July 31, 2025 • 37 mins
Are you getting ROI from your AI tools—or are you just adding more tech without solving real problems?
Today’s episode with Ryan Schreiber, a leader in AI and machine learning for logistics, digs into what AI means beyond the buzzwords, why most companies today are only seeing incremental and not transformational value, and what’s holding them back: strategy gaps, messy data, and weak integrations.
Ryan breaks down why most AI vendors chase the top 50 brokers while ignoring the bulk of the market, and how smaller companies can still get big wins by focusing on automating the unsexy stuff, think billing, compliance, and track & trace. Learn practical ways to rethink your workflow, price your time correctly, and implement AI with purpose, not hype. If you're in freight and wondering how to cut costs, improve ops, and scale smart, this one’s for you!
About Ryan Schreiber
Ryan has lived his career at the intersection of transportation and technology. As the Chief Growth Officer at Metafora, Ryan leads growth strategies that leverage the company's strengths and taps into new opportunities for both the company and the industry at large. Ryan’s commitment to the transportation and logistics industry is evident through his authorship for publications such as FreightWaves and Journal of Commerce and through his additional work as an angel investor and advisor to multiple logistics and freight tech businesses. Ryan has made substantial contributions to Metafora's progress and growth, including building partnerships, expanding services, launching new products, developing marketing strategies, and serving as a subject matter expert.
Connect with Ryan
- Website: https://metafora.net/
- LinkedIn: https://www.linkedin.com/in/ryan-schreiber/
- Email: rschreiber@metafora.net
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:04):
Came back with a bank window down yelling now money anything hey oh got the foot on the gas pedal to the metal when I'm get to the back hey Got the foot on the gas pedal to the metal when the lane moving fast hey Let them all cross if they hate then let them hate them Make a bigger balls a.
Speaker 2 (00:26):
What is up, ladies and gentlemen?
We are back.
We are live.
It is the Freight Coach Podcast, the top podcast in transportation, coming to you guys every single weekday, 8:30am Pacific, 10:30 Central, to break down some industry headlines.
But most importantly, you guys provide some actual insight into what you can do with all of this information.
If this is your first time tuning in, welcome.
This is the real side of freight, ladies and gentlemen.
(00:46):
And I do say that before every single show.
And what I mean by that is I only speak with transportation professionals because at the end of the day, you guys, I want to talk to the right individuals who have done what you're looking to do or who are currently doing what you're trying to achieve, so you can take that information, apply it, utilize it, and see a meaningful difference in your business and your life.
Happy Thursday, everybody.
I got a very special guest for you guys here today.
(01:07):
I'm really looking forward to this conversation.
It's a non AI company coming in to talk about AI today.
You guys, we're here, like, how do you deploy?
What do we do with all of this information?
There's so much stuff out there.
Where do you start?
Is it worth it?
Is it overblown?
Where are we at?
And there is nobody who is more qualified to talk about this than my friend Ryan Schreiber.
Ryan, thank you so much for taking the time to join me today.
Speaker 3 (01:28):
Yeah, that's true.
Speaker 2 (01:29):
Yeah.
Speaker 3 (01:30):
Yeah, man, thanks for.
Thanks for finally asking me to be a part of your podcast.
You know, like, for everybody else, I was giving Chris that, like, you know, it's four years or five years he's been doing this and he finally asked me to be on, so I'm happy to do it, man.
Thanks for joining.
Thanks for having me.
Speaker 2 (01:43):
Well, let's just clear some things up.
The zell deposited this morning, so that.
That's why.
That's why we're here today.
Speaker 3 (01:53):
Hundred dollars.
Yeah.
Speaker 2 (01:54):
Yeah, exactly.
That's all it is, you guys.
It's just a small nominal fee.
Chad told me to bill you directly for that to make that happen.
Speaker 3 (02:01):
So.
Yeah, that's good.
Yeah, ABRL is really putting it on.
So thanks, Chad, for.
Thanks, Chad, for sponsoring my.
My seat here on the Freight Coach podcast.
Speaker 2 (02:11):
Yeah, he.
He doesn't realize it yet, but he will be getting an invoice for this later on today and it'll be like per.
Courtesy of Ryan.
Speaker 3 (02:17):
Yeah, that's correct.
So dudes, assistants in the bill to him.
Yeah.
Speaker 2 (02:24):
Oh, man.
So what's good, man?
What's new in your world?
And, you know, and then talking about AI and everything, I think that I've had almost every AI company so far on the show and, you know, there's a lot of really good things that are out there.
I'm very much like, all about technology, automation, where we can.
But, you know, a lot of it is.
(02:45):
It's that deployment, it's that, do I actually need it right now?
What stands stage of my business am I currently in.
Speaker 3 (02:53):
Yeah.
So, you know, just for context, Chris, like, I've been working on AI and machine learning initiatives in logistics for about 10 years at this point.
Back in 2016, I started a company called Freight AI and were building artificial intelligence use cases in logistics.
(03:17):
So, you know, it's something that I have been working on for quite some time and longer than anybody else really, in the industry.
And so there's a lot of these foundational.
Well, the technology's evolved a lot.
And certainly over the last couple years with generative AI, we didn't have generative AI back then.
We just had kind of, we had chatbots and we had other applications of machine vision and NLP and machine learning.
(03:39):
But generative AI certainly has been a game changer and it's changed a lot in the last years of.
Couple.
Couple years.
But like, you know, kind of understand some of those foundational principles, working through, working on that for quite some time.
And then with metaphor, right?
I mean, it's the topic of conversation.
Metaphor does technology consulting for logistics and transportation companies.
And then primarily, yeah, yes.
Scott Watanabe.
(04:00):
I'm at the Hard Rock.
I'm playing, I'm playing.
I'm playing blackjack on the side, buddy.
