Advancing Freight Tech with Ryan Schreiber
Episode Transcript
DD Spotify DD Apple Podcast

In this episode, Blythe and Ryan Schreiber, the Chief Growth Officer at Metafora, discuss AI readiness, integrating data sources, developing a strong data strategy, and identifying specific business use cases.

Drawing from his diverse background spanning freight brokerage to tech startups, Ryan also offers practical advice for companies looking to successfully implement AI and extract meaningful insights from their data.




Are you experienced in freight sales or already an independent freight agent? Listen to our Freight Agent Trenches interview series powered by SPI Logistics to hear directly from the company’s agents on how they took the leap and found a home with SPI freight agent program.

Tai TMS is designed to streamline your brokerage operations and propel growth for both FTL and LTL shipment cycles. Book a demo with the Tai team today and tell them Everything is Logistics sent you

Maximize your website’s performance as a sales tool with Digital Dispatch’s website management.

Show Transcript

See full episode transcriptTranscript is autogenerated by AI

Blythe Brumleve: 0:05

W elcome into another episode of Everything Is Logistics, a podcast for the thinkers in freight. We are proudly presented by SPI Logistics and I am your host, Blythe Brumleve. We've got another amazing guest for you today. T his conversation is already off the rails. We just started recording, but we just started recording, so I wanted to make sure that I give you something as to celebrate your fandom. Okay, so a jacket Jaguar's case. Yes, here's your all.

Ryan Schrieber: 0:31

This looks used, which I really appreciate. So like was this like a game day giveaway?

Blythe Brumleve: 0:37

It's a lot of turmoil Got it, you know, experienced by that crazy, so I thought you would appreciate it. I'm to be honest with you.

Ryan Schrieber: 0:42

I don't know what type of experience happens in Jacksonville, but I know that I probably don't want my hands on it, but it's a lot of emotional trauma.

Blythe Brumleve: 0:50

It's the thought that counts.

Ryan Schrieber: 0:51

Yeah, also a lot of urine. Probably Not urine. Hopefully, it is the thought that counts. I mean, I hope not.

Blythe Brumleve: 0:55

But definitely alcohol sweat, yeah, for sure.

Ryan Schrieber: 0:57

But it's the thought. Thank you very much. I appreciate it. I will use this on my. I don't really drink, so I don't know actually what I'm even going to use this. I'll use it on my your water bottles.

Blythe Brumleve: 1:06

Yeah, there you go, your water bottles. And now, for folks who are just listening, ryan is a huge Jaguar's fan. We connected about this, we bonded over the Jaguars. He's actually a Tampa fan which just crucified my team last season. So we haven't really talked about the team, talked about the Jaguar since then. So it's a little bit of a sore subject, but we share that. We share that bond.

Ryan Schrieber: 1:25

I don't like to kick people when they're down. I like to kick them when they're out. You know, and just like remind them of how, how to keep people grounded in the fact that you're still the Jaguar's.

Blythe Brumleve: 1:37

I know it's a realization. It's sort of the picks and ballies of being a fan. So you have to appreciate the wins when you got them, because you know they're not going to be. It's going to be very short, I'm not going to get it. I've been a Bucks fan.

Ryan Schrieber: 1:48

I mean, I feel like I've had some good years but they have a lot of really bad. My first like football memory was, you know, it's probably like 1994, it was opening day at the old stadium and the Bucks were playing the Kansas City Chiefs. So it was 1994, I was 10, you know, and it was like unbelievably hot. Like you know, they had the metal seats in the old stadium. So I get it. I see there's a lot of down years.

Blythe Brumleve: 2:10

And you know I For Florida sports teams in general. Oh, God, God, who are you telling? Except for the Gators, they had, you know, very successful run, begrudgingly.

Ryan Schrieber: 2:16

Yeah, but very a lot of down times recently. Like they already want to fire this guy with their coach. Thank God.

Blythe Brumleve: 2:21

I just wish nothing but, suffering to that fan base. I agree, I agree, I don't know that. I've actually said who is. You know who we're talking to right now. Ryan Schreiber, I'm Ryan. Yeah, you work for Metaphora. Are you co-founder or founder? What's your role with Metaphora. I'm the.

