What It Really Takes to Future-Proof Your Supply Chain

"If you're not doing it now, you're really far behind." — Blake Tablak

In this Trax LinkedIn Live, Blake Tablak, CEO of Trax Technologies, joins the conversation to talk about what future-proofing a supply chain requires, beyond the industry buzzword. He covers where AI creates real value, why most companies are overweighting headcount reduction, and the data distinction executives need to understand before they can trust what an AI system tells them.

About This Conversation

Blake sat down for a LinkedIn Live discussion following his appearance at the American Supply Chain event, where future-proofing supply chains was the central theme. The conversation moves through where AI is accelerating decision-making today, why quality and throughput matter more than headcount cuts, the difference between a system of work and a system of record, and how Trax's Prizma.AI platform fits into that picture.

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Full Transcript

[00:03] Host: Hi everyone, and welcome to the Trax channel. Today I am here with Blake Tablak, CEO of Trax Technologies. Hi Blake, how are you?

[00:11] Blake Tablak: I'm wonderful, thank you. How are you?

[00:14] Host: Good, good. Summer's always fun, with the kids home and work going at the same time.

[00:15] Blake Tablak: That's it, the kids are home. Good daycare helps. I'm already thinking about when school starts back up, and then you get a little panicked about everything that has to come together to get ready.

[00:37] Host: I know. Of course, then they go back to school and you kind of miss them. The simplicity of summer is nice too. So today we're talking about future-proofing supply chains with AI enablement. Recently you were at the American Supply Chain event, and the theme there was future-proofing supply chain. What does that actually mean in practice, beyond the buzzword?

[01:08] Blake Tablak: Yeah. So I actually don't even call it future-proofing. I call it now-proofing. If you're not doing it now, you're really far behind.

There's two things AI has brought to the table in the last year in terms of acceleration. If you're an executive running a team, there's process automation. That's become far more effective. You can do far more complex workflows. And if you're in logistics or transport, you're under heavy pressure to reduce costs, that's the truth.

That said, it turns out there's more money to be found elsewhere. This is where I think the bigger asset is: the rapid ability to analyze information. As an executive, if you're spending all your time thinking about how to cut headcount, you're missing out on the actual big dollars that exist.

A good example: one of our clients does half a billion dollars in freight spend. The total number of people supporting that, even if you got rid of half of them, would pale in comparison to looking at service shifts, consolidation and other things, which, by the way, you can analyze in seconds, not days and months, and have to go get a professional and a consultant.

So with the two assets, one is process automation, which is great and everybody should be looking at it. But the analysis of information and the output is far more powerful, far more important.

[02:34] Host: So what's one capability companies need to build now if they want to stay competitive over the next few years?

[02:41] Blake Tablak: Your knowledge and understanding about how data works would be number one. And two, how you actually use artificial intelligence as a firm.

Your data doesn't need to be perfect, but it needs to be organized, and you need to know where it is. I talked about this at the American Supply Chain Conference: as an executive and a leader, you need to understand the difference between a system of work and a system of record. This is huge when it comes to understanding how to use artificial intelligence.

A system of work is a system where you are doing things, which means the information in it is constantly changing. Go to your CRM sometime, run a pipeline report, run a bookings report, and give it a time. Run that same report tomorrow, the next day, you get a different result, because things happen in that platform. That's a system of work.

If you go into the ERP and run what you're booking as revenue and expenses, and you run that again the next day, somebody's going to have a problem if it changed. That shouldn't happen. Whatever it is in your system of record, that's what it is.

Executives need to understand this because they have to know where information is coming from. If you want to know the total landed cost of an object, you're not getting that from one place. There are multiple places, and you have to understand how to get that information and which information you trust. By the way, you do not have to go get a big four firm to tell you this. If you've been around these systems long enough in this industry, you know who has good data and who doesn't.