I'm actually, I'm actually in Charlotte.
I'm not going by Armstrong's office, but I saw Cam yesterday, so.
So, yeah, man, it's, you know, we see the biggest companies in the space, you know, working on AI initiatives.
(04:20):
We're working with the biggest companies in the space on AI initiatives.
And we're working with some of the, you know, we're working with some of the technology companies themselves on implementing for their customers and whatnot.
And so there are a lot of, there's a lot of promise, there's a lot of value in the technology over time.
There are also a lot of challenges.
And the real issue, one of the biggest issues for companies at least making a selection, Chris, is it comes down to kind of the nuance that is in what's going to make one application useful for more complicated use cases and which ones are gonna kind of top out or hit a ceiling.
(04:57):
And so on the front end of like, selecting technology, that's certainly a big problem for people right now.
Speaker 2 (05:02):
What do you think most people get wrong about AI?
And, you know, I want to, like, from a, like a broker, like service provider's perspective.
And then what is being overblown out there by the AI companies trying to sell it into the market?
And I say that with the, with kind of a little caveat of like, if there's one thing that I have seen over the last five, six years in this industry is there's a massive influx in technology companies all promising how they're going to revitalize the industry.
(05:32):
And that really hasn't changed the landscape and the foundation of transportation yet.
Right.
Like, I, I think that we're a ways off from that.
But with that being said, what is being missed out there about AI right now, do you think?
Speaker 3 (05:47):
Yeah, I think the number, really, the number one thing that people need to take over, that people need to kind of realize is that artificial intelligence has been around for quite a long time.
Speaker 2 (06:01):
Yes.
Speaker 3 (06:02):
And that it means more than agent AI or even generative AI.
There's a lot of different ways in which AI affects and can affect your business.
And generative and agentic AI is only one part of that machine learning, something I talk a lot about.
And that's a big part of it too.
(06:23):
But the other is that it is a fundamentally different application of technology to your business.
And to get, but to get the absolute value out of it that you want to, it requires a different approach to technology implementation and business and implementation within the business than other technology does.
(06:47):
I mean, everybody has struggled like with every application of technology, you need to review process and you need to review operating model and you need to do some foundational work there to do some changes in your business.
But there's a, the power of this technology today, especially in the generative and agent space, is that you have to reimagine everything about how you want to do the job to get the most value out of it.
(07:18):
And most companies aren't willing, have not been yet willing to do some of that.
And so those are the two big Things I want people to take away from the AI conversation that have been really challenging to kind of get through to people.
Speaker 2 (07:31):
Yeah, I, I, I'm right there with you, man.
Because I think, like, what, from a consumer standpoint, from somebody who sees a lot of this stuff being released out there, you see some of the marketing behind some of these companies, and it's stating a clear message of, hey, we're going to automate everything.
We're going to make your life easier.
And then as a broker myself who I've interviewed, like, I've demoed like, a lot of these things out there.
(07:56):
And the end thing is it's like, hey, kind of tether your expectations.
We're not quite there yet.
And the messaging out there, and this isn't directed at any one company or not, I don't play that game.
But, like, I feel like as a consumer, I see a lot of message out there.
So I, I resonate with what you're saying there, Ryan, is like, hey, people need to understand, like, it's not there yet.
(08:16):
But I also feel like some of these companies need to tether their messaging out there because it's like, you can't sell a bill of goods that we're going to come in and do this.
And then when you're going through the demo and then the deployment phase, you're like, actually, we're not there yet.
We need another six months.
And then six months turns into another six months and then another six months and it's never there.
Speaker 3 (08:38):
Yeah.
And so I, Chris, the truth is the technology is there actually, like, it's capable of doing these things.
There are three main reasons that they're not delivering on that brand promise.
Speaker 2 (08:53):
Yeah.
Speaker 3 (08:54):
The first is really business strategy and business logic.
The second is data density.
And the third is connectivity and kind of like system.
System.
What's the word I'm looking for?
Speaker 2 (09:09):
Integration.
Speaker 3 (09:10):
Having to deal with antiquated systems, the core underlying technology.
Now, there are different, Some of the different vendors can deliver on the brand promise more or less than others, admittedly.
And that's kind of what I was talking about earlier in terms of how they're architected and how they deal with, like, how much context they try and pack into a message and stuff.
(09:31):
That's kind of particularly esoteric for this type of conversation.
But, you know, but in general, like, the actual underlying technology is there to deliver the types of outcomes and values that we're talking about.
The real challenge in delivering those is actually within the four walls of the brokerage and it's those three things.
(09:52):
So business strategy and business logic, data density and then connectivity are the three main reasons that people are really struggling to it.
And I can go deeper into those things if you want me to, Chris, but the reality that's kind of, I think a big part of the challenge is understanding that is really understanding what is holding some of these technologies back from being as successful in your business.
(10:16):
But that having been said, I will say Chris, that there are no one that I talk to is getting true deep business value out of any of these implementations today.
There are certainly people getting some business value and some incremental business value, but the transformational business value is not yet realized.
(10:38):
And again like some of that is definitely or most of that is actually on inside the four walls of the three PLs and the carriers.
Speaker 2 (10:44):
Do you think?
And I want to talk about connectivity, I want to talk about that.
But I want to put something else out there as well because one thing that I've kind noticed is there's a lot of tech vendors in the AI space that are fighting.
I, I personally think that are overlooking the biggest part of the market.
I think a lot of them are like hey, if you're not big, we don't want to work with you.
(11:05):
And it's like, I mean I just saw the TIA just released the other day like yeah, 75 of brokers do 15 million or less, right.
So it's like do you think that there's.
That some of these companies are missing the mark on where the real market is?
Because not everybody is going to work with, you know, we'll just transport topic releases.
