Hey, everybody. It's Patrick Escolas with another Banyan Technology, Tire Tracks Podcast. Joining me today is Lizz Harrell of Parade. How you doing, Lizz?

I am doing fantastic, Patrick. Great to be on.

Hey, thanks for joining. Lizz is special. She's so special. They had to add an extra Z on it. If you're writing Liz with one Z, it's not her. No. Is there a reason for that? Is there a story?

Oh, gosh. What a zinger for the first question? I call it double Z, double zeal. No, it's really funny and I know we're going to talk a lot about AI and data today.

Yes.

Very pattern-oriented.

Okay.

When I was a kid and started writing my name out, you'd see H-A-R-R-E-L-L. After each vowel, you have two consonants.

Okay.

It's like, I had to add the extra Z in, so it's like, now it all matches. L-I-Z-Z-H-A-R-R-E-L-L. The pattern.

That's awesome.

It all fits.

You said a much better thing, than when I was in school, I had to write my full name, Patrick, because if I wrote Pat, my parents were afraid that SNL skit was too popular at the time. I don't think anybody in any of my classes had ever seen it, but I could not just write the three-letter nickname. I had to write the seven out. It's like, come on, guys, you're killing me.

It's incredibly funny how our parents fears our works. My mom's name is actually Beth and my grandmother named her Beth, because she was terrified that people call her Liz. It all comes full circle, right? There you go.

Now you’re Lizz.

Of course, hates the name Liz and there we go. I got to school and I was like, could not wait to go by Lizz. Yeah. I guess, that's right.

That's fantastic. You're the SVP of Customer Service at Parade. am I correct with that?

That is correct.

All right. All right. As I always ask, who are you, Lizz? What do you have to do? No, no. Don't worry. We won't get that existential, but within –

Who am I?

- within logistics and the freight and where did you come from? How did you get here? So many people I talked to, I was born in freight, whether it was in the truck, or at the manufacturing plan, watching the docks, but what's your story? How did you get here?

Yeah. Great question. I was not born in freight. To be fair, I was born in Little Rock, or I was born from Arkansas. So, I at least drove a lot around trucks, hitting a lot of lanes through Arkansas, which I know so much more about today than I did at the time.

Right.

No, I was actually, I came up through tech. I've been in technology startups my entire career. Not necessarily the person building the tech, but really helping make sure that customers get the best use out of it. Came up through the sales, selling the dream, and then moved into post-sales and then delivered on the dream.

That is the dream. That's right. You're living the dream right there. That's right. Nothing like a quote of trust there, right?

So, that's the fun part. I think I've had the chance to work with a lot of different companies, a lot from small merchants trying to sell goods and services online. I've worked with the biggest, the big banks and FinTech companies. I'm recently distanced in data working with the likes of Instacart and DoorDash and Bloomberg and everybody, basically, trying to get the most out of their data from an analytics perspective.

Awesome.

Yeah, that's a bit of my break.

Tech, obviously, going to be an emphasis for this conversation. But one of the things, obviously, I come from Banyan Technology, we’re a TMS and API provider, as well as all of the other bolt-ons. But one thing I've seen about the logistics and freight industry is that for whatever reason, technology has been slow coming to the industry. It was one thing when I started with this company three or four years ago when I was calling people and I'd be like, “Well, yeah. They got to have a system in place, right?” I'm coming, my freight background is now from a system. So many people are like, “Well, no. I don't have one. Don't need one. Bye.” What is your input as why it's taken so long for technology to come to this industry that has so many moving parts all of the time?

Yeah. I mean, I think I'll just double down on what you said there from a moving parts perspective. That's usually one of the really interesting things is there are so many moving parts. Also, I think, there are so many people, right? So much is done on with people. When you're living in the physical world, essentially –

Which we still have to. We’re not in the metaverse yet.

Yeah. We still have to. It's about getting a physical good from point A to point B. There's a lot of, I think, ways that you can think about. But ultimately, that's key strength that exists. I think oftentimes, there is, you see tech really accelerate, even take fintech and payments, right? Money is now completely digital, right?

Which is terrifying.