The ability to make a decision as a human being results from your experience, which is the data you're looking at, and the remainder is risk. The unknown presents risk. If you have a line chart and you look at it and say, I have a lot of experience and a lot of data, I can make this decision with very low risk, AI is no different.

I joke that AI is like talking to a twelve-year-old with a PhD in vocabulary. Very sophisticated, but it can be very intense about a wrong answer. So I think it comes down to knowing where your data is, understanding what a system of work is, understanding what a system of record is, and picking where you want that information to come from and where you want it to reside.

[04:56] Host: So where are companies over-investing versus under-investing when it comes to preparing for the future?

[05:03] Blake Tablak: Number one, I think companies are overweighting toward headcount reduction. I really think they are.

Go back and look at Kaizen. Go back and look at all these things that still exist today, and what you see is quality and throughput. The two most important assets we have are quality and throughput. If you can increase throughput and increase quality, inherently you can reduce cost.

But if all you're focused on is automating workflows, you will do that, but what you'll miss is that the person who isn't doing that work anymore, that you may have let go, had an asset, or the function had an asset, that actually improved performance, and now that's gone. We see this all the time: "I'm going to use an agent to get rid of this workflow." We actually don't talk about it that way internally, even with our clients. What we say is we have agents constantly monitoring things in the background, making decisions for you, but it's focused on quality and throughput. Ultimately, a bigger pipeline and a higher-quality asset coming through is going to result in lower costs than you're in for sure.

I think people are way overweighting toward headcount reduction. Once you realize that quality and throughput matter more, you'll have opportunities for operational efficiency and headcount reduction to follow. First it's how do I get the object there better, faster, cheaper, intact. That's the number one thing we all get paid on. I think that's probably where people are overweighted, and I think it's a little bit dangerous.

[06:34] Host: How should leaders be thinking about balancing efficiency today versus resilience for tomorrow?

[06:38] Blake Tablak: That's a good follow-up to what we just talked about. There's a really good opportunity to take on more as an individual. For me personally, I can actually take on more work, I can do more innovation, I individually can do more as a person, and that's really different.

When you think about resiliency and efficiency, again, quality and throughput become a great measure. Cost, quality, effectiveness, and how much more of that can I do. If I had ten people today and I was solely focused on, well, if I cut five, I'm going to save a million bucks, great, awesome. But what if those ten people could do the jobs of forty people, and all this other stuff I couldn't get to before, now I can, and the result is a hundred-million-dollar cost reduction. The result is a wildly more efficient supply chain that moves goods from A to D faster. I can generate more revenue, faster, because I can make decisions quicker.

Every CFO's dream is to have teams that can operate that way. So I think when you start balancing resiliency and efficiency, the quality and throughput measure really gives you both.

[08:54] Host: So where does AI play the most practical role in future supply chains right now?

[08:59] Blake Tablak: It depends on who you are, obviously. I'll talk from the logistics team, because that's largely where we spend a lot of our time in transport. If you're in logistics, you're under pressure to reduce costs, but you're more under pressure to deliver on time.

What I would do is pick two or three use cases that seem impossible for you to get your head wrapped around today. Service shift is a hard one. You start looking at all the packages you're sending all over the world at different points, at different times: am I using the right service level to get there? It turns out if you had somebody on your team take a couple of minutes, you can probably figure this out. In our platform, you literally click a couple of buttons and it tells you these services between these zones, don't bother using them, because they get there at the same time as a lower-cost service. There are things you can figure out today that achieve the end goal, which is get it there fast so I can recognize revenue, but at the lowest cost, the most effective rate possible.

Another good one is starting to think about your carriers and other carriers. Most of the time, procurement is only limited to that which we can see. I know about these carriers, so I'm going to bring them into the RFP. There are fifteen thousand unique carriers in our platform. There's no way you know all of them. But the question is, is that data set available, and can I start to think about it in terms of cost, quality, speed and efficiency. Who's best at this lane? Where do I have single-carrier risk? All of that is really easy to do now.

