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June 19, 2025 39 mins

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In this episode, Stephanie McLarty speaks with Rich Savoie, CEO of Adiona Tech, about the importance of sustainable logistics and the role of AI in optimizing transport emissions. They discuss a circular pilot project in Australia focused on recycling champagne corks and the challenges faced in the logistics of recycling. Rich shares insights on the significance of commercial transport emissions, the lessons learned from the pilot, and how AI can help improve supply chain efficiency. The conversation emphasizes the need for businesses to engage CFOs in sustainability initiatives and the urgency of taking action towards greener logistics.


Takeaways

  • Transport emissions are often overlooked but critical to address.
  • Commercial transport contributes significantly to greenhouse gas emissions.
  • Setting clear KPIs is essential for measuring success in sustainability projects.
  • AI can optimize logistics and address driver shortages.
  • Engaging CFOs is crucial for the success of sustainability initiatives.
  • Understanding the entire value chain is key to effective circular projects.


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Want to be a guest on The Circular Future podcast? Email Sanjay Trivedi at strivedi@quantumlifecycle.com


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Transcript

Episode Transcript

Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Stephanie McLarty (00:00):
So much can be learned by trying something
new out, putting theory intopractice.
So what can we learn aboutdoing logistics right to enable
circular projects and to be lowcarbon as well?
Welcome to the Circular Future,your access to thought leaders
and innovations to help you be abusiness sustainability

(00:20):
champion, even if it's not yourcore job.
I'm your host, stephanieMcLarty, head of Sustainability

(00:43):
at Quantum Lifecycle Partners,where we close the loop for
electronics.
In our previous episode, number51, on sustainable procurement,
we talked about the importanceof starting with a pilot, so
today we're unpacking thelogistics takeaways from an
innovative circular pilot inAustralia.

(01:04):
We'll also give an announcementon the podcast at the end of
the episode.
I'm delighted today to have ourguest with me, richard Savoy,
ceo and co-founder of AdionaTech.
Adiona uses AI to powermillions of efficient,
low-carbon deliveries around theworld for brands such as
Coca-Cola and Amazon.

(01:26):
Richard is a sought-afterspeaker and thought leader on
transport, mobility and AI, sowelcome to the podcast, rich.

Richard Savioe (01:36):
Thanks for having me, stephanie, really
appreciate it.

Stephanie McLarty (01:39):
Well, we appreciate having you here and
I'm excited for this topic, allabout green logistics and what
we can learn from this reallycool pilot that we'll talk about
today.
But first let's start, as wealways do, what would be three
things that we wouldn'tnecessarily know about you and
Idiona.

Richard Savioe (01:59):
Well, the first thing would be just the origin
of our name, and I think it'ssomething that people often
overlook and then, when they ask, they're usually surprised to
hear that it's the Roman goddessof the return journey.
So Adiona and her sister,abiona were responsible for
schoolchildren making it safelyback and forth.

(02:20):
The initial motive for ourcompany was to reduce emissions
across all sorts of transport,including commutes and travel to
and from work and things likethat.
So ADN was a really perfectname for us, but it caused lots
of debate.
Of course, it's never as easyto land on a name as you think
it might be, like it just, youknow, popped up out of nowhere.

(02:44):
It was a fierce debate in theteam, but that's where we landed
and we really love it now, I'dsay.
Number two is you know, thereason why we're here and the
reason why ADNA exists is, Ithink, in terms of emissions,
transport, and commercialtransport specifically, is often
a bit overlooked.
So things that people oftendon't know about the transport

(03:04):
industry and its relation togreenhouse gas emissions is.
I'll give you an example herein Australia it's the second
largest emitter, as it is inmany countries around the world,
but as the grid decarbonizesand we move towards more
sustainable sources of energy.
Transport is actually going tobe the number one source of
greenhouse gas emissions by 2030here, so just in five years,

(03:26):
transport is going to be thebiggest.
And when you break downtransport, there's private
transport and things like yourown car, but then there's
commercial transport, thingslike public transport and supply
chain related movements, andanother thing that people often
don't realize is that commercialtransport has the lion's share
of emissions per vehicle or perunit.

