction because the regulators have not really provided significant incentives. And they've not mandated things like, I don't know how much of your audience might know this, but Australia was one of only a few countries in the world without a fuel efficiency standard for vehicles, for any vehicle. So, you know, the rest of the world is, is just dumping their worst, least efficient, most polluting vehicles in Australia because it's a very, good market. It's a great automotive market. A lot of people to buy cars here with money, and there's no regulation on the emissions, so they can just chuck whatever they want. And so you can imagine that now I say there is none. I mean, there was none. They've just started implementing it now, but this is something that even in the US has been around for nearly 30 years. In Europe for longer than that. So yeah, Australia is way behind the eight ball here, which is almost an opportunity for us because we're looking at these best practices from Europe. We're looking at the winners in markets like the US and Canada, and then we're trying to apply that knowledge here and do a bit of if you build it, they will come.'cause they will, they will come, they'll follow with the rest of the world, but it'll just take a little bit longer.

Tom Raftery: 33:59

If you were designing the perfect EV transition pilot for a delivery fleet, what would you say are kind of the must haves?

Rich Savoie: 34:08

To be really careful about vehicle choice. Don't just believe what the OEMs tell you. You know, think really, really hard about what payload you need and what range you need. And then also look at some of the details that make EVs very different from ICE. You know, internal combustion engine vehicles, they can't operate on as steep of a grade. They can get stuck on steep grades. The battery depletes much faster under payload than running empty. Temperature is a big impact. You know, whether you're operating in, in a really cold environment or a really hot environment, both of them will affect your, your battery consumption. So take a, a really hard look at the types of vehicles that you're, you're gonna pilot and then work with a trusted infrastructure partner. You know, always make sure that they have a relationship with the grid provider that you're on. You don't, you don't wanna be the first one that this, you know, infrastructure company is, is trying to negotiate on the grid with and make sure that they have a really deep and clear understanding of your requirements operationally. Meaning if I'm a, if I'm Australia Post, you know, or I'm a parcel courier, I might be operating three shifts around the clock. And that makes charging much more difficult at cheap times or, or at any time. Right? Likewise, if I'm a refrigerated, fast moving consumer goods company I've gotta run reefers. I, need to worry about refrigeration depleting my vehicles as well. And if my charge partner just doesn't understand that, which trust me, sometimes they don't. That could be really catastrophic. And, and so all those things really clear understanding. Don't treat it like a flight of fancy, like it's a, an interesting thing to do. You know, treat it like something that actually you want to succeed.

Tom Raftery: 35:46

Can you walk us through a real fleet you've worked with and what the before and after looked like?

Rich Savoie: 35:53

Yeah, well when we first started here in Australia, one of the first companies that we started working with was Coca-Cola Amatil, which is the, bottler here in Asia Pacific. They were acquired by CCEP, Coca-Cola, Europacific Partners. When we first built the first version of our platform, they were the pilot customer, and we were all a bit stunned with the early results because for one of their direct to consumer fleets running more than a hundred trucks nationally we were able to reduce the amount, total amount of time on road by 48%. So just think about that, like 48% reduction in the amount of drive time and a 36% reduction in the number of kilometers, and that resulted in about a 15% reduction in the number of trucks required. So big trucks. Big money, you know, six figures, operating costs per per truck, per year, being able to reduce that by 15%. And then the emissions were effectively you know, very similar to the kilometer reduction. So about 36% reduction in the related emissions. All to do the same amount of work. So it allowed them to reinvest in their network, reinvest in their drivers, and reinvest in the future of their business.

Tom Raftery: 37:06

Sounds like a, a very short ROI. If you could wave a, a magic wand and fix one thing about global delivery systems tomorrow, what would that be?