Ryan Schrieber: 2:35

Chief Growth Officer for Metaphora. So Metaphora is we do technology consulting but we focus exclusively on transportation, logistics by chain. So you know more or less. We help our customers figure out what to do with technology in their business we and then we help them execute on on whatever that strategy might be Technology and data and then execute on that strategy, whatever it might be. We help them procure software, we help them implement software, we help them build software. So that's a little bit of what we do.

Blythe Brumleve: 3:02

How did you? What did you do before Metaphora?

Ryan Schrieber: 3:04

So I come from the industry I come. I started my career at Google Global Logistics about 15 years ago, just as a freight broker slinging freight. I started a few companies in the space, so I started a couple of legacy brokerages. I started my own inventory consulting business at one point, which was a huge failure, just like unbelievable failure.

Blythe Brumleve: 3:24

How so.

Ryan Schrieber: 3:26

Well, I couldn't really get customer, like I couldn't pay my bills, basically, you know, and it was like I really struggled with like getting customers and also like trying to deliver solutions for customers. I learned a really valuable lesson that I was also a little half in half out Cause, like I knew somebody would hire me and pay me to a lot of money to, you know, build their brokerage or run their brokerage or what have you and I, so I didn't give my all to the thing. I kind of like was half in half out trying to figure out, you know, maybe trying to also find a job. And so I kind of learned a really valuable lesson there about like being committed to the to, like the thing that you're trying to, especially if you're trying to start something from scratch. Even though I had started two businesses from scratch before, then I started a tech company. We started in 2016,. We were a digital brokerage. We were applying generative AI. We didn't call it that back then but we were applying generative AI instead of an app to do digital logistics. And then I've been with Metaphor for about five years, so I come from industry like I. That's my background is. You know, the space is tracking logistics.

Blythe Brumleve: 4:26

I guess what was the catalyst of joining Metaphor?

Ryan Schrieber: 4:29

So I, that's it really. What was the catalyst? So one other thing you learn when you do kind of start ups if you will, especially when you have you get you're getting into bed with with people and if, whether that, if you raise capital from folks like you're getting into bed with your capital providers, if you have co-founders like you're, you're getting married to these folks. And so I was the freight guy and my two other co-founders were more tech folks and we just had some very, very fundamental disagreements about strategy. And so I I decided to move on from the business and, unfortunately, like we, the business failed as not necessarily as a result, but also not not as a result. And so I was trying to find the next thing that I wanted to do and and it was that was really hard for me I, I hate freight brokerage, I hate trucking, I just I hate them in the sense that they're very broken businesses, the operating models are broken and they really break people. I mean they, they really do. And so I spent some time thinking about, like what do I need, adam, the next opportunity, like what I know, what I bring to the table? Like what do I need to get back from a company, and so I spent a lot of time thinking about that. I had a couple of opportunities. You know that kind of was picking from, but metaphor really like it was a great team, still a great team. A great problem. Like. I'm a very curious person, so I like being able to solve different problems and so it gave me the opportunity. Consulting gives you the opportunity to see different problems, see them manifest themselves differently, but also like move from you know, move to, from problems to problems, and so it gave an interesting vantage point. I thought it would. I thought it would give me an intellectually stimulating experience, which it has. So like. I don't know that answered the question no, it does.

Blythe Brumleve: 6:25

I'm curious, though what are some of those big problems that you're solving, or maybe exciting big problems that you're solving?

Ryan Schrieber: 6:30

today Some of the really interesting, like you know, they're everybody. I think it's human nature to trend chase a little bit and so, of course, like all of our conversations over the last 12 months, the conversation, all of them, somehow touch on artificial intelligence, machine learning Not that we weren't having those conversations before, but they've certainly accelerated. And so some really interesting challenges when you think about the space of transportation and logistics. So our customers are our shippers, they're transportation providers, they're freight technology companies, they're private equity that serve the space of trucking and logistics and supply chain, and so Data is a big problem. So AI readiness, like most companies, there are areas where you can apply AI today Generative some generative AI use cases around natural language processing can deliver value, but the reality is most companies don't have the data strategy. People talk about clean data. That's a thing for sure. It starts with actually like getting all of the data together that you need. When I walk into these businesses a lot of times when I look around and I just see all the data, that's like lying on the ground. So, as an example, like most folks really, really underestimate the value of the data from phone calls and I don't mean what people are saying but being able to like see who's calling sorry, excuse me like to be able to tie together things. Like you know, this phone number is associated with this driver, that's associated with this carrier, that's on this shipment and what was happening with that shipment when that driver called in. So giving context to data, and so you know there's a lot you can learn about the behavior what's kind of referred to as observed behavior of participants, and you need a really connected technology ecosystem and you need a connected data strategy to kind of unlock some of those things. So AI readiness is a really interesting problem that we work on these days.

