Kevin Frechette: 0:03

People are definitely scared of losing control. And that could be control from a risk perspective or it could be control from their jobs. Because if people have been doing the same job for 15, 20 years, it's very tactical work, it's stuff that can be automated, and Gen AI can replace, then they have that concern. I would say, The same thing happened with computers, where everyone thought computers were going to take everyone's jobs. That didn't happen. It just created new jobs and made people more efficient

Tom Raftery: 0:26

Good morning, good afternoon, or good evening, wherever you are in the world. This is the Sustainable Supply Chain Podcast, the number one podcast focusing on sustainability and supply chains, and I'm your host, Tom Raftery. Hi, everyone. Welcome to the Sustainable Supply Chain podcast. Today's episode of the podcast is generously sponsored by Live EO, the company unlocking the potential of earth observation. My name is Tom Raftery. And with me on the show today, I've got my special guest, Kevin. Kevin, welcome to the podcast. Would you like to introduce yourself?

Kevin Frechette: 1:01

Yeah, would love to, and thank you for the invitation to join. So Kevin Frechette, co founder and CEO of Fairmarkit. We are an AI powered sourcing platform. We've leaned in very heavily to Gen AI the last eight to nine months. And we didn't originally start the platform to help with ESG initiatives and goals for our customers, which are typically large enterprises. But over the last four or five years, we've seen kind of this shift towards that being one of the major business initiatives that our customers do have. But it's been kind of this like tough polarizing trap they've been caught in, which is we don't have, can't get a lot more people to achieve our ESG goals. So how can we do it? And then how can we also set up the whole culture within our organization to say, let's make it easy to do the right thing when it comes to ESG. So it's been a, it's been a cool experience kind of seeing this shift both in the U S and international. We were about split half and half. And when I was preparing for this podcast, I listened to a bunch of episodes and I realized that I don't know enough about sustainability and ESG. So I went out and I talked to a lot of our customers. I talked to a lot of the experts in the field. Just said I wanted to pull some like different suggestions and ideas. So I, a lot of what I'll talk about today, some, I'll be heavy on AI, Gen AI, but some different ideas and examples I'll actually pull from customers and kind of share their stories as well.

Tom Raftery: 2:14

Okay. Excellent. Before we get into that, can you start by giving us a bit about your journey and how you ended up co founding Fairmarkit with Victor? What kind of inspired you to focus on autonomous sourcing and procurement?

Kevin Frechette: 2:27

Yeah we didn't wake up one day with this like crazy great idea. It was more we started the company and we started to talk to a lot of procurement teams cause we're very much in the sourcing space, procurement space, and it blew our mind how outdated and legacy the tools and the processes were today, just how manual they were. And then how that made it so challenging to go off and to achieve business objectives or just to take large leaps forward when it came to value, because everything was just like hands on keyboard, getting a couple percent better every year. So we kind of just decided to take this, this leap of faith and say, you know what, if we can bring in AI to this archaic industry and even back four or five years ago, it was very basic AI. It wasn't like this crazy, like earth shattering thing. But we could start to show incremental value. We could start to show people that you could get to a better state, deliver a better end user experience. And then that kind of was the springboard where once you start working with some of the largest companies in the world, you build trust with them as one of their digital or AI wins, you can keep building on that. And then that kind of put us in the driver's seat for these companies to say when Gen AI came out, we leaned into it. We showed how we could not create a whole new platform around it, but we could accelerate our platform with Gen AI. And then we've gotten wins with them along the way. Some of them ESG, some of them cost saving, some of them de risking, some of them turnaround time or operational efficiency. But yeah, it's, it still feels like a brand new startup, even though we're I'll call it a mid size company right now, still startup mentality, but it's been, it's been a great journey.

Tom Raftery: 3:48

Fantastic, fantastic. And how, well, what are the biggest trends you're seeing in the procurement space today, for example? What are, and what kind of role is technology playing in that? I mean, obviously from what you're saying, it's all about the AI, but what kind of trends are you seeing?