You don’t have to handle it. At the end of the day, if I want to get my shoes, or my jacket or man, I've got two small kids, I order a ton of stuff. I'm like, need it now, right?

I have four. The boxes are there all day, every day. Yeah.

Yeah. So, that's the thing. It's like, no matter, that's always going to be a constraint. We're still trying to get physical goods from point A to point B. There's a lot of systems and people and things involved in that. I think that's just one of the harder things. I think a lot of areas that are digitized, it's just easier because the actual good or service is technically digital.

Okay. I like that. It's a great call out. I add that to the brain tank here and let it digest. While I do that, so we talked a little bit about you, where you come from and how you arrived at freight Parade. Tell me about that. I know that they have marching bands sometimes and do you guys throw candy? What kind of a parade are we talking about?

Yeah. To tell you, I actually think the funny thing is, I think, the reason for the name Parade, as I do think like a convoy of trucks, a lot of trucks, I think exactly great.

Yeah. Like Smoky and the Bandit, you know? We got ourselves a convoy, right? Yeah.

There you go. I think that's actually where the name comes from. Yeah. Parade’s background, interestingly enough, the founders, not necessarily also born in freight, but have been together, launched the company in 2015.

Okay.

Have background in AI, machine learning, so they're true techies, true engineers, pointing themselves at a problem.

Yeah.

Then one of the founders, the problem they came or solve, one of the founders is uncle drove a truck, and so they learned a lot. They're like, wow, a lot of this seems really interesting, that who knew it happened that way, right?

Right.

How do you think about – so, they actually launched a brokerage. A brokerage is how they basically came in. Spent a couple of years doing that and then realized, you can either compete with the thousands of brokers exist. Everybody having their secret sauce, or we can give them technology. Some of the things that they caught on while working for them, but didn't have the expertise necessarily on the freight and logistics side of the house. And so, said, “Hey, we’re experts in tech. So, how do we bring some of that tech to the brokerage?”

Right. With that, you mentioned AI, which no one has ever heard about, hasn't been talked about for many, many years now. AI is everywhere. It's a great buzzword and anybody that's got a startup is going to say AI, and they just bought a ChatGPT model. How is AI being used within Parade? Because I assume it's not something as straight up as, “Hey, ChatGPT, tell me what I should get, who should I reach out to for this load?” What complex ways is it using this to get you, what I assume is a streamlined process? Or maybe it's just more intelligent data to make actionable decisions on.

Yeah. Absolutely. It's a great question. I mean, ChatGPT is telling me actually what to say right now.

I'm not real. This image is a spy DALL-E system. Yeah.

You asked the question. I'm a deep fake. Yeah. No, the funny part, I think, AI is actually – the background for Parade is it's pretty well baked in. I think at the end of the day, just email extraction. Taking, using –

Sure.

- and start processing the language coming through emails. It's really how Parade started. It's like, hey. People have all this capacity, technically, coming in the email. How do we scrape, read what's in the email using AI and then parse that into data that essentially is helping brokers who are interested in the capacity? That was basically –

That’s awesome.

- Parade. Yeah. It’s pretty cool. It's like, all of these emails go back and forth. Well, there's data in there. Instead of actually taking that data and saying, Great. I'm going to have somebody go keel this in to a spreadsheet and a database, things like that, just pull the data. That's interesting as a program. It's what they started doing. They said, “Oh, we'll start pulling the data from his emails and parsing into our systems.” That was the first use case.

Basically, Parade as capacity management, the goal is to help, your network is your net worth. Essentially, you're, yeah, you're basically taking all of the capacity. Historical data for lanes you've run, everything and helping brokers, basically find the right truck for every load. The newer use cases and can talk a little bit about some different approach about AI, too. That's a programming piece. Typically happens in the background, scraping the data, pulling it into your systems that you can actually leverage it.

Populating the screens in front of you. Yeah.

Exactly. Right. You reduce a lot of that modern data entry burden.

Sure.