Rich Savoie: 37:17

Only one. I'm only allowed one. I think it would really be about transparency of data. Being able to see data at every leg of a journey, of an item, of a parcel, of a raw material seamlessly from an end to end. Because the inability to see through that and to to have that visibility really creates a massive on-flow of problems, like a butterfly effect of problems where every time someone needs to inquire or wonder or challenge where something is, there is an inefficiency that's created there. And every little inefficiency that's created along that journey, which could be tens, hundreds, thousands of questions that are created about where something is or, or a shipment. That inefficiency effect is massive. It's very difficult to measure. Even in parcel shipment world, you know, what we call the POD, the proof of delivery, it's this one simple data point that people are constantly chasing, and questioning and referring to. And it's the reason that your courier takes a photo when they leave something because that one single piece of information, having it transparent, visible, and interrogable, you know, being able to interrogate it from end to end at any time creates a massive efficiency increase that you just can't get otherwise.

Tom Raftery: 38:37

Okay, a left field question for you Rich. If you could have any person or character alive or dead, real or fictional, as a champion for last mile sustainability, who would it be and why?

Rich Savoie: 38:54

Anyone alive or dead as a champion for sustainability? Well, I think we talked

Tom Raftery: 38:58

Re real or fictional?

Rich Savoie: 39:00

Well, yeah, that's a, that's a great point because you know, our name Adiona is inspired by the Roman goddess of the return journey. And I think

Tom Raftery: 39:07

Hmm.

Rich Savoie: 39:08

might have mentioned that at the, the beginning. So circling right back around, you know, there is almost this mythical proportion that we need to defer to, you know, our, our existence on this planet is is something that we can't take for granted. And it is something that's bigger than us. It's literally existential to the truest definition. So I almost feel like if you were to give me that option, I would invoke a god or goddess like character that has a bigger than life, beyond the realm of reality type presence, to really help people understand that what we're dealing with here is, is beyond ourselves. It's, it's you know, whether we live or die, the earth will still be here. If we ruin the terraform here, the earth will still persist and life will probably march on, but we won't be here to see it. And we are notoriously self-destructive. We're just notoriously unable to see the big picture, and that's okay. That's, that's part of who we are and how we got to where we are today. But if, if I wanted one person, it would be maybe Adiona the goddess of the return journey to, to swoop down from the heavens and scare the pants off people to get them to be serious about this.

Tom Raftery: 40:20

Great. Great. I love it. Super rich. We're coming towards the end of the podcast now. Is there any question I haven't asked that you wish I had or any aspect of this we haven't touched on that you think it's important for people to be aware of?

Rich Savoie: 40:35

No, Tom, I think you've done a fantastic job of really teasing through the, the edges of this. I guess the only thing I can add is that I'm easy to find, so if people want to, to seek me out on LinkedIn or send me an email, they're more than welcome to. I really do enjoy talking about this stuff and having discourse and debate. So, if anybody disagrees with me, I also encourage them to, to reach out and challenge me in any way, because that's how we all grow.

Tom Raftery: 41:00

Okay, fantastic. So. I'll put those links, the links to your LinkedIn account and I assume the Adiona website in the show notes so that everyone has access to them. Fantastic. Rich, that's been really interesting. Thanks a million for coming on the podcast today.

Rich Savoie: 41:15

Thanks for having me, Tom. It was really fun.

Tom Raftery: 41:18

Okay. Thanks everyone for listening to this episode of the Resilient Supply Chain Podcast with me, Tom Raftery. Every week, thousands of senior supply chain and sustainability leaders tune in to learn what's next in resilience, innovation, and transformation. If your organisation wants to reach this influential global audience, the people shaping the future of supply chains, consider partnering with the show. Sponsorship isn't just brand visibility, it's thought leadership, credibility, and direct engagement with the decision makers driving change. To explore how we can spotlight your story or your solutions, connect with me on LinkedIn or drop me an email at Tom at tom Raftery dot com. Let's collaborate to build smarter, more resilient, more sustainable supply chains together. Thanks for tuning in, and I'll catch you all in the next episode.