(03:47):
What I mean by that, to make itreally simple, is, here in
Australia, articulated trucks,you know so semi-trucks, big
rigs are only 1% of the vehiclepopulation, but they're
responsible for 15% of theemissions.
So, commercial trucks run longer, they're more hours on road,
they're utilized around theclock, whereas your personal car
is probably only utilized 5% ofthe time and it sits there idle

(04:09):
95% of the time.
So while it's great todecarbonize personal transport
and switch to EVs for personaltravel, doing it for commercial
travel is actually, I think,overlooked a bit too much
globally.
So I think that's two and ahalf rounded up to three
unexpected things maybe.

Stephanie McLarty (04:32):
Yeah, I completely agree.
We need to look at commercialtransport and for many companies
, in terms of looking at theirgreenhouse gas emissions, that
is often the biggest source oftheir emissions is their scope.
Three basically upstream anddownstream transportation
emissions.
What they outsource, it is forquantum.

(04:52):
I know that.
I also wanted to mention youknow what?
You're the first guest fromAustralia here on the Circular
Podcast, so welcome.
But I wanted our listeners toknow that we did not travel.
We're not doing this in person,we're doing this virtually,
with a big time difference.

Richard Savioe (05:12):
Just in case anybody thought.

Stephanie McLarty (05:14):
Yes, I know we walk or talk here on the
Circular Future, so we weretalking about a really
fascinating pilot that you'vebeen a part of that has been
around collecting champagnecorks and other types of alcohol
packaging, and it's a reallyfascinating case study, I think,

(05:35):
into how to set up a system tocollect this, but you've learned
a ton out of it.
So tell us about this pilotthat you've been a part of.

Richard Savioe (05:46):
Yeah, and thanks for having us on the podcast to
talk about this, because Ithink it is again something
maybe that people don't thinkabout or is a bit unexpected for
people including myself.
Some of these insights weretotally unexpected and really
important when it comes tocompanies thinking about
circularity and circular economyand the impacts that that has

(06:07):
across the value chain, and Ithink the supply chain component
of the circular economy issomething that's just as
important as every other piece,but is easy to overlook because
it's under the hood.
And you made a great point,which is that a lot of companies
, especially in manufacturingand things like that, they have
these massive scope threeemissions footprints because of

(06:28):
their transport component, butbecause it's scope three and
because they don't have controlover it, it's very easy to
either misestimate it or simplyignore it, and that's the last
thing that we want to be doingif we want to make a real impact
as a team right, as teamsustainability here that we're
all a part of.
Yeah totally.
Yeah, so this pilot is a majorbrand in Australia.

(06:49):
I can't say the name, it'sstill kind of in process, still
happening, but they are one ofthe biggest alcohol distributors
in the country and I knowAustralians have a bit of a
reputation for liking to drink,so you can imagine it's probably
a pretty big company.
So they have a retail footprintaround the country thousands of

(07:13):
stores and what they wanted todo is address some of the
traditionally more difficult torecycle items in their value
chain.
So they're really great abouthaving recycling systems set up
for a lot of the more typicalthings like bottles and cans,
and there's container depositschemes and things like that
which encourage people torecycle those.
And then they've even got apretty mature system around

(07:33):
recycling things like beercartons, like the box cartons
and things like that as well.
But two things that they foundare really difficult to recycle
and require specialist handlingare champagne corks.
As you said, I think a lot ofthe wine industry has moved to
screw top bottles.
So even in your mid range wineshere it's still mostly screw

(07:55):
tops and all that.
But champagne corks andsparkling wines and things like
that still a lot of corks andthey're very difficult to reuse
and repurpose and recycle thingslike that still a lot of corks
and they're very difficult toreuse and repurpose and recycle.
And then the fancier, thealcohol gets.
There's also these kind of waxboard containers that they come
in like the nice fancypresentation boxes that you

(08:16):
might get for a nice bottle ofalcohol, and that goes beyond
champagne.
Things like whiskey and scotchor whatever might have these
really nice boxes.
Again, they can't go in yourtypical household recycling
stream.
So they set up a pilot with aspecialist recycling company to
manage the return to store ofall those items.
So you as a consumer will seethis pop-up display that says,

(08:39):
hey, recycle your wine corks andyour boxes here and you drop
them in this bin.
And the idea is that all ofthose stores will then collect
those items.
They'll then be bundledtogether and consolidated and
then they'll be shipped overseasto a specialist recycler in a
container.
And in theory that soundsreally good.