Kevin Frechette: 4:03

Yeah curiosity, intrigue, and Gen AI. I wouldn't say that's a trend yet, that's a hype cycle. That, it's not a bubble, like Gen AI is real, AI is real, but it's overhyped, kind of Amara's Law where people are kind of overestimating its potential in the short term, probably underestimating the potential in the long term. But from a business output perspective, as much as people don't like to admit it, cost savings is still always a big one. And you don't have, you don't hear people talk about it at conferences, but it's real. ESG has been much bigger. We saw that more with our customers U. S. It was more diversity. International, it was more sustainability. We're just starting to see kind of that cross pollination of ESG just being widely accepted and driven towards across everywhere across the globe or most, most regions. So that's a big one. And then it's more so like, how do you do it? And how are you making sure you're not just doing window service and trying to like talk to the market about it, but actually doing it and setting up the plan, process, people, technology to do it. And then risk is always a big one. Risk could be risk in terms of who you're working with, or it could be risk from a continuity perspective. Because as you see, like from a supply chain perspective, if you are single threaded, it makes it very difficult to say with like strong confidence that you do have resilience in your supply chain to support your customers. And then the final one is like, how are we getting more productivity out of our people with AI? So I'd say every one of our customers, like, depending on who you're talking to, that's one of the biggest wants. Because you have people, you want to make sure they're getting as much output as possible with them. And a lot of people are starting to move towards, like, let's not have them do tactical work, it's strategic, and have it be human by exception. Not have it be humans do all this redundant manual work, because that also burns people out.

Tom Raftery: 5:36

Yeah, yeah, yeah, yeah. Of course, of course. But how, from a kind of a practical perspective, how is Gen AI revolutionizing the way organizations manner manage supplier transparency and compliance, for example?

Kevin Frechette: 5:50

There's a lot of different ways. And I think I think the one thing to call out before we get into any type of Gen AI talk, and happy to go into as deep as you want, is Gen AI is not a silver bullet. Gen AI is not going to solve the problems of the world. It's not gonna be this like end all be all, but I think it's a really cool like if humans assist it, it can have some good incremental value. A couple of different examples. So one would be looking at Gen AI to say, how do we make sure, A, we're getting the right ESG suppliers to actually come to the table, where if you think about the process today, for a lot of our customers, they have a very manual, we're in the world of sourcing, very manual sourcing process for their large, complex events. So their biggest contracts that they say, all right, for these contracts, we're going to make sure we invite in a couple ESG suppliers, and then hopefully they win. And if they don't win, then that's kind of is what it is. If they don't win, then what we're going to do is do the ESG requirements to make sure we validate who the supplier is that we do want to win the business, but that's usually after the fact in terms of a lot of that work getting done. So if we want to go like very top of the funnel in this process, I think you're going to see a lot more of this being required by the SEC in terms of like regulations of like, what's your process and compliance to show that you are being inclusive for ESG suppliers is, first, let's make sure we're asking the right questions when we are going out to these suppliers for the events. And not just for your biggest events, those 5 or 10 you do a year, let's do it for the tens of thousands of events that you have, or purchases that you do. A lot of times it's called the tail spend or the tactical spend, those events are forgotten about. So first is, let's not just trust the suppliers that they ask one question about, let's make sure we ask proper questions. So when we're capturing that information, we have it. Next, you can use AI and GenAI to say, all right, based off these requirements, based off what our policies and procedures are, because you can have your policies and procedures now tagged within Retrieval Augmented Generation. So you have an LLM that's interacting with your end users. You then have your policies and procedures, a lot of them being ESG, that are saying, all right, based off this type of request, these are the type of questions we need to ask. And then based off this, here's the suppliers that we believe should be invited to this. All of that's very manual or very difficult to do without technology. And then once you have the suppliers actually bidding, now you can actually start to look at their responses. And instead of saying, so example, I literally right before this, I was on the call with a CPO of a fortune 500 company, and we were talking through these different examples. So he gave the example of like, all right, so say we want to ask them, do you have a modern slavery statement? And then the question could be, yes. Okay. Checkbox. We got that. But what if their statement is that they only use children over the age of 12. This is the example he used. Like that's not going to help us out from sustainability. So then the question is, all right, it's, you can ask, what is your modern slavery statement? And then, so now you have all these responses back, then you can actually use Gen AI to say, Okay, let's look across all of those so you can index them and ask questions to understand what they are. And then he even took it as far as there's new technology coming out where you can actually have an app that will do like a virtual reality of the different factories and locations where you can then have the app in Gen AI start to narrow in on different things within the factory, which previously you needed multiple people to go on site to do that and do it manually. So there's like, there's so many different pieces, it's a tough question to answer. But there's, it's a, I guess the main theme that I'm seeing is that without AI and GenAI, this is all a very manual process. So you can only do parts of it, and you can only do it for a certain amount of your purchases. But as you start to bring in AI with human assisted, you can actually do it across a significant amount of, like, more purchases, and you could get much more in depth on the data side as well. So, long winded answer, but it's, it's, it's kind of been a cool kind of evolution that we've been seeing.