The top 100 brokers and top 100 for hire carriers every single year go down that list.
(11:28):
The top 50 of them are probably building their own product at the end of the day.
So it's like are they really only fighting for 50 to 100 companies?
Because then the drop off from a top line revenue perspective is drastic below that top 100 list.
Speaker 3 (11:43):
Yeah, yeah.
So you know I also work as an advisor to freight tech companies and I deal with this in my business at Metaphora.
Right.
Here's the challenge.
Are they missing a market opportunity?
Kind of.
But there's really two big problems with working down market in logistics.
(12:04):
One is wallet share.
And so there's only so much money that any company has to spend on any initiatives.
Like I was, I use the analogy a lot of times.
It's like, you know, if you promised me, Chris, hey man, I will give you $300 million in six months guaranteed.
(12:25):
I'll put it in an escrow account right now.
So you know it's there.
Like I can prove that it's there.
It'll be there.
It's an irrevocable whatever.
And you're definitely going to get it.
You're absolutely going to get it.
To get it you have to give me $100 million right now.
I don't have a hundred million dollars, bro.
So like it kind of doesn't matter that you can get me a $200 million ROI because I don't have a hundred million dollars to give you.
Speaker 2 (12:47):
Yeah.
Speaker 3 (12:47):
No matter how much you can prove it and how much I trust you, I can believe you.
So wallet share is one of the problems.
There's only so much money to go around and as you go down market that gets exponentially worse.
Right.
And so one of the challenges there is kind of is there the money at these businesses to spread across all the interesting things that they want to do.
(13:08):
Gen logs or highway green screens, you know, their own tms dat, you know, and then you know, something in the AI space.
Whether that's, you know, whether again is that's this agent type AI or other types of artificial intelligence that are like data science related or machine learning related.
That's one problem.
The other problem is honestly it costs just as it's actually more difficult to deal with and sell to a smaller company.
(13:38):
Like so part of the problem is the brokers and carriers themselves that are smaller businesses and like just how they buy and, and how it is to deal with them and get a deal done.
And sometimes going down market is just more difficult.
So I would say that like these companies are willing to work down market.
The more you can make it easy to work with you.
Speaker 2 (14:01):
Yeah.
Speaker 3 (14:02):
You know, and to get a deal done, you know, the better it's going to be for you.
Because admittedly like it is actually more difficult to get a contract done with a top, sorry like you know, a $15 million broker than it is a top two.
I'm working on a contract right now with a top two broker.
Speaker 2 (14:22):
Yeah.
Speaker 3 (14:22):
And it's actually an easier process.
It's an easier sales process.
It's an easier, and it's taking just as much time as it has been or would if I was selling a, you know, a 15 million dollar broker.
Speaker 2 (14:33):
Yeah.
Speaker 3 (14:33):
So those are kind of the challenges.
So.
Yeah.
I mean is there.
Speaker 2 (14:38):
Do you think that in time there will be somebody who kind of comes like I'LL call it.
Not that the Toyota Camry is a bad car but like you know how the Toyota Camry is just, it's reasonably priced, it's nice and it's very reliable.
Do you think that in due time technology will kind of expedite up there to where it's like hey man, we have an, like this account.
(15:01):
We're gonna, we've developed the technology, we've ironed out a lot of this stuff.
It's gonna cost 500 bucks a month, hypothetical example ladies and gentlemen.
But 500 bucks a month, there's your AI.
It's going to come in and do all that.
Do you think that's going to happen?
And if so about how far out are we from something like that happening?
Speaker 3 (15:16):
Yeah, that's, yeah that.
I mean it's absolute like we're there now, we could be there now.
I mean there are so many of these companies to your point like I was actually talking yesterday, I was at the Freight Waves AI symposium or what have you and you know every week I hear about two new companies minimum that are working on this problem and so they're all going to need to find product market fit somehow and some of these solutions are going to struggle with more complex use cases.
(15:52):
But yeah, I mean absolutely like and there are companies now that again will sell down market.
I think that some of it is, some of the other part of it is I think that smaller brokers and carriers they don't need as robust tool set as bigger companies do.
(16:13):
And yet they sort of like they misunderstand and listen again or for everybody who's listening who may not know my background.
I've started three brokerages in my career.
So like I've had to build a company from nothing.
Like I know what it's like to be a 5 million dollar 10 million dollar 20 million dollar 50 million dollar broker.
And so you know you, I did the same thing and did I see everyone doing else doing which is overestimated the complexity of my business and how robust the tool set I needed at any given time in my business was.
(16:48):
And so those exist today.
Looking at more point solutions as opposed to platforms would be a good place to start.
So folks who are focused on a specific use case and then look at other things for AI that aren't agentic or generative really agentic as such like look at back office situation like look at things, look at your P and L and identify areas where you're wasting money.
(17:13):
A quick story that and then I'll stop for a second.
But you know there was one year where it's probably, you know, it was the first or second year of one of the brokerages I started and we did 15 million in top line revenue.
We did a million and a half in gross profit and I took $20,000 to net operating income.
Only $20,000.
And I looked at my, you know, P and L and I was parsing at the end of the year, God, where's the money to grow, you know.
(17:34):
And I had spent $200,000, excuse me, $500,000.
I had spent a third of my overhead, my over, sorry, my GROSS PROFIT ON SGNA 4HR Track and Trace, carrier compliance and onboarding and billing.
(17:55):
Billing and collections.
Yep, that was third of my.
Like there's real ROI there and it doesn't need to be this sexy carrier sales, it doesn't need to be customer acquisition.
Like that was real money that if I could get access to, I could use to grow my business, I could use to invest in sales, I could use to grow revenue.
(18:16):
So look in some of the non sexy places, Chris is where I think that the low hanging fruit is for, you know, smaller brokers today, down market brokers today.