Blythe Brumleve: 8:34

What are some tips, I guess, for companies to maybe want to you know? Thinking about that next step and thinking about you know that had AI shoved down their throat for the last year, so how are they, how should they prepare, I guess, for AI or data readiness?

Ryan Schrieber: 8:47

Yeah, focus on integrations, like, focus on well, let me rephrase that Focus on getting access to the data that you have. And then step one is for the last 10 or 15 years, we've really focused on, like, get your hands on data and put it in front of a user. Okay, well, users have too much data to parse. Humans can't consume the amount of data that we're talking about. So, in the absence of a clear path forward, they make things up like genuinely like, because there's enough data to validate or justify the decision. On the backend, you can point to these data points, to these same points. So, step one focus on getting access to as much different types of data as you can. Your phone, like you know, phone information a lot of vendors, especially if you have, like, off the shelf things, they have tools that underlie analytics, tools that maybe you're not using too, but then make sure that those are connected. And then focus on a data strategy. So, like, how are you master? Data management is a term, so focus on how you're managing your data, where the data is moving, and then how you can get access to that data, how that data is structured. Those are all like they're obviously difficult and thorny problems, but AI and machine learning are very difficult things to do. It's not as simple as saying like hey, okay, we're gonna do AI, and so there are certainly vendors that can help you with that. There are off the shelf tools that are making use of AI. Be careful with those, like some folks are talking about AI that aren't doing AI, but also really getting access to that data. And then the most important thing is answer the question what do you wanna do?

Blythe Brumleve: 10:31

What are the use cases that you're seeing? Ai ML exactly.

Ryan Schrieber: 10:33

AI ML is not some like magic elixir, like what are the questions you want answered into Insight, into so one of our large customers I've been talking to. They have a support staff that's doing kind of like shared services around answering in-mountain phone calls for everything from like what's my delivery number to what's my payment status. Well, like analyzing those phone calls to understand what's the most common problems these people are solving, so that you can then automate from there. So really focus on, like what are the business problems that you wanna solve with technology? That's true of AI, machine learning, that's just true of anywhere you're gonna apply technology. What's the business problem I'm solving? What's the question that I wanna get answered and then, obviously, get access to that data.

Blythe Brumleve: 11:26

Are you in freight sales with a book of business looking for a new home? Or perhaps you're a freight agent in need of a better partnership? These are the kinds of conversations we're exploring in our podcast interview series called the Freight Agent Trenches, sponsored by SPI Logistics. Now I can tell you all day that SPI is one of the most successful logistics firms in North America, who helps their agents with back office operations, such as admin, finance, it and sales. But I would much rather you hear it directly from SPI's freight agents themselves. I want better way to do that than by listening to the experienced freight agents tell their stories behind the how and the why they joined SPI. Hit the freight agent link in our show notes to listen to these conversations or, if you're ready to make the jump, visit SPI3PLcom. Are you a broker, ready to level up your business? Well, I've got a game changer of a solution for you because, let's face it, your TMS choice can make or break your company, and that's where having the right ally becomes key to success. Meet TIE Software, an all-in-one platform with user-friendly automation that makes your day-to-day operations smoother and smarter. Whether you're running a big brokerage or a startup, tie's got your back through every phase of your domestic freight Gear up because your logistics journey is about to get a serious upgrade. Experience it now by heading over to tie-softwarecom for a demo. Are there any questions that they should be asking? Maybe they don't know the questions that they should be asking of their data. Is there maybe like a framework that you work with your clients, with?