Then now, what's interesting with our co-driver solution, we're now talking to carriers directly on behalf of our servers. You basically, you got your loads out there, you've got an email address carrier rights and low details, low details, right? Instead of having a person necessarily just responding, “Yeah, load’s still available. Here you go.” Capacity co-driver is doing that for folks. It's basically, responding to all those inbound emails, looking to get to price action. All of that communication can, or may not even know, nor may they even care if they're actually talking to a bot, because they're going to the information that they need to get to basically to quote, getting faster, faster of that. The bot responds at every email in a few seconds, versus having to have somebody babysit that inbox. So, it's a good experience all around. Records get more quotes and more options. That's the goal of the entire thing.

That's the win. Yeah. With that, what's the outcome there? To your point, yeah, bot or person, it doesn't matter. As long as there's a button somewhere that says, “This bot isn't doing it for me, get me a person,” that's all. What are you seeing as an effect of this AI, as you said, first, just from scraping the emails to get the data and now from actively participating in the conversations?

Absolutely. Probably, the first is just put your people where people are special, right? Or they have value add. The creativity, critical problem solving, connected to all of the different things that make humans viable, they can build those relationships, that could be more strategic, help you get basically, the highest margin for each load, right?

Yeah.

The best option, right? The best service, the right carrier, all of those pieces. It’s not necessarily all about the margin. You reduce, also, the number of activities that they're doing just related to that email conversation back and forth. The second thing that we found out is because of that speed, a lot of basically, for each load that our customers have, they're using co-driver, they're getting more quotes per load. We're literally talking how brokers go from 1.2, 1.5 quotes per load, four to five. It is just a mass amount of number of quotes. Less time wasted on back and forth on details and more getting to price action.

Then the third piece, right, is really the more quotes that you're getting, the more that we're seeing that automation of some of that digitization of freight. That's the other piece that pretty exists is automating that end-to-end workflow to try to get more things digitized from a freight perspective. We're seeing just more and more bookings and increased percentages of loads that are basically covered digitally, versus out there via phone calls and the [inaudible 0:13:04] and things like that.

It sounds like, and these are some similar themes to what I've heard before. It's allowing your key persons who are special to focus on those items that can't be automated, that aren't the bread and butter, hey, that's day in, day out stuff. I think, it's also interesting, you tapped on more quotes are coming through. One of the things, I could not remember who said it, but sometimes it's not the best quote, sometimes it's the first quote that comes through. Within AI, I think, one of the emphasis, at least from an outsider, I guess, an insider, who knows? As I'm thinking about this for all the – we'll say that there are cons to AI, or there are limitations to it. But for all those things, it spits on now quickly and it gets it back to somebody. I think that that's probably just as important as the most detailed and most accurate quote is getting the first quote.

Then speed and quality are sometimes tradeoffs. I think that's a, yeah, definitely what we're seeing too. It's just celebrating that speed. You can go win more freight and you can cover more freight. That's the vibe perk of itself.

Now, with something like Parade and the AI usage, is there a niche in that you're finding a broker with less personnel, because you're trying to do more with less? Or, you are also seeing it at the large organizations too, because, I mean, who's not trying to do more with less? But it's harder to justify the workforce you had before. There's quantitative and value to just having a system like that in the background, even if you have the manpower.

Absolutely. Thinking about the ultimate goal that more loads booked per rep per day, right? That's ultimately, because –

That's the ultimate KPI, right? Yeah.

Exactly. Your cost to cover, essentially, and so it is. Right now, and what we've heard from a lot of brokers, right? Just, again, I'm a bit of a newbie, but I learned from a lot of fantastic people who know way more than I do about all of that.

Those are all my clients. Yeah. They're like, “Patrick, this is why this works. This is why it does it. I believe you.”

I ask questions and I try to find what everyone's like, what's working for everyone, right? At the end of the day, as long as I'm listed on, I’m learning.

That’s right.

What they see is we've heard people are trying to focus on volume to cover compressed margins, people, and so it is, how do you – you're driving more volume, right? Well, you're keeping those carrier reps busy, potentially. That ability to get freight covered, and sometimes automate the stuff that's easy, stuff that you repeated.

Yeah, the no brainers. Yeah.

Yeah. Absolutely. Just automate as much of that as you can. Then focus those reps on the hard to cover loads. I think what we're seeing is, again, it's like, how do you deploy the talent that you've got? That's because everyone wants to grow. But when it comes to what you've got covering freight, put them on the best stuff, automate what you can, give them the tools to help them drive up their productivity, they'll make more money too, right? Right through incentives out there, too. Yeah. If you're crushing your goals, then everybody feels good.