(09:00):
But what we realized, you know,working through this process, is
that there were some traps,there were some hidden pieces of
information, and let me justuse that as a jumping off to
just explain a little bit aboutwhat we do, what Adionatech does
, which is we do optimizationsoftware for all sorts of
different transport companiesand that's, you know, route

(09:21):
optimization and routeefficiency for individual van
drivers and truck drivers, andthings all the way up to
extremely high-levelconsolidation of minimizing
fleet size, doing fleet analysisand simulation for different
types of organizations that areeither using the fleets
themselves, so they're a carrieror a transporter that has their

(09:42):
own trucks, or, like we weretalking about before,
manufacturers and brands thatoutsource that but want to have
visibility and control andmeasurement of their emissions
through their transport partners.
And that bridge can often bereally difficult to stitch
together.
Our role in this whole pilotwas not really to do any of the

(10:15):
collection or to manage it perse, but to provide them a way to
understand the transport impactthat this recycling stream was
going to have or was having.

Stephanie McLarty (10:20):
in the pilot, yep, go ahead.
And so did you?
Set up goals from the forefrontaround what you wanted to
accomplish, or what they wantedto accomplish, out of this pilot
?
I'm assuming the emissions wasone factor, but what other
things did they think aboutupfront?

Richard Savioe (10:35):
Yeah, that's a great question because there
were goals and KPIs set uparound the more hard KPIs of
recycling how much weight ofproducts are they going to be
able to get back?
That was seen as the mainmeasure of success would be.
You know, to justify this wholeprogram, they need to get a
certain amount of material backto make it worthwhile, and that

(11:01):
is related to the sustainabilitymetrics of well, how much
volume of cork or mass of cork,shall we say, rather than volume
, you know can be recycledthrough this process.
So those KPIs were really muchmore business focused around.
Is this something that, even ifit operates at a loss but it
provides a clear sustainabilityboost in terms of amount of

(11:23):
product that can be recycled, itcould still be worthwhile to
the business because it's apositive thing for their
corporate social responsibilitymetrics, right?

Stephanie McLarty (11:29):
And you were mentioning that this pilot is
actually still going on.
There's clearly some lessonslearned already out of it, but
it's not complete yet either.
Is that right?

Richard Savioe (11:40):
That's right.
That's right.
So the emissions piece that wehelped work on is one piece of
the overall pilot and that isgoing to result in an assessment
across the board of is thissomething that's viable to
continue doing or is thereanother way to potentially
address it that's a bit moresustainable?

Stephanie McLarty (11:59):
Right, because a lot of times you don't
necessarily know or see otherpaths forward until you get
started on one path and stillyou start walking down the path
to see what are the forks in theroad and where do we go.
So let's break this down alittle bit and unpack what the
lessons learned were or so farhave been.
On the positive side, what aresome of the good things that

(12:23):
have occurred out of this pilotthat are takeaways to do again
or to keep doing?

Richard Savioe (12:29):
Yeah, definitely one of the high-level takeaways
is the reduction of waste tolandfill, so they absolutely
have been able to encourageconsumers to return these
products in pretty largequantities and keep them from
going in the traditional wastestream.
I think the other metric thatthey are measuring as well is

(12:50):
they had some data around howmany of these products go into
the actual household recyclingstream and the impact that has
on the sortation facilities.
Because in Australia mostrecycling is overseas outsourced
, like it's actually a prettydifficult thing to get most
things recycled here inAustralia, so they're typically

(13:12):
sent over to into Asia and therecycling is actually done there
.
So anything that you can do tomake the traditional household
recycling stream more efficientis actually a massive ripple
effect.
Right, because just I'll giveyou a worked example, right?
Just imagine a champagne corkgoes into your in Australia it
would be your yellow bin,probably and your yellow bin,

(13:34):
you know, then goes to thesortation facility and this cork
causes a problem with sortationbecause they know it can't go
into the stream.
So either they have to dealwith it there and it causes
disruption locally before theycan get it out, or it does end
up going, I think, as typicallywould be the case, into the
master stream.
That then has to go intocontainers and go on a ship and

(13:56):
get shipped overseas.
So already you can imagine thatthere's this flow on effect
when you can try and divertthings out of the stream at the
origin versus having tocontinually deal with the ripple
effects of it downstream.
Yeah, those are the kind ofpositive outcomes that they've
been measuring and been reallypleased with.
Is you know, working with thelocal sortation facilities to

(14:18):
say, you know, is this a goodthing?
Are you?
Are you saving time andefficiency?
And also like modelingdownstream?
What are the improvements thatcould be seen in the overall
chain?