Ryan Schrieber: 13:06

They should probably ask themselves like how do they free up money to work with somebody like me, but no, a framework to work with the data? Yes, that's a really like. I don't know that I got enough time to really walk through a framework, especially without some visuals. But I would say that really the key, kind of like one of the keys is making sure that the data is like the master data management, having a cohesive and consistent kind of like way of describing a piece of data. So you know, like, as an example, you know how is a shipment conceptualized from a data perspective within the entire ecosystem and so, but there's no one-size-fits-all answer for any of this. Like every business is discreet. There are certainly like ways in which these businesses are similar. Likewise, you know we wouldn't be able to do anything together or there wouldn't be a use of technology, but that you know if you're a traditional 3PL doing distribution versus you're a shipper, you know doing chemical versus healthcare, or you're like a freight broker or a trucking company that's doing you know last mile how you think about pieces of data that's going to differ by your business, and so there's no kind of like one-size-fits-all answer for how to look at that. But yes, I mean, I think if you need, if these are things that you really want to do, educate yourself on. You know data management and it doesn't require there's ways to make incremental improvement that aren't millions of dollars of investment, and so certainly like that's a way to kind of like start to think about it, and a lot of it will start with kind of what your technology ecosystem looks like and what tools you have and how they're helping you get access to the underlying data and how easy they are to tie together with other things.

Blythe Brumleve: 15:07

One thing that's really helped changed a lot of my marketing is using these AI note-taking apps that automatically join the meeting, transcribe it and then I'm able to filter through and parse through a lot of that data with different customers. Can a lot of 3PLs or carriers, maybe tech companies? Can they utilize a similar approach with some of these tools?

Ryan Schrieber: 15:27

Yeah, so like that's leveraging natural language processing and so like. Again, my last business was using natural language processing to digitize like a lot of things within a brokerage, and absolutely like NLP, especially because, like you're not going to build you know NLP is built on natural language processing. Nlp is built on large language models. That's what we refer to as deep tech. You're not going to build a new large language model and the great thing about you know where we are today with NLP is there are these large language models like ChatGPT that are commercially available. What you're going to do, if you're going to build an application, is kind of train that model on your use cases. But there are a lot of opportunities right now to apply NLP across your business from chat-related applications like automated phone calls or automated text messages, replies to emails, but also like less, but also a parsing document. So any place where you get text-based communication right, I can read an email and understand what's happening. I can look at a POD and see an OS and D notification and I can run automation off of that. So there are a ton of use cases like across a business that can solve this problem. So a good example is I had a customer when I was a freight broker, they used to say every day they'd email me in the morning and say are we good on our load today? That's all I would say. The email said are we good on our load today? And I'd be like, yeah, yeah, willie, we're good on our loads. And so then I was like, hey, man, I can give you a login to the TMS and you can check all your loads. You can see who the carrier is, whatever. So I gave them this thing and I told them how to use it. I got an email every day hey, are we good on our load today? And I was like, all right, man, well, here I can automate this report. It'll email you a report that says this, that and you know, and, then, and, and, and he would still email me every day are we good on our loads? And so I started emailing him every day. Before he emailed me, I started actually just creating an email that would go out and said hey, we're good on our loads today. Why? Well, because he not that he just wanted to hear me say, but he had trust in the fact that if there was any information that wasn't salient to him or that wasn't readily available to him in a, in an app, in an email, I would tell him right, and so that's human to human communication. And then he also had the opportunity to ask me questions because he's engaging me. So there are a number of opportunities there. The biggest challenge that companies run into is is in change management, and everybody hears about change management and talk about it. That's really like how are you going to, how does your business, how does the business, part of your business, need to change to get value out of these things? That's less a problem with things like natural language processing, with other areas other than other types of applications of technology, because it doesn't ask users to change their behavior. Usually, external users, especially external users Like again Willie didn't have to start logging into the TMS. He could just still keep emailing and I could say, yeah, willie, these things are good. I could tell them load numbers, I could tell them who the carriers were. But change management still is definitely something to consider. And how and in what areas do you want to refocus your internal users Now that you've created these other efficiencies, and what is their incentivization like? So how are they not compensation? Compensation is a subset of incentivization, right, natural, human incentivization. You've seen OfficeSpace. What's the line of he's like? I have three bosses, so like my only goal is to not get hassled If I make one mistake, three people talk to me about it. That's incentivization His incentive, overriding incentive of everything else, even if the right decision would make the company more money or hit more money. But it's the wrong process or whatever. He's gonna do this thing because he's gonna do whatever gets him not hassled, because it outweighs every other incentive. And so that's certainly a big part of thinking about how to apply things like what you're describing. So that was a long-winded answer.