This brings up a thought to me. Since COVID, maybe the onset, or the aftermath, hiring has been a hard sell just across the board, across the industry. How is AI as tools becoming an effect to help that process? I don't mean, you have an AI bot go look for who you should. I mean, you get somebody completely new to the game, and you're playing in a world where there's guys that have had 35 years’ experience, know the numbers offhand, know what lanes are good and what's bad. How does AI play into that? It's got to.

Oh, amen. Well, and it's a great question, and I'll actually respond to the specific customer story.

Oh, perfect.

Not the seat that I sit in necessarily, but brokerage. We’re talking to a customer and newer customer for Parade and they started onboarding, gosh, maybe three or four months ago. What they are seeing on productivity from their first, they have hiring classes, right?

Okay.

They're the first folks, they're really getting into parade.

Sure.

Which is pretty cool. They're starting, without the 35 years of experience, they're starting them with the tech, right? They're starting them with the tools that are bringing all the quotes and they're starting with smart matching on their capacity and trying to understand those pieces. For people that have basically not been able to bring that experience, the ramp time is so much faster with enabling people with the tools that help them guide them through that process, versus someone that comes in with the same relationships, or same understanding of decades of data living up in their head. You can fast cycle that.

I think, that's the key thing, right? That’s the hope is, as you've got potentially people that are retiring, you got to figure out, how do you maintain the quality of talent? In those cases, tech should be an accelerator for that.

Yeah. I think that to a lot of people, the, I would say assumption, or the real hope is that AI can, or AI in tech in general can close this gap of anecdotal and tribal knowledge that we're going to lose now, the next two or three years here across the board, whether that's – we know a lot of carriers decided to get out of the game in the past few years. Brokers are not having a great time now. Some of them are saying, “All right, let's hang it up.” You made some great points there. I think back to this one, where someone hanging it up, how does technology and AI help today, specifically, in a world where the margins aren't great right now? The pendulum hasn't swung back as everybody in the game will talk about.

Yeah. Yeah. Definitely. Well, and not I think that everyone – the cost to cover, really big thing. If you can increase number of loads, book per rep per day –

Sure. There it is again.

I was onsite with a customer, just even a couple of weeks ago. He looks like a rock star right now. He's like, “You know what? Our volume is growing. My team has stayed the same size.”

All right.

Pretty cool, man, right?

There you go. Yeah.

They're able to cover it. The technology is a key part. We're part of that team. Then, I think, the other thing, I'd say, look, the cool thing with Parade, we never forget a link. You ran a link, we got the data.

That’s a straight point.

Yeah. I think that's what's interesting, and it is. We pull all the information at TMS. It's really easy for that tougher to cover stuff, shipped to the load boards, get all that coming back, all of the quote data, the pricing data that you have. Yeah, typically in a world where, yeah, “a lot of your knowledge may be leaving the building,” for people that just – they just, man, they know how to do the stuff like the back of their hand. They're so fast. You wonder, they all have their secret sauce. You want to know how they do it.

I remember someone said, they used to have post-it's. Like, I got this truck post right up here. Yeah. But no, it is. Everyone's accessing a lot of the same information, you never forget a lane, right? You've got history of pricing data perspective. I think that's going to be the secret sauce moving forward is, yeah, there's nothing – nothing is ever going to replace that focus in the carrier relationship and just relationships in general. That's the thing that I think that is still really critical.

That’s key. Yeah. 

Yeah. Yeah. You basically empower your reps to do a lot of things much faster and streamlined and more automated, and then you know that they get to spend their time focusing on value added activity.

You don't have to have your desk look like a serial killer, or somebody chasing a serial killer with the pictures, the maps and the, yeah, the yarn all over the place.

Yeah. Oh, the map. Yes.

One, I've always dreamed to be in a situation where I had to have one of those just for the – But it also seems like an arts and craft project. Somewhere between those two, I both love it and I’m like, “That's way too involved.”

Uh-huh. Well, maybe what the movie, The Minority Report, where they were just putting – you’re like, you're just moving the trucks down like this. Hopefully that's a future.