Speaker 2 (18:24):
That is like, I mean you are honestly listing out like kind of my strategy of implementing technology and automation into my operations here.
Ryan is.
It's a lot of the stuff behind the scenes like, and I say this on the show often, man, I'm like 95 of my day as a broker should be automated.
The 5% that I will never automate in my company is the customer experience and the carrier experience because they want to talk to real people.
(18:48):
So if you're one of those AI people in freight who are trying to do automated carrier sales, you're not going to get it from me.
I'm not, I'm not doing that.
And I.
Speaker 3 (18:58):
Perspective, sorry.
Go ahead buddy.
Speaker 2 (19:04):
From my perspective, there's a lot of stuff behind the scenes where I can automate to grow smart.
Right?
Because like that's ultimately.
At the end of the day, Ryan, I need to build a war chest of funding while I'm scaling my business.
I, I'm not, I don't have investors.
I don't want to take on investors because I want to do this on my own.
You can call me, people can call me wrong, whatever they want, but it is a lot more important for me to own 100% of Chris than it is to get a capital investment to possibly expedite five years of my life.
(19:35):
And I look at it as, there's a lot of roles behind.
Speaker 3 (19:37):
I see it very similarly, for what it's worth.
Speaker 2 (19:39):
Yeah.
And I, I just look at it, Ryan, as is.
I'm like, man, there's a lot of stuff that I can automate behind the scenes where it's like, hey, instead of hiring three people for this role, I can hire one, make them more accurate, and I can actually pay that one person more money than I would be able to if I needed to have a manual task and have three people in that role.
And I look at that as.
(20:00):
It's not.
Chris is trying to not hire people.
On the contrary, I'm trying to hire the right people.
So where if there is a down market, I don't have to look at you and be like, hey, I'm paying you too much money.
You're out.
Speaker 3 (20:14):
Yeah.
So I would.
Chris, I think you're painting automation with a little too broad of a brush and talking about automating the carrier experience and the customer experience because they want to talk to a person.
They do.
Sometimes what they really want is their problem solved quickly, like, and they want to be met where they are.
So I'll give you an easy example.
(20:34):
If a driver, it's three o' clock in the morning, the driver shows up to a delivery facility and he's like standing in line to check in and he goes, I don't know what my delivery number is.
He doesn't really care if he talks to a person.
He just wants his delivery number really quickly.
But he also wants to be met where he is.
(20:55):
Right.
Which is why, like, kind of the Download my driver mobile app doesn't work.
So that driver's ability.
And again, we're talking too much about, we're talking all about agents and generative AI, but that ability for that driver to call in quickly, get somebody on the, get a bot on the phone to, and it gives him his delivery number and he can move on with his life like that for sure, is a significantly better experience than they call, he calls you've got to get out of bed.
(21:21):
I actually, there's a transport topics article that came out this week that quotes me saying this exact same thing.
It's.
It's better.
And then you having to get out of bed, turn on your computer, get into the TMS, call them back, it's 15 minutes.
Like, everybody's better off for that experience.
I got to stay asleep.
And the driver got the information answered for him.
And you know, and so I do think that painting automation with too broad of a brush, that there are things that we aren't going to automate or that we shouldn't automate.
(21:48):
Right.
Which is like I used to call my customer, there was one customer, you know, he's still a good friend of mine to this day.
And like I would call and do an NFL pick in with him every week.
Like that's, we literally would do that.
That's.
That's the real relationship.
I'm obviously not going to automate my NFL pick them with him, but I can automate the rate core quote, you know, that is I can automate that if he wants that if he opts into it.
(22:10):
If he doesn't.
And if he doesn't opt into it, I can, I should price in my time.
My time is very valuable, right?
That's why you're paying me to be here.
We talked about this out like, yeah, you know, that's why you're paying me seven grand a year just to bring that joke back.
But you know, it's.
My time's really valuable and it should be paid appropriately, right?
(22:31):
It should be, it should be compensated for.
So if you're going to make it difficult to do business with you, if you're going to require me to call you on the phone to give you the rate quote, if you're.
Those types of things need to be priced into the freight opportunity because I actually do pay for it.
I pay for it below the line.
Brokers P. Ls are deceptively simple in ways that actually hide a lot of the cost of doing business with a shipper and in ways that I think are really damaging if you don't really dig into it.
(22:57):
But yeah, Chris, I think I agree with you.
There's parts of it or I agree with you in part, right.
There's parts of it you absolutely don't want to automate.
Shouldn't automate.
Never automate.
But I do think brokers, I see brokers frequently rather paint automation with too broad of a brush.
And you really need to break down what's the situation and what are we trying to accomplish and what's the best way to do that and where do people want that and then how do I make sure I meet them wherever they are, if they want it by email, if they want it by phone, if they want it by SMS or they want to be, you know, if they want to be top.
(23:29):
If they want to buy carrier pigeon, like great let's meet them where they are and get them that and price it in.
Speaker 2 (23:34):
Do you think people in freight are painting AI with too broad of a brush because they've been told that it is way more capable than it actually is out there in the market?
Because like I see where you're coming from, Ryan, 100%.
And like you do bring up a good point, right?
Like that automated, hey, what's the delivery number?
Stuff like that.
Like we don't have enough time.
But I could go down the argument that like a real broker would have made sure that driver had that information prior, you know, yada, yada in form.
(24:01):
But I look at it is we're, we're at a point where I think one of the big struggles that AI companies are going to see over the next two to three years is they are going to have to fight against AI tools that are out there in other facets of a person's life and they're going to instantly make that correlation.
(24:22):
Because a lot of people, when, you know, if you've ever worked in sales, your prospect tends to kind of make up their own story on what they think you're saying is.
And I feel like it's on you as a sales rep to make sure your messaging is crystal clear on what your product is actually able to do.