Stephanie McLarty (14:31):
What about what were some of the ahas that
you got out of this in terms ofthings where you realized you
know we could have done thisdifferently or there's a
different way.
Yeah.

Richard Savioe (14:42):
Well, that's a great segue to you know, we've
only talked about the positivebenefits so far.
Right, I think what our workuncovered was some of the
negative effects, and those weresurprising even to us.
Because, again, I'll give you alittle bit of a worked example.
So say you're in, you knowAustralia is very big for your

(15:04):
listeners that haven't haven'tvisited here, right, it's.
It's physically, geographically, about the same size as the
United States.
So now imagine, from a UScontext, right, for people who
are more familiar with thegeography, you're collecting up
these corks in California, corksin California.

(15:30):
The consolidation center isabout geographically the same
distance as if you were thengoing to consolidate them in
Georgia.
So you're basically goingacross the coast, right, right
these corks and consolidate theminto a container where the port
is, and then ship them overseasto be recycled and mitigated.
So now imagine you've got thesedrop off points all over the US
.
All of those corks are going toget consolidated to Georgia.

(15:52):
Ok, to go in a container and beshipped overseas.
What would be the minimum sizeof a shipment coming from, say,
la or Montana or Toronto to goto Georgia, where the amount of
emissions created from simplyshipping and transporting that

(16:13):
recyclable material back toGeorgia to be consolidated is
going to be outweighed.
So they're collecting thesecorks but they might be calling
for a pickup of those corks whenthere's only about five kilos
of cork, which to a human, youknow.
You pick up a five kilo bag ofcorks.
It seems pretty big right.
But that five kilo bag now hasto travel from wherever the West

(16:33):
Coast or Toronto all the way toGeorgia just to get into the
consolidation stream.
And a five kilo bag of cork,alternatively, going to landfill
.
What is actually the trade-offbetween the transport emissions
and your impact of going tolandfill?
Now that's not a question I cananswer on this podcast.
That's something that's underfierce debate with this pilot.

(16:55):
But you can imagine when youhave thousands of locations all
shipping small consignments toone consolidation center, all
trying to do the right thing.
Are they actually doing theright thing in net benefit way?
And this is an argument acrossall sorts of sustainability
programs, but it was the onethat came out of this pilot.
That was really a bit thoughtprovoking.

Stephanie McLarty (17:17):
Yeah, as a comparable, I remember having a
similar debate around the reuseof electronics.
A similar debate around thereuse of electronics, which is
what we do at Quantum andshipping, let's say, a laptop
over to Europe for reuse.
Does the benefit of having itreused outweigh the
transportation emissions?

(17:38):
And it always depends.
There's so many factors that gointo it so it's a really hard
call to just make a blanketstatement on.
So what were some of the thingsout of this pilot?
You realized that you could dodifferently.
Clearly, researching into whatis the shipment size or weight

(18:03):
that should be shipped acrossthe country Could be one of them
.
But what else have you learnedor done differently?

Richard Savioe (18:10):
This is a great question.
I think one of the things thatwe've applied to this is
knowledge of other types ofsystems that we can use to help
improve, and I'll give you anexample.
One of the fundamental ones isthat rail is a much more
efficient way of transportingthings, and Australia does have
a very significant railfootprint because we have this

(18:31):
massive geography, so this railnetwork is going across the
country.
So a simple change to thestrategy that could be proposed
with this is to simplyconsolidate more and consolidate
enough locally and thenconsolidate it locally until you
have a big enough shipment togo on a rail car to then go
across the country to theconsolidation center and the

(18:54):
difference in your emissionsprofile could be up to 10x like
a full 10x reduction in theamount of emissions that you'd
create from aggregating locallyand then shipping big things in
a rail car versus, like we saidyou know, shipping five kilo
satchels around the country.
So you know, this is the typeof thing that, again, your

(19:16):
average person and well-meaningperson that's setting up a
program like this isn't going toprobably know that that's not
common knowledge outside ofsupply chain and even within
supply chain and even withinsupply chain, it's something
that's debatable because itdepends on how you use it.
So that's one way to again lookat consolidating locally and
making a much more healthycircularity project.