That's closer to it.

That’s way more fun than anything else, right?

I like that. Now with AI and the, the learning, one of the things that here at Banyan, we've really leveraged on is that business intelligence. A, business intelligence can mean a lot of things. For my money, it's a lot of systems dumping data in one and getting the feedback and the visibility to give you actionable insights. Hey, I've got all this data. Now, I know what to do with it, because the reports don't mean anything by themself. How does AI from your technical knowledge and with your play in Parade, how does that benefit the landscape of something like, business intelligence?

Oh, amen. Well, and that's why I just spent five years in business intelligence. I got a couple of – maybe a couple of well-earned opinions on that.

Yeah. I'd assume one or two. Yeah.

Yeah. Maybe one or two. It's funny. The first thing is the actual, like the ability to use natural language processing is taking a lot of unstructured data and turning that inside. It's mentioned all of the information exists in emails and things like that that you can basically parse and basically upload into your database, it’s remarkable.

When you say unstructured data, is that just those emails? What is structured data versus unstructured data, just from a high level.

Yeah. Absolutely. Yeah, structured data probably already is something that could potentially fit in a table, right? Unstructured data could be what we saw – I mean, solve like social media, right? Think about what people are saying on Twitter, for example, or some people are taking unstructured data that's come from –

Things are still calling it Twitter, by the way.

Yeah. Exactly. Yeah. That's one thing for customer sentiment analysis. Again, Parade’s use case as well. All of the potential emails that are going back and forth between carriers and –

Yeah. That would be huge.

Also, unstructured data. There's use cases like documentation, I think, is another interesting one, too. Just pages of pages of pages of documentation. Protocols, things like that, right? Contracts is another really interesting amount of data. Just taking a lot of that unstructured data that is very hard to parse and analyze and from where it's been, and being able to parse it into your data systems and analyze that as one. That's a piece. I’d say, organizing, right? You can't be now –

Yeah, here’s a stack of papers. Put it in order that makes sense to me, or from alphabetically.

Yeah. Now, you get all this data. Now, how do you organize it? How do you model it? That's the thing, I spent my last gig a ton of time talking to data engineers, just figuring like, how do we actually model this data? How do we actually make sure? Cause it can all get really expensive. You have large amounts of data and I am on it. AI can have a huge impact on reducing a lot of the data engineering.

Yeah. That's the goal.

And the last is, and I actually, I think this is one of my favorites, asking questions your data, right? You stick an army of people that know how to write SQL and tweak things at the very smallest amount and say, “Oh, but I need to address this.” There are tools that are coming out to the base to say, “Hey, just like natural language. You ask, question your data and you pulls you up an answer, right?”

Yeah. Keep me away from the database management liners, please.

Yeah. I hope you visualize it and give you a story to go off of, which is pretty amazing. I think that's the thing. It's like, used to need an army of data scientists, data engineers to go set up your stuff in a data lake and then model it correctly and quickly and da, da, da. I think that a lot of that will be automated. Then the ability to ask questions and actually understand what you can do with it, just from a speed to analysis and insight perspective, I think that'll be huge, too.

As you're talking, it has me thinking, so you take AI and to get all this business intelligence data together and do the processing. At what point do we start using AI to tell us what questions we should start asking? Then AI to say, okay, I've asked the question, how do I use that answer? Is coding going to be no longer? If so, then it'll be, okay, based on these results, go use a smart process to think of what my next action item should be with it to do the thinking for me and then let me know what you – Not just an assistant, but really, coding your whole decision, or logic process as you get data. 

Yeah. 100%. I think that's the thing, when you think about what a lot of the use cases are for BI across them. This is model in brokerage, for example, exists across. It's pretty simple. Oh, I got to go. I got a shipper. I got to find a truck, and I'm going to – There's a buy and sell, right? Then I think, to your point, the types of questions you typically ask of the data are probably similar. That's like, as the models learn, and as the questions get better, hopefully servicing the insights proactively, I do think that that's another opportunity for sure.

As those questions get better, because as you said, the freight, it's one of those easy to learn, impossible to master type things, right?

Well, yeah.