Tom Raftery: 9:26

Sure. Sure. And can you talk me a little bit about some of the other examples, because you said you'd done a bit of research for this and you'd come across some interesting examples. So that's example number one.

Kevin Frechette: 9:39

Yep.

Tom Raftery: 9:40

Talk to me about some other use cases for AI in procurement.

Kevin Frechette: 9:44

Yeah, so like, like a large mining company we work with. They wanted to do reforestation reforestation of different locations where they've had a heavy impact on the environment. So, what they've done, is they've used Gen AI to say, okay, like, let's start to identify across all of our different locations where we could have the biggest impact. So look at where, like, from even like demand perspective, they've then said, based off that, how can we then set up and run events at scale and bring in the right local suppliers or local businesses that can help with that. So right now that they're checking off the box of not only working with local businesses, but also kind of giving back from an environmental perspective. So that's been a cool one. We had another one that, like, the main theme that they want to, to really leverage Gen AI for is to make it easy to do the right thing. The right thing being follow their ESG policies and procedures. Because right now, you have an end user, like, they have enough on their plate to, like, go figure out, try to keep up to date with everything that the company is kind of putting together for ESG. So what their whole view is, is if you can have a prompt that you allow the end user to type in what they're looking to do or what they need and then make it very easy for Gen AI to understand the context of what they're looking for, the policies and procedures of how to source it or buy it, along with your ESG policies, you can actually make it very easy for them to do the right thing and go through that process. So that's kind of been a cool that I do think is a very, very applicable one for most people. It's like, how do you make it easier on the end user to follow your policy, because usually it doesn't happen not because people have ill intent. It doesn't happen because people have enough on their plate. what, what are your thoughts though? I feel like you've been doing, you've been talking to some different AI people within sustainability. I guess what's in, in specifically sustainability and procurement, what are you seeing as like the one or two biggest trends?

Tom Raftery: 11:27

it's, all over the place. It really is. Some of the more interesting ones I came across, I guess, were ones where it's used, where they're using computer vision as opposed to Gen AI, but they're using computer vision for QA, for example. So that, that's a, an obvious one that's been around for a while, but it's a particularly good one. You know, you can, your, your computer vision can look at whether it's things coming out of casting presses, you know, and, and look at those and see defects much faster than a human could and much more accurately. I've seen railway companies deploy computer vision as well on trains to check the quality of the tracks as they're, as they're going over them or on tracks to check the wheels as they're going over them. Things like that. Also. I was talking to a guy from BDO and he was talking about a use case in the health and safety area where, for example, they can tell if employees have got all their safety equipment on or not, just again, using computer vision, or if they're stepping into an area where they're not supposed to or, you know, all these kinds of things. There was one use case he talked about in particular in an iron smelting plant where they'd had an accident the year before where an employee had actually tripped, and fallen into a cauldron of molten iron and kaput, that was the end of that employee. So now they're deploying a system using Vision AI to deploy nets in the event that they see someone tripping and falling to make sure that they don't actually. So, you know, there's, there's all kinds of ways it can be used. Procurement is an obvious one to your point. There's hundreds and hundreds of examples I've come across. I got to say throughout the, the, the, the many episodes of the podcast I've done, but those, those couple of ones stuck in my, stuck in my mind.

Kevin Frechette: 13:16

Yeah, those are wild. I mean, and those are all things too that like it's, some is, how do you make people more efficient so you don't have to have someone go look at the tracks to your point or the tires? What's interesting a lot of your examples came back to safety

Tom Raftery: 13:28

Yeah.

Kevin Frechette: 13:28

Which came back to risk into like actually taking care of employees and humans which is awesome because I feel like that's where it actually has like like there's a lot of different impacts a lot of ways you can slice it But when it comes to like actually helping people in terms of from a health perspective and safety, it's one that honestly we don't we don't see it as much in our daily world because for us, it's more about that sourcing process. So are we actually asking the right questions? But that being said, we see it as if you're asking the right questions, if you're doing the vetting and once again, not doing the vetting at the very end where they've already decided on what supplier you want to work with. Okay, now let's go. Just make sure we vet them out and they follow our process. But if you do it up front and you have that data and you can see what their policies are, like how they're set up from the ESG perspective, You can actually have that be part of your decision process, which is like, it's kind of a novel thought where usually a procurement's thought is coming at the end just to validate, okay, like, let's check the box. As opposed to actually enabling that end user to actually make that decision and give them the data. But it's like what Haptic Group calls it in our space, it's like decision automation. So, like, it's not autonomous, you don't need to give up control, but let's give people data to make the right decisions. I would make the argument over time is, that could be autonomous. Like, you can automate that over time and just have humans assist it and jump in by exception where it's needed.