Blythe Brumleve: 19:32

No, it was great because it's helping me sort of connect the dots and I'm sure for a lot of folks out there that have heard you know a lot of these phrases it's helping them too. Now I'm curious, switching gears a little bit, you know, with your company and all the people that you're working with, what are some of the most, I guess, aha moments or like exciting moments, that you think is building for freight today and in the future?

Ryan Schrieber: 19:56

I think that what I really like, that I'm seeing in technology today is like there's a lot of disillusionment around technology that's available commercially right now. That's what I'm sort of sensing, and I'm actually kind of happy about that, and it's not the take of like. Oh, you know, there's too much like of these people in the industry who you know. There's venture money and we need to clear out. The challenge is like there's a lot of most of the time for what it's worth like when we go into a company and they're like I hate my technology nine times out of 10. The reason they hate their technology is their fault, not the technology's fault. But and yet, like that's still meaningful, that still matters, right. They're not getting the value that they look for. A lot of like. I think the trend in the last eight, nine years that I've seen is all around automation and it's skipped a step, which is user enablement, right. So like how do I make a user do their job better? And so there's been a lot of focus on automating things that aren't working the way that the underlying entity actually wants them to work or needs them to work to effectively grow or scale their business, and so I think that's something that's been really exciting for me is people focus, refocusing on how do I delight the human in the machine, right, how do I create space? And I think that's actually gonna make automation better in the future. Number one, because you're gonna be able to automate things that are working. And number two, you have built more trust with your users that their job can change over time and that you can create space for them to do the things that humans can or should do, and that's not executed transaction, which we've sort of co-opted the term relationship to mean do a transaction, but actually a relationship Like talk about, like boardals on the good place or things like that. So that's something I'm really excited about as a trend in technology.

Blythe Brumleve: 21:53

That, I think, is that folks are starting to come around to and I think that, especially during this interview, you are asking a lot of the deeper questions. That, I think, helps companies save a lot of time and resources. I'm curious, though, for a lot of maybe the other players, or maybe some companies that are interested in working for or working with a company like yours how do they know how to spot the bullshitters Like the bullshit tech, the bullshit consultants? How do you sort through that to get to the good stuff?

Ryan Schrieber: 22:22

So my experience in this industry and in large swaths of the industry has been that you have some really great business leaders that know how to build really great businesses and they know how to operate really great businesses. But they don't understand their businesses in academic sense. Like you have to sort of like, and most consultants, most consultants, take an overly true like, kind of true consultants, like management consultants, strategy consultants. They take like an overly academic approach, which is why people don't like consultants. They're like you've never had to sit in our chair and make these decisions. We're like, obviously, folks at Metaphoria, some folks at Metaphoria have, and so we understand it very pragmatically. But there's also like an academic understanding, like too often companies are like they look at a technology partner or a consultant and they're like hey, my arm hurts and the doctor will be you know. And then you know I'm using like a doctor analogy it's like all right, great, well, here's some aspirin, take this aspirin, your arm will feel better. When the truth is like they're having a heart attack and they kind of like if you understand the like, you have to understand how the body works, right, but if you're just a person and you go to the doctor, you're like my heart hurts. I expect that you are going to know, and so I think that the key really is like really really drilling down to try and understand better their business and ask, keep asking kind of questions, keep peeling back the onion, because the most obvious answer or reason that something is or isn't the way that it is is usually not the reason that it's that way. The pain is usually somewhere else, the challenge is usually somewhere else, and so I think that's that's certainly step one. What are the challenges that you're trying to solve? And then ask your, ask your potential partners really difficult questions about their experience, like what they've actually done, what types of problems they've solved, what impacts they've had, and ask questions about what would make them disqualify a customer. I actually, when we help customers select software, that's one early question that we'll ask a potential vendor hey, who's a wrong fit customer? And if their answer is a wrong fit customer is totally other industry, not super helpful, right? I wanna know how? What's a customer that kind of looks like me but that's a bad fit for you? And that's true, I think, of consultants, especially some of the like individual consultants as much as it is technology vendors and whatnot. So I think that those are really kind of important things is really get smarter on how your business really operates in a more theoretical or academic sense, and to marry with your pragmatic, really valuable operational experience.