Stephanie McLarty (19:40):
That just reminds me.
In episode number three of theCircular Future podcast, way
back in the beginning, weactually did a case study on the
difference between shippingsomething via rail versus truck,
regular diesel truck versus EVtruck, for example, using the

(20:00):
Tesla semis that aretheoretically out on the road.
I've never seen one.
And what came back and we usedthe case study of shipping a
load from our Edmonton Albertafacility to our Toronto Ontario
facility is what you just saidthat rail actually saved 10
times the emissions than if wedrove it via a diesel truck.

(20:23):
And actually the EV semi wasvery similar to the rail.
It was just slightly under whatthe rail was, but because you
have to charge along the way andthere's different emissions
footprints in each of theprovinces.
But certainly, yeah, optimizingrail is a solution, that's

(20:45):
interesting.

Richard Savioe (20:45):
Oh sorry, I was just going to ask.
Optimizing rail is a solution.
That's interesting.
Oh sorry, I was just going toask In that episode and I may
have to go back and re-listen,as all of your listeners
probably should was there a costmeasurement in that as well,
Like the per kilo or per unitcost between rail and the semi
and the diesel?

Stephanie McLarty (21:02):
We did not look at cost for that, but I
know anecdotally that we do shipprimarily by rail wherever
possible, because it is cheaper.
The downside is it often takesa few days longer than shipping
by truck, and at least in Canadawe don't have rail everywhere,
it's only the major lines, andso we have to get the product to

(21:23):
one of the major centers inorder to get it back.
I'm not sure if it's differentin Australia or not.

Richard Savioe (21:29):
It's definitely pretty similar in the regional
areas.
But it's an interesting pointbecause the other, you know and
this is part of what we do atAdiona is we try to help
companies improve theirsustainability and reduce their
emissions by way of financialefficiency their sustainability
and reduce their emissions byway of financial efficiency.
So that's the world we live in,that your CFO really needs to

(21:50):
be signing off on thesesustainability measures if
they're going to last, and so ifwe can find ways to help
organizations reduce theiremissions but also save money at
the same time, that's how weget the triple win that we call
it.
So this example of a Tesla Semiversus rail your emissions
profile may be identical, but ona dollar for dollar measure,

(22:11):
it's still going to be a lotcheaper via rail.
And if you look at, you know,road congestion and things like
that, you're not affectingcongestion by switching from EV,
switching to EV, from diesel.
And that's another argument thatwe try to apply to commercial
vehicles is, you know, if youswap your car.

(22:33):
Sorry, I don't want to accuseyou of having a certain kind of
car, but if I actually drive, Idrive a gasoline car still.
I still have Mazda because itjust won't die but say, for
instance, I swap my Mazda for anEV, it's not affecting
congestion on the road, it's notaffecting traffic.
So there's just this massivewin to consolidate more into
things like rail or you know,the bigger the better, and then

(22:54):
transport slower.
And the other thing that's coolabout this type of example, in
this case study, is there's nourgency around shipping corks
for recycling.
You can take as long as youwant.

Stephanie McLarty (23:03):
You can take as long as you want.
This is true.
This is true Now.
I know at Adiona you use AI andI believe it's machine learning
to help to optimize the roots.
Basically, you know best inclass technology.
How is that impactingeverything, like what is
available to us now around,these AI type of tools that can

(23:27):
really change things from alogistics perspective.