Tom Raftery: 14:45

Yeah. I mean, the ideal scenario for procurement is one where, you know, you have a list of suppliers, you're going to tender for something and you say, okay, this is my financial budget. This is my carbon budget. Look out amongst all the suppliers I have and see who's going to give me the best deal.

Kevin Frechette: 15:01

Well, and there's that's a great point, where it's, it's not also single threaded, where sometimes people think of it as polarizing a little bit, where, hey, if I want to work with an ESG supplier. I might pay a little more right now up front. Long term, you'd hope that that supplier becomes more efficient over time because of their practices, their cost goes down. But in the short term, and I see it less actually on the sustainability side, I see it more on the diversity side. Where someone wants to work with a women owned, veteran owned, like my area of business, or a local business, they think, oh, we're going to have to pay more. But in reality, like if you actually look at the data and we've done millions of sourcing events, that's not the case at all. Typically they, the diverse supplier or local business is more aggressive from a price point perspective. But it's difficult to get people over that mental hurdle if you don't bring data to them. Like, like that's where data speaks and you can show it. And we see that though, where like even companies like BP, who we work with, they made this huge push towards working with more local businesses as well. And it's not, it is to do the right thing. There's a lot of obviously like business benefits and advantages of it. But it's also because it's like a strong business move economically as well. So it's I feel like we're starting to see that shift. But once again, you have to bring data because otherwise people will fall back. No, like I know the deal, like we always pay more, whatever it is. And if you don't have a way to disprove it, and the only way to disprove it without technology is to throw a ton of humans at it and people at it to go do the work and bring out the data. Then that project gets deprioritized because there's something else that's urgent or pressing more than this ESG initiative. What's your take on in terms of sustainability and diversity, do you think we've crossed that point where it's less of like, lip service and that, like, the majority of companies have leaned into it with a real why and, and, like, have rallied the culture around it or is it more lip service for the majority of companies?

Tom Raftery: 16:42

That's, that's an it depends answer I gotta think. It, know, it depends on where we're talking about. It depends on which kind of industries. It depends on. I would say possibly in some regions it's lip service. In some regions it's not even looked at. In some industries as well. So, very much it's an, it depends, but I think, I think it's one of these trends that's not going away. And so the ones who may not be looking at the moment are the laggards and the ones who are, you know, doubling down on it are the leaders in the space who will benefit from those results and have a competitive advantage over those laggards.

Kevin Frechette: 17:22

So I fully agree. The leaders and laggers like mentality is a really interesting one. And typically, no matter what space you're in, that gap starts to grow and it grows to a point where it's like insurmountable over time. Like you just can't catch up and leapfrog. We see a similar trend in AI and Gen AI, where it's like companies that are waiting too long to start to enable Gen AI on the platform, because realistically, we're in a one of nine for Gen AI, but you need to learn along the way with customers, and then you get to a point where you're halfway through, and it's going to be way too big of a gap to make up. I do think the exact same thing with ESG, and I agree so I, I personally don't think that it's crossed that point. I think there is a lot of companies that you have a couple people, you have a couple teams within the organization that really care about it. And then you have the market report or you have the quarterly earnings where they talk about it. But I think if you like ask a lot of the organization, yeah, that's like a nice side project for us that we should do the right thing. It's not, here's the why. But I, I think that the companies that are doing it the right way, and there are a ton they, that gap is going to continue to grow. And then as ESG continues to become more and more relevant and more and more. Hey, like this is a standard. It's not like a question or hey should you do it and it's a standard not just from like a like a social perspective but also you see it with the rules and regulations that continue getting hiked up in terms of like what you need to report on. Like what your processes need to be. It's just gonna be this huge gap, which once again, it's good It's good for the companies. It's good for their business, but it's also it's good for like the world

Tom Raftery: 18:48

It's probably where sustainability was back in 2008, 2009. So at that point you had some of the larger companies releasing PDFs of CSR reports, and that was kind of best practice. And now, you know, now we've gone way beyond that. And I guess D&I is coming in there at about that kind of, that kind of stage now. So it, it will, hopefully it won't take as long for it to become kind of default, but it is still very early days for it. But going back to AI and Gen AI, what are some common concerns organizations might have about adopting it in procurement?