Speaker 3 (24:38):
Right?
Yeah.
Yes.
I mean, I like, no, I guess I agree with your underlying point.
Yeah, I don't think that I really push back on the over promising piece of this because it really again, like the biggest reason that brokers struggle, the number one reason, as I said earlier, it's like business strategy and business logic.
(25:03):
Like these companies, I mean even the biggest companies in the space, they struggle to pull out the business.
The complex business logic that goes into their decisioning, it's what you would call implicit, right.
Like it's that institutional knowledge that's just like, well, I just know what to do.
Okay.
But you know, to think about, you know, agentic and generative AI like, and then actually really like any types of machine learning, like there's, you have to know the information to get good outcomes.
(25:34):
Like you have to train.
Literally like everybody talks about training models but like you have to train a human just like you have to train a, you know, like an AI model and the information has to be available.
Like imagine I came to you and I was like, Chris, I want you to quote me on a shipment.
Okay, well what, where's the pickup and where's it deliver?
(25:56):
I can't tell you.
Okay, well, when does it pick up and when does it deliver?
I can't tell you that either.
Well, how long of a transit is it?
Yeah, it's like, I don't know, it's somewhere between like 600 miles and 6,000 miles.
Okay.
What's the commodity?
What's the equipment?
If you can't answer any of those, like, you know, if you can't answer, the more of those questions you can answer, the better I can get better results I can give you.
(26:19):
And when I talk about things being implicit, sometimes things aren't available to these applications.
That goes to data connectivity and data density and some of the other stuff.
Some of these things aren't available to the applications in a way that allows them to deliver the business value you're describing.
Now, I do agree that at some level, like as a salesperson, if you really kind of, or like as a company, like you want to disqualify customers as much as you qualify them.
(26:49):
I walk away from customers sometimes that I don't believe will be successful working with me and with Metaphora and with other businesses that I have.
But at the same time, like, Chris, if you bought some, you got sold.
Like, that's on you.
Like, their responsibility is to try and sell like you're, they're trying to sell their product and like, they should care, quote unquote, that you're going to be successful, but really, like, the world doesn't work on should.
(27:17):
This is capitalism, as a lot of people like to point out all the time.
So, like, it's on you, bro.
And so, yeah, man, do your own due diligence.
Are you in a position to articulate the business logic that's required?
Probably not.
Or the business strategy.
Like, how do you decide when to take a 9pm appointment, delivery appointment, you know, when you wanted 9am like, sometimes you'll ask for a reschedule, sometimes you won't.
Speaker 2 (27:40):
Why?
Speaker 3 (27:41):
In what scenarios?
You know, if you don't have, if your systems can't connect to each other, do the due diligence to figure out what these applications need to be successful with you when talking to them and then figure out if they can do that.
Because if they lie to you, that's fraud, right?
But if you didn't do your due diligence, which is what I see more frequently than not, when people are upset about how they, the outcomes they got with technology, it's that they didn't do their homework.
(28:07):
They didn't ask the right questions.
They didn't ask the right depth and level of questions.
And.
And so then they didn't get the value out of it.
So, I mean, I'm sorry that I'm pushing back so much on this concept of, like, technology is not there.
Speaker 2 (28:19):
Because, Ryan, here's the thing.
Speaker 3 (28:21):
This stuff, it largely is.
Speaker 2 (28:23):
Yeah, this.
This needs to be said because, like, nobody's asking these questions out there, man.
And then they find themselves in.
In that exact position you're talking about right here where they feel like they got.
And now they're sitting there and they're on.
Like, they're blaming other people because they never stop to take five seconds to be like, hey, where am I at in the business?
(28:44):
Do I actually need this?
Why am I signing this contract?
And, you know, again, man, you're.
You're right in your.
In your stance here of, like, hey, sales reps are there to sell.
If you got sold, that's on you.
But again, that, like, that.
This is the entire premise of the show, Ryan.
This is where real conversations need to be had.
Because, like, we need people to think about this stuff outside of how they're currently thinking.
(29:05):
Because otherwise, man, one thing that.
Again, it's not my responsibility to feel bad for people, but I'm a human being.
I feel bad when I hear from people, like, yeah, man, I got out of $30,000.
And, you know, like, as a business owner who's bootstrapping, it's easy to hear that.
And that's why I'm like, I want to have these conversations on this show because hopefully somebody hears this, Ryan, and.
(29:25):
And they think about it differently when they go into that next demo.
Speaker 3 (29:30):
Yeah, I.
So, you know, bro, like, it's not just about AI, man.
This is like Beauty and the Beast.
It's a tale as old as time.
Like, this is.
This is.
This is the story of people picking technology for quite some time.
And admittedly, like, it's the entire reason that I have a business, because people need help picking technology.
They need help building technology.
They need help implementing technology.
(29:53):
So, I mean, the key is part of what you just said.
Why do I need this?
Why do I want this?
What am I trying to get out of it?
Chad, you talked about.
We talked about Chad Olson earlier.
Chad and I have this conversation frequently that, like, he'll also walk away from customers that he doesn't believe will be successful with this product.
Because, you know, there is a.
There is a FOMO element in freight tech where it's like, everybody else has this.
(30:16):
I should get it now.
I think that, I think that people also go the other.
Excuse me, I see people also go the other way of like rejecting.
Rejecting stuff just for the sake of it because they don't need to do it.
Because I still use fax machines and.
But like, you know, but.
(30:38):
But the reality is I also feel bad.
I give a lot of.
I give away a lot of free advice.
Like I, you know, I give away a lot of free work of.
Because I want people to be successful.
Number one.
Why are you doing it?
Ask that question, what the business problem you're trying to solve.
Speaker 2 (30:54):
Yeah.