Richard Savioe (23:31):
Yeah, there's so much changing and so quickly,
and it's both an opportunity anda threat, as we all know, and
there's lots of debate around.
But from our perspective, inour industry, and especially in
relation to transport emissionsreduction, it's a massive
opportunity to use these AItechniques to augment what

(23:53):
humans need to do, and what Imean by that is supply chain is
notoriously manual, it'snotoriously still paper-driven
in a lot of organizations, andso AI has this great ability to
help us advance supply chaingenerally.
The other thing that I think alot of people don't know and may

(24:13):
be useful to think about foryour listeners would be that
across the world, but especiallyin places like North America,
but especially in places likeNorth America, Europe and
Australia there are massivedriver shortages.
The amount of pay per unit toemploy a driver is enormous, and

(24:39):
even though in the US it'sstill the most popular job for
non-college-educated males,which is kind of stunning to
think about millions andmillions of people out driving
trucks, you know millions andmillions of people out driving
trucks.
There's just less and less ofthem every year, but at the same
time, e-commerce is growing.
There's more delivery to home,there's more deliveries just
generally, so you've got thismassive rise of deliveries and

(25:02):
supply chain logistics movementsand you've got this massive
decrease of people willing toactually do the work to drive it
.
So AI is a massive weapon whenit comes to addressing that gap
and making sure that we cancontinue to get things where we
need them when we need them.
And look at examples like whathappened during the pandemic and

(25:22):
the shortages of products thatpeople were seeing in stores.
I'm sure you can remember ifyou go way back.
There was no shortage ofproducts.
There was a shortage of theability to get those products
onto the store shelves.
It was simply a misfire in leansupply chain, and AI can
absolutely help us address thatby being able to predictively

(25:43):
resource things for humans andfor automation.
That's definitely one of themthe ability to say, for instance
, in Canada and the US there's alot of regional transport
networks and if you want to shipsomething across the whole
country, you have to think aboutthe most cost-effective and,
ideally, least or mostsustainable way to do that.

(26:04):
And it's an optimizationproblem because you have to
figure out well which carriercovers which network and point
to point all the way across thecountry, and I can help to solve
that without, without anyintervention.
You know it's a relativelystraightforward problem for it
to solve, but there's all sortsof other cool examples, like in
our industry.
Looking at again, if you have anetwork where you want to hit a

(26:27):
certain emissions reductiontarget, there's so many
different permutations oroptions of your fleet that you
could have.
So I want to reduce mytransport emissions for my fleet
.
Which vehicles would be thebest to convert from diesel to
EV?
Now that's a really complicatedquestion because it depends on

(26:48):
where they serve, the range thatthey serve.
Obviously, range anxiety isstill a real problem.
Where can I get access topublic charging infrastructure
or higher private charginginfrastructure, and how much is
that going to cost me?
What about the depreciation ofmy existing vehicle pool?
I can't just throw away athree-year-old diesel vehicle to
swap it for an EV.
That's not cost effective formy company.

(27:09):
So how do I factor in the ageof my vehicles as well?
You can imagine the number ofvariables that go into that
decision.
To just reduce the emissions by1% of a big fleet Enormously
complicated 1% of a big fleetenormously complicated, rich.

Stephanie McLarty (27:26):
It's not that I need to imagine it.
We have had these conversationsat Quantum looking at all of
these factors, and also anotherone would be the weather.
So in Alberta, fleet has colderwinters than we do in Toronto,
and so there's differentrequirements there.
So, yes, there's so manyfactors to look at.
So use AI to help you.

(27:48):
We didn't use AI to help us, sothat's a really great point.
Okay, let's move into ourhow-to section.
On that note, speaking of AIand especially in this case,
applying AI to logistics, how toimplement AI successfully?
Is it just about using thetools that are available or is

(28:12):
it like a mindset shift that'sneeded first?
What do you think?

Richard Savioe (28:16):
That really depends on the organization.
We see some organizations thatare very excited about AI and
they're charging ahead withexperiments, and maybe they're
sometimes a bit too much of azealot with it, thinking that
it's going to solve all theirproblems right out of the box.
And while that's not the case,I still think that they're going

(28:38):
to do some cool experiments andlearn a lot very quickly and
then that'll guide the future.
So, you know, the top tip thatcomes out of that is just get
started with experiments.
You know stuff that's safe toexperiment with, just data
exercises.
Chuck it to a couple of internsand say, hey, can you do some
analysis using ChatGPT to figureout, you know, to give us some

(28:59):
answers and does that work orwhat value do we get out of it?
And the other the other youknow cautionary tale is that the
market is evolving so quicklywhen it comes to third party
tools.
So also, just, you know, bevery mindful and cautious of
what's what and what is asustainable tool that's going to
be around for a long time.