Kevin Frechette: 19:30

I mean, there's a lot. And, and, like, just I'll delineate AI versus Gen AI. Because AI, you are training algorithms that are running on data or the compute layer, and you have an application on top to give you a predictable outcome. So that's like AI, in a nutshell. Gen AI is, you're, you're running on the underlying data or compute. Those are large language models, so billions of parameters. To then give you unique and like creative, responses or outcomes. Then you have the application that sits on top. So from an AI perspective, I think that we're kind of over that hurdle of like, okay, are people worried about AI? Because Gen AI has taken all the focus. And from a Gen AI perspective, the concern that people have the main one, I guess there's a couple. One would be the data security side. So it would be, is our data being used to train an external model? And then that's our company's sensitive proprietary information. It's training an external model, that gives away trade secrets. Obviously that's a non starter, you can't do that. Even as our data is stored by a third party external like provider, that's usually a non starter as well. We don't do either. So all the data is our customers data. The next thing that is an interesting one that is like a double edged sword when it comes to Gen AI is Gen AI is reacting to the underlying data that it's trained on. So that underlying data is a lot of times like a massive, massive data set of what's on the internet as well. So, there's arguments of like, like, does it have bias, which it absolutely does. It's trained on the underlying data that it's, it's It's looking at. So like the double edged sword here is humans have bias too. So what's better or worse? Because when it comes to ESG, human bias may always go back to the same suppliers. So they might have different views or personal opinions based off their experience of who they want to work with that might not be the best from an ESG perspective. Now, Gen AI could have a bias as well. You could fine tune that. So you could use RAGS or Retrieval Augmented Generation or fine tuning from an LLM to then say, alright, I want to fine tune to make sure it is doing what I want it to do, like prevent hallucinations and to make it less biased. But there still is that element. So like, that's something that I think will come up more and more, which is interesting. And then people are also just scared of the unknown. So they're scared of the AGI of like the Terminator. Which is fair, like down the road, that could be the case. We talked about Amara's Law earlier. We're nowhere near that. Like, we're not even close. Like, these are still just algorithms. They're just trained on massive data sets and can, like, have more human interaction, which surprises people, which is why GPT took off. So I, I do think there is that concern, and that's where, like, we use the term AI powered sourcing and autonomous sourcing. Autonomous sourcing for some people, like tech companies that, like, high growth tech companies we work with, they love it. Autonomous sourcing for a Fortune 500, it's terrifying sometimes because that's essentially thinking of us as like the Tesla for the procurement industry. But but some people don't love Tesla. They don't want to give up control and take their hands off the wheel, especially if you're going around like a, it's a wet rainy night and you're going around like a crazy turn. So people are definitely scared of losing control. And that could be control from a risk perspective or it could be control from their jobs. Because if people have been doing the same job for 15, 20 years, it's very tactical work, it's stuff that can be automated, and Gen AI can replace, then they have that concern. I would say, the same thing happened with computers, where everyone thought computers were going to take everyone's jobs. That didn't happen. It just created new jobs and made people more efficient. That's where I think this is going as well. Just at a much, much faster rate than the computers to now. I think Gen AI in the next 3 or 4 years is going to be 10 to 20x what it is today.

Tom Raftery: 23:25

Cool. Cool. And where do you see this all going? What's kind of the future? What innovations on the horizon that could further transform procurement?