The concept is real simple, A to B. But in mastering and being successful, it's all of this nuance. Possibly, and with this, as the questions to ask get better and more subtle about, I think that's probably where the predictive nature can get better.

Yeah.

Hey, not just, what should I charge for this? What affects the charge of this? What affects the scarcity of capacity for this lane? You know what, I mean, the historically, what will happen in the future? And give you an idea of what to look out for, so when it says, obviously, something as easy as, oh, there's a hurricane. Okay, it's going to have an effect, but exactly how? What percentages should I be looking at from there?

Yeah. That'll be a really interesting, because then it's like, what do you have that's proprietary? That's something with your question about data, too. What is that you have in your own data that's actually proprietary and who owns the data, who becomes king, right? That's where things get really, really interesting.

Yeah. No one has paid me yet for all of the ads that I get on my phone about the things that I clearly am into. When do I get that 5-cents a month kickback?

Cut me your check, right? Then it is. It is. That's, I think, the thing about, yeah, as it grows and the insights grow and things like that, it's like, you do have your own proprietary systems that arguably leveraging those against more public data sets, but that's going to be played out. There's a lot of things we’ve played out and lots of suits going on these days. Again, I'm not a lawyer, certainly. But you know what is public.

But AI can probably help us be one. Yeah.

Yeah. For sure. Speaking of industries that are going to get disrupted, those billable hours come in –

I think the California Bar is one of the first organizations that was against the AI, because when it first came out, people are using it to fight speeding tickets without just – and it was doing as they say. They're like, “Whoa, whoa, whoa, whoa, whoa. We charge five hours for that. Calm down. Calm down.”

Yeah. Yeah. ChatGPT, man. Find this precedence in the 50 pages of legalese in here, because who wants to read that, right? That’s it, yeah, to your point. That's what interesting, right? It's like, what is public available information that’s trained the models, versus what's proprietary.

Mm-hmm.

There’s be a lot of interesting privacy stuff over the course of time.

You know, without going into some of the, I don't want to say cons, but I guess, the friction and the controversy within that, how else, and I don't mean, generally across the board, how else AI can be used, but specifically within freight, logistics, brokerage, how else could we be using it that you haven't seen it used today? I mean, we've talked about how Parade use it, some pretty general case studies that we've heard or seen, as well as how it could be used from how it's already asking questions today. Where's an area that it hasn't touched that can have a big disruption in the industry? Or maybe there are pieces where AI will never take root, because it's not pattern-based and it's all unique? What do have thoughts on that?

It's a great question. Because I still think that even as a company who has AI baked into our DNA, there's still so much on top with the amount of data that is out there. It'll always come out to like, what's the data available and how do we learn from it, right?

Yeah.

Because even when working with brokerages, there's data that's trapped in disparate systems. Our vision is to pull all those together and make sure that you can gleam the insights and basically, take action from it. I think, we find, there's going to be a ton of opportunity still, I mean, we’re barely scratching the surface. We've started testing out some things from a pricing perspective that basically allow folks to use their own capacity to help price lanes with shippers. We're just scratching the surface there. There's so much information. That's what's, I think, the notion of efficient marketplaces, where there's inefficiency and things like that. I think there's a lot of questions that still exist, because so much can change, and I'm learning from a ton of people. Oh, this is we've tried to look at which markets are hot, right?

Yeah.

And where there's areas where there's undersupply, right? It's one of those things that real-time insights and data, I think, or something that can potentially track is depending on where people are bought into it. Yeah. It's always going to be what's available and how do we use it?

Yeah. I think that, and I think you're right on a lot of where it can be. I think that you're also right on where the emphasis will probably stay at that rate generation. For a lot of it, I know that we at Banyan have put, basically, a self-service truckload rate generation portal in place, where I might be a broker, or a 3PL and have these clients and more and more, just like the same way we order food. You and I grew up at our SDRs, BDRs, so we might be okay with picking up the phone. But more and more people, “I don't want to talk to a person. I just want to hit two buttons, get the number and go from there.” I know that that's where a lot of our system is going, because more and more, especially that's what the customer wants. I think AI and the BI is going to play a big part in getting them everything they need as quickly as possible, without me having to go, “Hey, how you doing? You want to talk to a live human being today? No. All right. Cool. I'll hang up now. Yeah.”