Speaker 3 (30:55):
Don't not what's cool technology?
There he is.
You know, there's.
What's the business problem you're trying to solve?
Why are you trying to solve it?
And how do you.
What's the best way to solve it?
Here's the thing, here's the other thing about AI actually that I want people to take away that they're missing.
It's actually the worst.
(31:18):
It's the worst is the wrong way to put it.
It's the.
It should be the last solution to many of these problems as it relates to technology.
It's incredibly powerful.
I love is.
It is.
It is incredibly powerful.
And it's so powerful that actually there's.
You should have tried everything else before you get to artificial intelligence or machine learning or whatever else it is because, you know, we see it in reporting a lot.
(31:45):
Like, you could do a lot with machine learning, but you have to be able to ask really interesting questions that are different than you could get from a BI dashboard.
And, and so it's probably the wrong way to solve the problem.
It's just cool and sexy and seems neat and also seems easy.
And there's ways in which it is easier than other technologies.
And I wrote like, I actually wrote an article for TIA about this like three or four years ago that natural language processing is the.
(32:09):
Is kind of like the easy but solution to certain aspects.
But like, and then, and then get into what do I need to be successful?
What do I need from a vendor to be successful?
I see this in TMS selection just as much as I see it in AI.
What do I need from a vendor to be successful?
I might need a vendor to help me suss out the business logic if they think I'm coming to the table with all of the answers.
(32:34):
Like the deep, deep answers.
Like, I know how my business works, but like, really be able to articulate again Why I might take this 9pm appointment but other times I might reschedule it because this carrier, because this customer, because I missed this load yesterday, blah.
All of those things that go into that.
If I need somebody to help me suss that out, I need to vet the vendor for how they're going to do that.
(32:55):
What does customer success look like?
What does implementation look like?
What are the activities that you are going to do?
How are you going to do this?
You know, literally walk me through.
Just like a job interview, walk me through a scenario where you did this with someone.
Show me this.
In production, I mean there is vaporware out there, Chris.
Like I'm not going to pretend that there's not for sure.
(33:15):
Even though I've been pushing back on you a bit where the technology is like.
But okay, walk me through.
In production, I mean we have a whole, we have a nine step.
We have a nine step technology, our framework at Metaphor.
When we do technology selection for people, there's a, it's a nine step process.
There are nine different areas.
Like we do a technical questionnaire, we do a technical demo, we do a, like we do, we have people, we give them a use case and have them walk us through in production.
(33:44):
Like an example of this.
Like there's a lot of things that we do to get to the right answer and a lot of.
But it all starts up front with business requirements, gathering at a level of detail that is way more than you think you need.
So you know, it starts with doing the self discovery.
Speaker 2 (34:01):
Oh man, I, I love that.
And I think that's a.
You're so right, Ryan.
You do.
You need to start with that self discovery.
You need to push back, ask questions.
Actually ask yourself, do we really need this or is that FOMO starting to set in there, man?
But hey man, I appreciate your time.
I promise I won't.
It won't be five more years unless Chad doesn't open up his wallet and pay for you to come back on.
(34:23):
But dude, how does anybody reach out to you to find out more about what you got going on or what you guys got going on at Metaphor?
Speaker 3 (34:31):
Yeah, always just find.
I mean LinkedIn's the best place to find me.
I don't do I have an X account.
But like I, I can never find myself finding the time or the space to use it.
So just find me on LinkedIn.
Ryan B. Schreiber.
You can always shoot me an email.
Ryan Schreiber, metaphor.net It's metaphor with an F by the way, metaphor.net and, you know, yeah, just shoot, you know, just reach out, shoot me any LinkedIn message.
(34:52):
And I'm always happy to chat.
I'm always here to help and, you know, and, or just message Nick Dangles and just tell them you're trying to get to me because he always likes when people do that.
So thanks for having me, bro.
Speaker 2 (35:02):
No, absolutely, man.
Speaker 3 (35:04):
Ryan, let me give everybody Nick's cell phone number.
Let me give everybody's next cell phone number real quick.
It's 2, 1, 7.
No, I'm just kidding.
Speaker 2 (35:11):
That's funny.
Oh, Ryan, thank you so much for your time today.
That's going to be it for today, ladies and gentlemen.
If you guys can't find Ryan or Metaphor out there, hit me up.
I'll gladly put you guys in contact with them, but that's going to be it.
As always, if you got value in what you heard, subscribe to the show, you guys.
And if you're feeling really ambitious after this one, rank the show on itunes and Spotify.
Because if you saw value, your network's going to see value as well.
(35:32):
I appreciate you guys.
I love you guys and we'll be talking to you.
Speaker 1 (35:40):
Came back with a bank window down Yelling out money in a Got the foot on the gas pedal to the metal when the lane moving fast hey let them all cross if they hate then let them made them make a bigger ball Hey.
Came back with a bank window down yelling now money anything hey oh got the foot on the gas pedal to the metal when I'm get to the back hey Got the foot on the gas pedal to the metal when the lane moving fast hey Let them all cross if they hate then let them hate them Make a bigger balls a.
Speaker 2 (00:26):
What is up, ladies and gentlemen?
We are back.
We are live.
It is the Freight Coach Podcast, the top podcast in transportation, coming to you guys every single weekday, 8:30am Pacific, 10:30 Central, to break down some industry headlines.
But most importantly, you guys provide some actual insight into what you can do with all of this information.
If this is your first time tuning in, welcome.
This is the real side of freight, ladies and gentlemen.
(00:46):
And I do say that before every single show.
And what I mean by that is I only speak with transportation professionals because at the end of the day, you guys, I want to talk to the right individuals who have done what you're looking to do or who are currently doing what you're trying to achieve, so you can take that information, apply it, utilize it, and see a meaningful difference in your business and your life.