(29:20):
Like, don't invest a lot oftime in something that maybe
just will evaporate overnight oror become obsolete, you know,
in a year.
So, but the key is to getstarted quickly and just start
doing some experiments to seehow these tools can help you
achieve your goals.
But in order to do that, it'sabout setting some goals.
But in order to do that, it'sabout setting some goals.

(30:04):
And that's where I think a lotof people waste time and maybe
get burnt out on using AI is ifthe goal isn't clearly defined
in the beginning, or at leastkind of you know gray and fuzzy,
but you know you've got adirection to go it can actually
be counterproductive.
And then you know the AI isn'tgoing to be able to make up
those goals for you.
It's still up to theorganization to figure out what
those goals are.
So an example for some of ourcustomers that want, to say,
deliver their products in moregranular time windows, so
meaning, like today they deliverparcels and you get it from 8
am to 6 pm your typical kind ofwindow for getting a parcel and
you don't know when it's goingto come why not use AI to narrow

(30:29):
that time window down and makeit more predictable and then
price stratify it for thatconsumer to say, if you want
your parcel before you leave forwork, you could pay a premium
to get it there in that time,but then AI is under the hood
doing all of the pricingcalculations and profitability
calculations to make sure thatthat's going to be something

(30:52):
that works for the business andthat the pricing is set at the
right level.
So it's just one example of waysthat organizations in our
sphere can use AI to actuallybuild a healthier business,
using AI to protect theirmargins, I mean.
Another thing that's reallyshocking is that, despite the
number of transport companiesthere are here in Australia and

(31:15):
the demand for it and the drivershortages and everything else,
there's transport companies thatgo out of business every day.
They go out of business becausethey're just manually
calculating pricing.
They're manually figuring outwhat their costs are going to be
, and then there's a mismatch ora mistake that leads to
multi-year contracts that aren'tpriced right and then it forces

(31:38):
them into bankruptcy.
It's actually astounding howoften that happens.
Ai can absolutely be a weaponto prevent that.
Once you set it up and you knowwhat your target margins are
that you need for a healthybusiness, let these tools help
protect that and make sure thatany change you make it can help
consider that it's the rightchange long-term for your

(31:59):
business.

Stephanie McLarty (32:04):
I hadn't considered that factor before,
and especially for logistics.
Yeah, that's really important,and the last thing that a
customer like, for example,quantum, would want is that
they're using a service provider, a fleet, that is pricing too
low and it goes out of business.
It doesn't help us either, souse the AI tools that are
available.
Okay, one more how-to question.

(32:24):
You've talked about having goodmargins and the importance of
getting the CFO on board, so akey factor in any successful
sustainability project isgetting the CFO to want to do it
.
How to do that?
How do you get the CFO to wantto do it?
How to do that?

(32:44):
How do you?

Richard Savioe (32:47):
get the CFO to want to do these projects.
It's a great question, and Iremember when we first started
our partnership with KPMG, whois one of our partners the lead
partner that was involved saidwow, adiona is really the CFO's
best friend.
The lead partner that wasinvolved said wow, adiona is
really the CFO's best friend.
And you know, I still take thaton board and think about it,
because you know, if you're aCFO or you're trying to build a

(33:08):
business case for a CFO, theytend to think very wide, you
know.
Obviously, they're alsoextremely smart about thinking
narrow and into the details, butthey're the person who has to
understand how every change inrevenue and every change in cost
affects the profit, and it'sextraordinarily complicated.

(33:31):
So this is where and it's aperfect segue from that last
point this is where you can usemodern data science and AI tools
to build a beautiful,well-thought-out, comprehensive
business case that addresses allof those questions for a CFO
and makes it an easier decision.

(33:52):
Typically, you want them todecide yes for whatever it is
they're proposing, but to haveit really well thought out, and
it's almost like the antithesisof a modern software development
company.
So, if you look at theantithesis of a modern software
development company.
So if you look at the Amazonmindset, where you just break
things really quickly and youiterate super fast, cfos hate
that.
They don't want to do thatstuff.
They want it to be supercalculated, super well thought

(34:15):
out and bulletproof businesscase.
It's a very different mindsetthan your typical developers and
engineers.
So if I'm a developer or anengineer, I'm thinking you know,
if I'm a hammer, everythinglooks like a nail and I just
want to, like, build somethingreally cool, go fast, check it
out to the market and see if itworks.
You present that mindset to aCFO and they're going to shoot a
million holes in it, right?