Yeah. It is. Amen for the SDR call out. Nothing will humble you like getting hung up on a cold call, right? Yeah. We're seeing that on the, I think, on the carrier side as well with folks just wanting to meet folks where they want to communicate is a huge thing right now, right? Yeah.

No. I think with that, this is where I've asked as many questions I can while still sounding intelligent, like I'm following. I'll quit a little while I'm ahead, but for you, Lizz, with two Zs, sorry, this is where I – what do you have as a message to anyone listening, whether that's from Lizz, Parade, or just anybody that, as I always joke, that five to seven people, not including my family that are watching or listening to this right now, what message do you have for them?

It's okay. I'll send a link out and a couple people might listen from my site, too.

That's right.

Yeah. I think, the thing about it is, right, is AI is both under and overhyped. I'm not the first person to say that, right? The overlords are coming to take all of our jobs and they're also not coming to automate everything we do, so we can go hit the beach with a Mai Tai, I tend to say, start simple. I have a little bit of a framework for a pyramid. It is programming, productivity, and progress. The programming is just finding some simple things that can be automated, right? Then the productivity is really thinking, like, talk to your people, figure out what are some of the mundane things they are doing that maybe they don't have to do, like details, emails.

Can you get some of these meetings off my calendar? Yeah. No.

Yeah, right? Like, oh, that could have been an email on a meeting. It's like, documentation is oddly enough, like meeting transcripts on notes, right?

Yeah. I love my AI notetaker. It's one of my favorite things I've invested in, because I can actually talk to someone without worrying about writing ever, or typing everything down.

Absolutely, right? That's the thing. It’s just like, the things that start saving you time so you can do the things that actually require critical thinking and thought, and then progress. I'm a big fan of everyone typically meets for whether you do quarterly, or some annual planning, what are some of the big things that can move the business forward? Then just to ask questions, could AI help with that? Is there a tool?

Sure.

A lot of times, you don't have to implement it yourself. There's great tools out there, obviously, like plug for Parade.

Yeah, you don't have to learn how it all works yourself. Yeah.

No. Then find the right partners. Talk to some folks. Say, “Hey, we have this problem we love to solve it with AI. Is this something that we need to go GPT and do on our own side? Or are there other tools out there that could be the right fit and help us implement something here? Because, I think, there's a ton of folks trying to figure out how to hop into the space, and yeah, I think it's a really good opportunity. And it doesn't have to be super complicated.

Yeah. Doesn't have to be daunting. Yeah. I have to call out here, you have a pyramid and it's three Ps. Did you have other words, but they started with other things and you had to work the productivity, the –

Typically.

Yeah. I had to get that pattern right.

I’m one of those people, Patrick. I actually start with the slide first, and then I figure out what I'm actually going to say. I was like, the pyramid of AI, what fits in here? Again, I think a lot in the productivity realm. When talking to people on my teams on a day-to-day basis and it's always like, okay, how can we make that task less painful? That's one of the most exciting things that I find, just run in teams organization like, man, if we can reduce some of the things that people do that they just really like.

Yeah. People are not going to fight back on that either.

Oh.

You talk about starting with how you wanted, all I can think about is creed from the office when he's in charge, you just got an acronym. They're like, “What's going on?” You’re just like, “We've got an acronym. I need to figure out what the words stand for.” It’s just completely as not.

Yeah. I got an acronym for all. It's like, again, people remember things if you keep it simple. If you make it really complicated, they tend to be like, “What was it Lizz said that our focus is for the quarter, right?” I'm like, yeah. Just simplicity wins.

No, Lizz, thank you so much for the conversation today and the insights, not only with recently getting into logistics field, but just AI and data from your tech background. I really appreciate having you today.

Absolutely. It was a absolute pleasure, Patrick. I appreciate the time. This is super fun.

Hey, thank you. For everybody listening and watching, this has been another Banyan Technology’s Tire Tracks episode. If you like what you see, subscribe, comment, engage in any way. Lizz, thanks again. I'm sure we'll talk soon.

Amen. Thanks, Patrick.