Kevin Frechette: 23:35

I do believe that, a lot of people focus on AI and Gen AI for their business. So for the enterprise, so for procurement teams or for supply chain teams or whatever role you're in. What you don't hear a lot about is both sides of the marketplace. So more AI and Gen AI that are being given to buyers and to suppliers or to your supply chain team and the people that you operate and your partners. So I do think that in the future state, there's going to be a really good harmony in terms of providers that can have strong Gen AI that are kind of like autonomously negotiating with each other, sharing information, collaborating. I think that is definitely the future, because then you have people that are saying the controls of how do you want to operate, what do you care about from a business perspective. On the, like, procurement side in our world and on the supplier side. So I think that's really interesting. I think multimodal is really interesting. You kind of brought it up a little earlier. So that's not just looking at text. So looking at text like visuals, audio, everything like that. I think that is, and you actually did a podcast back in the beginning of May. About like voice and speech about helping different people be able to talk in different countries. I do think that it's just a further, that's one example of just like a further bringing people together. It's it's standardizing the process and standardizing how you view different suppliers, different partners, different regions, which ultimately is a great thing. Because then what we're essentially doing is you're leveling the playing field, which in the ESG world, like, that's how it should be. You have a level fair playing field, you have access and opportunity, and then you make the right decisions for your business and the suppliers make the right decisions for them. And a big piece of that is language barriers. It's one of the, one other example that you brought the idea of like in factories. I think that's a huge one in terms of being able to recognize different security or health risks is a big one different inefficiencies in factories or in different kind of jobs. And not having humans look at the video, but having Gen AI surface, here's some thoughts based on all of our training, based on all the data we have. And then you have humans go in and they're taking actions on those decisions or thoughts. So, like, once again, the whole thing shifts towards people doing different work and being more productive in the work that they're doing. I think that is the key theme you're going to see across the board. What are your thoughts?

Tom Raftery: 25:42

Yeah. No, I was just thinking as you were talking about that, I was just thinking I had a recent example here at home. So my younger son is just finishing second level in, in schools. That's the equivalent in America of high school. He's just finishing up getting ready to apply for universities. And he had to fill out this form yesterday morning and we live in Spain, the form was in Spanish. He was looking over it and there was some terms he didn't understand, not because he doesn't speak Spanish, he lived here all his life, speaks it fluently, all his friends are Spanish, but because it was bureaucratese and so he was looking at it and he called me and I didn't understand it either. So I had my phone with me. I opened up the chat GPT application on the phone and I spoke to the phone. I spoke to chat GPT in English and then said on this particular form, on the Junta de Andalucía's website, form Modelo 06, and I started reading out the words in it that we didn't understand in Spanish. So I was speaking to it in Spanglish. And then I said, could you explain what those terms are? And it replied to me in English, switching to Spanish for the words and then give me the explanation back in English. So the, the switching between languages mid sentence would normally be very confusing for a computer, humans less so if you speak the two languages, but ChatGPT had zero problems with that. So I think breaking down to your point, breaking down the, the language barrier between people is, is it going to be a huge, huge boon, I think for organizations.

Kevin Frechette: 27:17

Yeah, I mean, outside of the world of procurement, completely separate, I have an example like you have. I got strep throat about two and a half weeks ago. It sucked. It was bad. But that being said, so like, I had a cool output from it. I went to urgent care. And And there was someone at Urgent Care that was next to me that they were trying to, like, get an appointment and there was a massive language barrier for the person to be able to get the appointment. So I, honestly, I tried to do that on my phone. I actually had trouble doing it because I have the GPT 4. 0. Because I thought I had seen the demos and I, like, I actually, it wasn't as clean for me in terms of being able to help out. But I could see where that use case, and it's obviously one, but I think it goes back to use cases where Like, yes, there's always going to be cool business applications, and that's going to continue to grow. Massive values can be generated. I think the way that the whole world shifts on their view of Gen AI is for things like that. It's for things like safety. It's for things that people can associate with, like, themselves and say, all right, like, this is actually helping. This is better for humanity. I think that's when you'll see that inflection point of, like, holy shit. Like, this is a game changing technology, and it's not crypto, it's not this bubble. And I'm not saying crypto isn't, I know it's having its moment right now. I think that, I think, I shouldn't even say crypto, I should use the word blockchain. Cause I'm still a blockchain fan, but I just think that it hasn't hit real life applications in terms of changing the world. I do think Gen AI will be that.

Tom Raftery: 28:36

Yeah. Yeah. Yeah. Quick left field question for you.

Kevin Frechette: 28:40

Yeah, sure.

Tom Raftery: 28:41

if you could compare the evolution of procurement technology to any sci fi movie or series, which one would it be and why?

Kevin Frechette: 28:50

Oh, man, what a great question. Procurement technology to any sci-fi. I'm not even a big sci fi fan. Give me one second. You know what? I like that. Yeah. No, I gotcha. I gotcha. I'll give you one example. This is probably a horrible example, but I love that you're putting me on the spot. So I would say that the, the example I'll give once again, might not be relevant would be, movie Back to the Future. It was big when I was a kid. So it was back in like the 1990s. They were talking about, I think they were talking about like 2020. And it was talking about the future of what 2020 is going to be. And

Tom Raftery: 29:21

it was 2015 even. I don't think it was even this. Yeah. I think it was 2015. I It was 80, 85 to 2015 and 85 to 1955 were the two jumps he made.