(34:36):
So this is where we have theopportunity to look across the
entire business and at leasthave a hypothetical scenario
best case, worst case, mediancase of how whatever you're
proposing is going to affect thebusiness.
So if it's, for instance, yourfleet wanting to transition to
more sustainable, loweremissions vehicles, cool, build

(34:59):
a business case that the CFO canlook at and really feel
comfortable that all of thevariables have been addressed
and all the risks have beenaddressed.
All the assumptions are reallyclear and if some of those
assumptions could be wrong, theimpact of those wrong
assumptions is thought out.
Now, that's something that couldtake an enormous amount of

(35:19):
human effort to do traditionally, and still does take a lot of
effort, but this is where yourLLM and AI tools can really help
to make sure that you've gotall of your bases covered.
So when the CFO finally gets ahold of it and does a quick read
through the brief, they're likewow, you've really thought this
through and thought ofeverything.
And then they're on their heelsrather than their toes.

(35:42):
That's where you want them tobe.

Stephanie McLarty (35:44):
The solution to everything.
If you want the CFO to do it,use AI.
There you go.
It's actually really smart.
I love that, rich.
I feel like we could keeptalking for hours.
We don't have that amount oftime.
So, to close things off here,what would be one piece of

(36:06):
advice that you would leave ourlisteners with, particularly
around this whole notion ofgreener logistics and doing
things differently?

Richard Savioe (36:16):
The one notion is to get started.
Today, we're already under thepump.
We're already missing ourtargets, and it's getting worse.
Lots of multinationalorganizations are getting
absolutely brutalized in thepress for missing their net zero
targets.
Their 2025 targets, their 2030targets are under threat, not
going to be made.
So it's all the more importanttoday than it has ever been to

(36:40):
just get started and do what youcan, because we're all in it
together.
There's no planet B and so,regardless of whether you're
interested in our technology oranyone else's technology, or AI
or whatever, just think how canyour business be more
sustainable and how can you lookacross that entire value chain
and not fall into a trap likethe case study that we were

(37:03):
talking about earlier.
Right, like, really think of itfrom end to end.
And then the cool thing is is,when you think about it end to
end, some of the things thatmight seem like great ideas
might actually not meet thenumbers you want to hit or make
a measurable impact.
So just drop them off the listfor now.
Don't don't, don't worry aboutit, don't get stressed out.
If a good idea, superficially,isn't going to lead to the

(37:24):
results you want, just keepgoing until you find ideas that
will move the needle even alittle bit.

Stephanie McLarty (37:30):
Get started today.
Yeah, and on a personal level,one of the things I think about
as a mother is will my daughterask me years from now why I
didn't do anything more thanwhat I'm doing?
So we have to do something.

(37:50):
So get started, use the tools.
Thank you so much.
You've given so much insightand little nuggets of wisdom
throughout this.
I've really enjoyed thisconversation and I see it's
light out now behind you, sohave a great rest of your day.

Richard Savioe (38:09):
Thank you, yeah, it looks like it's going to be
pretty nice out there's no rain,so I'm happy about that.
And thank you for thisconversation I mean it's been
really thoughtful and theperspective that you bring to
the value chain acrosstechnology and supply chain.
It's really nice to speak withpeople who get it from their own
context but then see the bigpicture too.
It's something that we justneed to evangelize more and

(38:31):
hopefully people listening tothis get something out of it.

Stephanie McLarty (38:34):
Yeah, totally .
Thank you, Rich.
Now I made a comment at thebeginning that we're sharing
what's next for the podcast, soa heads up.
The Circular Future podcastwill be taking a break over the
summer months.
This will give us anopportunity to, you know, take
vacation, but also to do areview of the podcast and make

(38:57):
some tweaks.
We'll be back in the fallrefreshed in more ways than one.
And remember, if you haveelectronics you'd like to reuse
or recycle, If you'd like to trya circular pilot, we'd love to
chat, Head on over toquantumlifecyclecom and contact
us.
This is a Quantum Lifecyclepodcast and the producer is
Sanjay Trivedi.

(39:17):
Thank you for being a circularfuture champion in your company
and beyond.
Have a great summer Vloggingoff.
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