Happy Thursday, everybody.
I got a very special guest for you guys here today.
(01:07):
I'm really looking forward to this conversation.
It's a non AI company coming in to talk about AI today.
You guys, we're here, like, how do you deploy?
What do we do with all of this information?
There's so much stuff out there.
Where do you start?
Is it worth it?
Is it overblown?
Where are we at?
And there is nobody who is more qualified to talk about this than my friend Ryan Schreiber.
Ryan, thank you so much for taking the time to join me today.
Speaker 3 (01:28):
Yeah, that's true.
Speaker 2 (01:29):
Yeah.
Speaker 3 (01:30):
Yeah, man, thanks for.
Thanks for finally asking me to be a part of your podcast.
You know, like, for everybody else, I was giving Chris that, like, you know, it's four years or five years he's been doing this and he finally asked me to be on, so I'm happy to do it, man.
Thanks for joining.
Thanks for having me.
Speaker 2 (01:43):
Well, let's just clear some things up.
The zell deposited this morning, so that.
That's why.
That's why we're here today.
Speaker 3 (01:53):
Hundred dollars.
Yeah.
Speaker 2 (01:54):
Yeah, exactly.
That's all it is, you guys.
It's just a small nominal fee.
Chad told me to bill you directly for that to make that happen.
Speaker 3 (02:01):
So.
Yeah, that's good.
Yeah, ABRL is really putting it on.
So thanks, Chad, for.
Thanks, Chad, for sponsoring my.
My seat here on the Freight Coach podcast.
Speaker 2 (02:11):
Yeah, he.
He doesn't realize it yet, but he will be getting an invoice for this later on today and it'll be like per.
Courtesy of Ryan.
Speaker 3 (02:17):
Yeah, that's correct.
So dudes, assistants in the bill to him.
Yeah.
Speaker 2 (02:24):
Oh, man.
So what's good, man?
What's new in your world?
And, you know, and then talking about AI and everything, I think that I've had almost every AI company so far on the show and, you know, there's a lot of really good things that are out there.
I'm very much like, all about technology, automation, where we can.
But, you know, a lot of it is.
(02:45):
It's that deployment, it's that, do I actually need it right now?
What stands stage of my business am I currently in.
Speaker 3 (02:53):
Yeah.
So, you know, just for context, Chris, like, I've been working on AI and machine learning initiatives in logistics for about 10 years at this point.
Back in 2016, I started a company called Freight AI and were building artificial intelligence use cases in logistics.
(03:17):
So, you know, it's something that I have been working on for quite some time and longer than anybody else really, in the industry.
And so there's a lot of these foundational.
Well, the technology's evolved a lot.
And certainly over the last couple years with generative AI, we didn't have generative AI back then.
We just had kind of, we had chatbots and we had other applications of machine vision and NLP and machine learning.
(03:39):
But generative AI certainly has been a game changer and it's changed a lot in the last years of.
Couple.
Couple years.
But like, you know, kind of understand some of those foundational principles, working through, working on that for quite some time.
And then with metaphor, right?
I mean, it's the topic of conversation.
Metaphor does technology consulting for logistics and transportation companies.
And then primarily, yeah, yes.
Scott Watanabe.
(04:00):
I'm at the Hard Rock.
I'm playing, I'm playing.
I'm playing blackjack on the side, buddy.
I'm actually, I'm actually in Charlotte.
I'm not going by Armstrong's office, but I saw Cam yesterday, so.
So, yeah, man, it's, you know, we see the biggest companies in the space, you know, working on AI initiatives.
(04:20):
We're working with the biggest companies in the space on AI initiatives.
And we're working with some of the, you know, we're working with some of the technology companies themselves on implementing for their customers and whatnot.
And so there are a lot of, there's a lot of promise, there's a lot of value in the technology over time.
There are also a lot of challenges.
And the real issue, one of the biggest issues for companies at least making a selection, Chris, is it comes down to kind of the nuance that is in what's going to make one application useful for more complicated use cases and which ones are gonna kind of top out or hit a ceiling.
(04:57):
And so on the front end of like, selecting technology, that's certainly a big problem for people right now.
Speaker 2 (05:02):
What do you think most people get wrong about AI?
And, you know, I want to, like, from a, like a broker, like service provider's perspective.
And then what is being overblown out there by the AI companies trying to sell it into the market?
And I say that with the, with kind of a little caveat of like, if there's one thing that I have seen over the last five, six years in this industry is there's a massive influx in technology companies all promising how they're going to revitalize the industry.
(05:32):
And that really hasn't changed the landscape and the foundation of transportation yet.
Right.
Like, I, I think that we're a ways off from that.
But with that being said, what is being missed out there about AI right now, do you think?
Speaker 3 (05:47):
Yeah, I think the number, really, the number one thing that people need to take over, that people need to kind of realize is that artificial intelligence has been around for quite a long time.
Speaker 2 (06:01):
Yes.
Speaker 3 (06:02):
And that it means more than agent AI or even generative AI.
There's a lot of different ways in which AI affects and can affect your business.
And generative and agentic AI is only one part of that machine learning, something I talk a lot about.
And that's a big part of it too.
(06:23):
But the other is that it is a fundamentally different application of technology to your business.
And to get, but to get the absolute value out of it that you want to, it requires a different approach to technology implementation and business and implementation within the business than other technology does.
(06:47):
I mean, everybody has struggled like with every application of technology, you need to review process and you need to review operating model and you need to do some foundational work there to do some changes in your business.
But there's a, the power of this technology today, especially in the generative and agent space, is that you have to reimagine everything about how you want to do the job to get the most value out of it.
(07:18):
And most companies aren't willing, have not been yet willing to do some of that.
And so those are the two big Things I want people to take away from the AI conversation that have been really challenging to kind of get through to people.