Kevin Frechette: 29:33

Got it, got it, yeah. Amazing movies. Like, absolutely loved them. My brother was a huge fan, my older brother, so that like made me like want to like it more. So like the fact that like the future state it like it came so fast Like you were watching it and then you're like, holy shit. Like this is 2015 That's this is in two years and then you see it's like, you know what? There are some cool parts of it like the hoverboard we don't have right now But there are some things like you see on water but like what you, what I realized by that is there's so many additional things, even like the AI, Gen AI, I said that like you are true now that it couldn't even predict. So it had nothing to do, like there wasn't even a lot from like an internet perspective from like, like there was, I don't think there was any robots, which I know like, like from that perspective, you expect maybe there'd be robots. That's like obviously a big push like Tesla's even thinking about now is one of their big bets. The robo taxis is one of their big bets coming up. So I guess the main point I'm making is. Like even the future like it could think of hoverboards like that was like the main thing like holy cool And it was a jacket that air dried itself when Marty McFly fell into the water and that was cool It's like well, you could have a jacket that does that but I guess my point is like we don't know what we don't know. Even from a procurement perspective where once again, we're still so early days and what this could be that it's impossible to predict what it's going to be in 10 years. So the only thing that like we can do is just adapt and react in real time. And to even keeping it outside of procurement and like, AI, even on ESG, we don't know what it's going to evolve into. So you just got to keep going with that wave and that trend, because then when it does come up, you're ready to adopt it. So not a perfect response to your question, but I do love the question.

Tom Raftery: 31:03

Okay. Good. Good. Good. For people starting out on their AI journey, what advice would you give them?

Kevin Frechette: 31:10

Start small. Don't go for a big swing. You, you can kind of map out your different AI opportunities. And that would work, find a couple suppliers that are partners that can help you brainstorm. Okay, here's the art of the possible. Here's different things we can do. You can map out what's the level of impact and what's the effort. And then you can start to say, all right, like, what are my first couple of bets I should be making? Because ideally the first couple of bets you make, they're just like, they're quick wins. They're little quick wins. You can show that, demystify it. You can kind of show that, okay, we did this, this, this. You do want to have the roadmap of where it can go in the future. Because if not, these little wins might actually demotivate people like, you know what, that didn't do too much. Maybe it's overhyped. But if you can show here's where it can go in the future, and then you show these little wins, you build up that internal political capital to then get your next win and your next win. I'd say the other one would be, like, find the partners that you want to go, go along with. You can't do it with everyone. Everyone's talking AI. I'm sure everyone listening to this has gotten a million emails in the last two years on AI and Gen AI. So, the, my advice would be, find a company that you can say, alright, like, I understand where the company's going. I, I like their rate of innovation. What they're providing can service some of our short term goals, but I could actually partner with them to go on the journey with them. We've seen that, once again, with, like, the largest companies in the world, we work with a lot of Fortune 500s, and that's their view for us. It's, like, they don't know where exactly we're going. We have a roadmap, we've talked about it, but they just want to more go on the journey with us, and because of that, we lean into them and we give them a very high level of service, because we know that they are helping us kind of drive that future state of procurement. So, that would be the main two things. And, and be ready for push. Be ready for pushback from your organization. Because once again, legal, IT, different people. If they don't know it, you need to demystify it because what you don't know you're scared of. In a lot of cases it's not always, I'm curious to learn more. It's sometimes like throw up the wall.

Tom Raftery: 32:57

Right. Okay. No doubt. No doubt. And for people who may not be starting out, but are further along in their journey, what advice would you give them to help them stay ahead of the curve in such a, you know, rapidly evolving industry?