I think when you start thinking about AI, start at the end. What's the goal I would like to accomplish. Don't start at the beginning, worrying about how complex it's going to be. Start at the end, and you will figure out how to get there. It needs to be on a coffee mug: start at the end, and the rest will follow.

[10:12] Host: So how does Prizma.AI support the idea of future-proofing? What does it enable that wasn't possible before?

[10:14] Blake Tablak: When we first started thinking about what we wanted to do as a company, and this predates me, it was all lanes, all modes, all currencies, all countries legal to operate in. That was a founding principle of the company. I feel ever grateful to the founders of this firm that they made that decision, because it's hard if you don't start there.

The reason we call the platform Prizma is that in a prism, white light comes in and a great array of color comes out the back end. Think about it as we're ingesting plain documents, like bills of lading and invoices, but what's coming out the other end is a constant set of adjustments that are possible for you to make. Simple things like, hey, you're using overnight AM and PM between these locations, stop, use PM, get there at the exact same time. It's really easy, and nobody else is doing that for you. The platform is doing that for you. Hey, you've got single-carrier risk in these lanes, here are twenty other carriers that do that at better quality and potentially lower cost, you should consider them.

Prizma is designed to give you a different view of the world. I say to most of our executives, don't look at it and say, well, I don't see it, it's not in there. One of the great parts about Prizma is whatever question you have, the data can be constructed in such a way to give you the answer.

Prizma is also designed to export its information into systems of record. We are a system of work, and I'm very clear about that when I talk to our executives. Your inventory systems are systems of work. We are a system of work. When you start to combine that information together, you do that in a system of record, and that's where you're starting to keep track of historicals. That's where the real power comes from. Now you have an integrated system, and that becomes wildly powerful for people.

So Prizma really does two things: it gives you the ability to analyze things very quickly, and it also moves that data from one system to another in a structured fashion. If you're a large-scale enterprise, that's what you're trying to do, twenty-four hours a day, seven days a week.

[12:29] Host: So the last question is, for you, is there anything else you'd like to add? Any new trends, insights or observations you've picked up recently, especially from events or conversations with industry leaders?

[12:34] Blake Tablak: Maybe not picked up recently specific to this, but I was old enough that I was around for the mainframe to distributed movement, distributed to SaaS, SaaS to AI. One thing is constant whenever there's a ton of disruption: if you are terrified and hold on to the thing that you thought made you valuable before, you will get clobbered.

I remember my father telling me, be careful what you ascribe value to, because the thing you ascribe value to, you will protect. Now there are obvious things, your family, your faith, you should always ascribe value to that. But when it comes to your work output, be careful. Because if before you thought your value was in really understanding how to make logistics work and move objects from A to B, that's changing. Don't get me wrong, the output still has to remain the same. But as a leader, become more comfortable using solutions that involve data. Become more comfortable in your data and know what's possible. Don't let that be a gray area, because your team may tell you what's possible, and one of those reasons could be that they don't want to lose their job. They may tell you things that aren't necessarily accurate, and again, they're not trying to hoodwink you, there's just a lot of emotion, because the more you know, the more you can empower your team, and the more you know, the more you can actually go do yourself.

My grandfather was sixty-seven when he learned how to code. He had been an accountant, he had been a CFO, and at sixty-seven years old, his son started a software company and he said, well, I'll learn how to code. And he did. There's nothing in your life where you can't go learn something new. This is a pivotal moment where billions, if not trillions, of value is about to be unlocked. If you're on the back end of that, it's going to be awful. But if you embrace it and realize the value you used to provide for a company is changing, you will become the center of the universe for that company.

So I'd really encourage people to stretch themselves a little and start thinking about new, creative ways they might add value back to their organization.

[15:03] Host: Sound advice. I definitely think continuing education, especially in AI and any field you're in, is paramount to your success. Well, this was such a great conversation, Blake, thank you for joining me today. We'll make these a regular thing.

[15:09] Blake Tablak: Thank you so much. Great to see you.

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