Blythe Brumleve: 25:20

That's a pro right there. You just brought it back full circle from the first question to the last or one of the last questions. Now we're here at Manifested Future of Supply Chain and Logistics. So what's your favorite thing that you've seen so far?

Ryan Schrieber: 25:31

So I'm not really a dog person. That being said, the puppy thing was cool and I wanted to bring this up, since you had it on your LinkedIn and you had the guy who runs it.

Blythe Brumleve: 25:41

Yeah, Dan Reese.

Ryan Schrieber: 25:42

You had Dan on and asked about the puppy thing. I think they should do like a puppy alumni event, right, so they should bring back the dogs, oh.

Blythe Brumleve: 25:49

You know, like bring back, like when are they now? Where are they now?

Ryan Schrieber: 25:52

Like two years ago dogs, so you can have like a puppy pen and like a dog pen. I've just had some really great conversations, you know it's. They've done a great job of bringing a lot of folks together, and so I don't know that anything I've seen is really cool. But I think the one thing that they do better than any other conference is giving a place for early stage companies. I have a real passion for that. Our customers are always kind of like interested in what is up and coming. They do an incredible job at that. So talking to some of these earlier stage companies that I either have talked to before or just got introduced to me, I think that's been a lot of fun.

Blythe Brumleve: 26:31

Ryan, it was awesome to finally get you on the show. This would be the first or the only of many.

Ryan Schrieber: 26:35

It probably hurt my feeling. That's why I wasn't.

Blythe Brumleve: 26:37

He's been invited several times. So we just never formulated it, it's been one of those like we got to get you on, we got to get in.

Ryan Schrieber: 26:43

And then it just you know it is.

Blythe Brumleve: 26:45

It's the truth. Do, ball yes Till we die.

Ryan Schrieber: 26:47

Yeah, we literally die. Well thanks for having me, by the way.

Blythe Brumleve: 26:52

Absolutely. Where can folks follow you? Follow more of your work. What's your favorite social media platform of choice?

Ryan Schrieber: 26:57

I'm not a big X person, although I am, on accent underscore user prime. There's a little bit of a story to that one, but LinkedIn is a great place to find me. Ryan B Schreiber and you know kind of I never had a state to reach out. I always love talking to new people.

Blythe Brumleve: 27:10

Yeah, thank you, ryan, for coming on the show. Finally, finally.

Ryan Schrieber: 27:13

Thanks for answering the request.

Blythe Brumleve: 27:14

Yeah, I hope you enjoyed this episode of Everything Is Logistics, a podcast for the thinkers in freight, telling the stories behind how your favorite stuff and people get from point A to B. Subscribe to the show, sign up for our newsletter and follow our socials over at everythingislogisticscom. And in addition to the podcast, I also wanted to let y'all know about another company I operate and that's Digital Dispatch, where we help you build a better website. Now, a lot of the times, we hand this task of building a new website or refreshing a current one off to a co-worker's child, a neighbor down the street or a stranger around the world, where you probably spend more time explaining the freight industry than it takes to actually build the dang website. Well, that doesn't happen at Digital Dispatch. We've been building online since 2009, but we're also early adopters of AI, automation and other website tactics that help your company to be a central place to pull in all of your social media posts, recruit new employees and give potential customers a glimpse into how you operate your business. Our new website builds start as low as $1,500, along with ongoing website management, maintenance and updates starting at $90 a month, plus some bonus, freight marketing and sales content similar to what you hear on the podcast. You can watch a quick explainer video over on digitaldispatchio. Just check out the pricing page once you arrive and you can see how we can build your digital ecosystem on a strong foundation. Until then, I hope you enjoyed this episode. I'll see you all real soon in Go Jags.

About the Author

Blythe Brumleve
Blythe Brumleve
Creative entrepreneur in freight. Founder of Digital Dispatch and host of Everything is Logistics. Co-Founder at Jax Podcasters Unite. Board member of Transportation Marketing and Sales Association. Freightwaves on-air personality. Annoying Jaguars fan. test

To read more about Blythe, check out her full bio here.