Kevin Frechette: 33:13

Yeah. I'd say. You just gotta keep learning. That's the number one thing. Just keep, like, finding ways to get more up to date information. And it would be on the overall space. So, just making sure you fully comprehend and understand, and I'll talk more about, like, Gen AI right now, like, who the different LLM providers are, where they're going, what's the advantage of different models, what's the advantage of using, like, a public provider versus building a private. Like, where could that go in the future? So just really knowing that, but then also networking with other people that are a little further in the journey than you are. Because you always want to talk to people that are a couple steps ahead, and usually those people are the ones that you see on podcasts, the people that you see at conferences. And I'll tell ya, they love talking about it, because that, they're like, they're betting their career on it right now. So they're typically very open and excited to brainstorm with other people to get involved and help the community. Cause like, that's really what it, what's happening right now. As you're having this, you brought leaders and laggards. You've seen this community of people that are leaning in, that are the leaders in it. And like, that is such a good and cool group to be in. Not because like, oh, cause it's cool, but it's because they're driving their businesses forward and they're setting their businesses up. The laggards are the people that are still like, like skeptical. It's okay to be skeptical, but skeptical if you're eager to learn. If you're skeptical and you're not eager to learn, then like you're, you're doing probably yourself and your company a disservice.

Tom Raftery: 34:35

Fair. Yep, absolutely. We're coming towards the end of the podcast now, Kevin. Is there any question I didn't ask that you wish I had or any aspect of this we haven't touched on that you think it's important for people to think about?

Kevin Frechette: 34:47

Yeah. No, honestly, we hit on a lot that I was thinking about. I'm just going to go back to my, to see if I had anything else from my examples. No, I mean, I, there's a lot of, I guess, one final, like, point that I think people might be reducing the barrier to get them to start is we, we start working with a lot of companies that they, they don't know the current state of the state. They don't know how they're doing today from the ESG perspective. So almost that, like, unknown is a barrier to get going and start. But what's very interesting is we work with a lot of companies, so we're typically helping them do tens of thousands of sourcing events. We help them report on it. We help to make sure we're bringing in outside data sources to recommend the right suppliers. There are a lot of them being ESG, to then see how they're winning business, to create programs around it, to say, okay, how do we better engage with their ESG suppliers? What's shocking is a lot of companies are actually doing better than they thought just by like just by doing their normal business So like it's like some have been very very surprised by the fact that they're actually they're actually like not starting from zero if it's a one to ten They're starting from four or five and a lot of times that's a cool motivator where we have one financial services company a very large one we started working with them. They now have a way to structure all the data. They have a way to report against it. They can see all of it. And on 80 percent of their events, they were actually inviting ESG suppliers. So now they brought that back to the ESG team. And that team was absolutely thrilled. So then what that did is they brought that to the CEO and then they said, cool, how do we accelerate this program even more? So then procurement very much went from like this back office. People were doing quoting in our world sourcing. So they were quoting manually through emails, through phone calls, whatever it is. They digitalized it and they amplified it with FairMarkit. And then they were able to report back and I'd say like we helped, but in that situation, they were already doing it in a lot of ways. So we were just able to help highlight and showcase it and it made them more strategic as like a department versus being a past back office function.

Tom Raftery: 36:38

Nice. Nice, nice, nice, cool. Kevin, if people would like to know more about yourself or any of the things we discussed in the podcast today, where would you have me direct them?

Kevin Frechette: 36:47

LinkedIn's great. So just Kevin Frechette on LinkedIn. And to be honest too hopefully this didn't come across in any way as like a pitch for FairMarkit. It's, I'm just really intrigued to learn what people are doing from a Gen AI perspective, AI specifically around procurement and then ESG as well. It's like, like, how do we think we can move it forward? Because we're constantly evolving our roadmap. We're a very agile team. Like we move very quickly. We don't thrash, but we do, we're very open to figuring out from a roadmap perspective, what can we keep doing to make sure we're staying up to date with the trends? So even if someone wants to jam on some different ideas and brainstorm, I'm always open to it. So Yeah, LinkedIn is the best way

Tom Raftery: 37:21

Fantastic. I'll put your LinkedIn link in the show notes so everyone has access to it. Cool. Great. Kevin, that's been fascinating. Thanks a million for coming on the podcast today.

Kevin Frechette: 37:29

I appreciate you having me. This was a blast

Tom Raftery: 37:32

Okay. Thank you all for tuning into this episode of the Sustainable Supply Chain Podcast with me, Tom Raftery. Each week, thousands of supply chain professionals listen to this show. If you or your organization want to connect with this dedicated audience, consider becoming a sponsor. You can opt for exclusive episode branding where you choose the guests or a personalized 30 second ad roll. It's a unique opportunity to reach industry experts and influencers. For more details, hit me up on Twitter or LinkedIn, or drop me an email to tomraftery at outlook. com. Together, let's shape the future of sustainable supply chains. Thanks. Catch you all next time.