Speaker 2 (07:31):
Yeah, I, I, I'm right there with you, man.
Because I think, like, what, from a consumer standpoint, from somebody who sees a lot of this stuff being released out there, you see some of the marketing behind some of these companies, and it's stating a clear message of, hey, we're going to automate everything.
We're going to make your life easier.
And then as a broker myself who I've interviewed, like, I've demoed like, a lot of these things out there.
(07:56):
And the end thing is it's like, hey, kind of tether your expectations.
We're not quite there yet.
And the messaging out there, and this isn't directed at any one company or not, I don't play that game.
But, like, I feel like as a consumer, I see a lot of message out there.
So I, I resonate with what you're saying there, Ryan, is like, hey, people need to understand, like, it's not there yet.
(08:16):
But I also feel like some of these companies need to tether their messaging out there because it's like, you can't sell a bill of goods that we're going to come in and do this.
And then when you're going through the demo and then the deployment phase, you're like, actually, we're not there yet.
We need another six months.
And then six months turns into another six months and then another six months and it's never there.
Speaker 3 (08:38):
Yeah.
And so I, Chris, the truth is the technology is there actually, like, it's capable of doing these things.
There are three main reasons that they're not delivering on that brand promise.
Speaker 2 (08:53):
Yeah.
Speaker 3 (08:54):
The first is really business strategy and business logic.
The second is data density.
And the third is connectivity and kind of like system.
System.
What's the word I'm looking for?
Speaker 2 (09:09):
Integration.
Speaker 3 (09:10):
Having to deal with antiquated systems, the core underlying technology.
Now, there are different, Some of the different vendors can deliver on the brand promise more or less than others, admittedly.
And that's kind of what I was talking about earlier in terms of how they're architected and how they deal with, like, how much context they try and pack into a message and stuff.
(09:31):
That's kind of particularly esoteric for this type of conversation.
But, you know, but in general, like, the actual underlying technology is there to deliver the types of outcomes and values that we're talking about.
The real challenge in delivering those is actually within the four walls of the brokerage and it's those three things.
(09:52):
So business strategy and business logic, data density and then connectivity are the three main reasons that people are really struggling to it.
And I can go deeper into those things if you want me to, Chris, but the reality that's kind of, I think a big part of the challenge is understanding that is really understanding what is holding some of these technologies back from being as successful in your business.
(10:16):
But that having been said, I will say Chris, that there are no one that I talk to is getting true deep business value out of any of these implementations today.
There are certainly people getting some business value and some incremental business value, but the transformational business value is not yet realized.
(10:38):
And again like some of that is definitely or most of that is actually on inside the four walls of the three PLs and the carriers.
Speaker 2 (10:44):
Do you think?
And I want to talk about connectivity, I want to talk about that.
But I want to put something else out there as well because one thing that I've kind noticed is there's a lot of tech vendors in the AI space that are fighting.
I, I personally think that are overlooking the biggest part of the market.
I think a lot of them are like hey, if you're not big, we don't want to work with you.
(11:05):
And it's like, I mean I just saw the TIA just released the other day like yeah, 75 of brokers do 15 million or less, right.
So it's like do you think that there's.
That some of these companies are missing the mark on where the real market is?
Because not everybody is going to work with, you know, we'll just transport topic releases.
The top 100 brokers and top 100 for hire carriers every single year go down that list.
(11:28):
The top 50 of them are probably building their own product at the end of the day.
So it's like are they really only fighting for 50 to 100 companies?
Because then the drop off from a top line revenue perspective is drastic below that top 100 list.
Speaker 3 (11:43):
Yeah, yeah.
So you know I also work as an advisor to freight tech companies and I deal with this in my business at Metaphora.
Right.
Here's the challenge.
Are they missing a market opportunity?
Kind of.
But there's really two big problems with working down market in logistics.
(12:04):
One is wallet share.
And so there's only so much money that any company has to spend on any initiatives.
Like I was, I use the analogy a lot of times.
It's like, you know, if you promised me, Chris, hey man, I will give you $300 million in six months guaranteed.
(12:25):
I'll put it in an escrow account right now.
So you know it's there.
Like I can prove that it's there.
It'll be there.
It's an irrevocable whatever.
And you're definitely going to get it.
You're absolutely going to get it.
To get it you have to give me $100 million right now.
I don't have a hundred million dollars, bro.
So like it kind of doesn't matter that you can get me a $200 million ROI because I don't have a hundred million dollars to give you.
Speaker 2 (12:47):
Yeah.
Speaker 3 (12:47):
No matter how much you can prove it and how much I trust you, I can believe you.
So wallet share is one of the problems.
There's only so much money to go around and as you go down market that gets exponentially worse.
Right.
And so one of the challenges there is kind of is there the money at these businesses to spread across all the interesting things that they want to do.
(13:08):
Gen logs or highway green screens, you know, their own tms dat, you know, and then you know, something in the AI space.
Whether that's, you know, whether again is that's this agent type AI or other types of artificial intelligence that are like data science related or machine learning related.
That's one problem.
The other problem is honestly it costs just as it's actually more difficult to deal with and sell to a smaller company.
(13:38):
Like so part of the problem is the brokers and carriers themselves that are smaller businesses and like just how they buy and, and how it is to deal with them and get a deal done.
And sometimes going down market is just more difficult.
So I would say that like these companies are willing to work down market.
The more you can make it easy to work with you.
Speaker 2 (14:01):
Yeah.
Speaker 3 (14:02):
You know, and to get a deal done, you know, the better it's going to be for you.
Because admittedly like it is actually more difficult to get a contract done with a top, sorry like you know, a $15 million broker than it is a top two.
I'm working on a contract right now with a top two broker.
Speaker 2 (14:22):
Yeah.
Speaker 3 (14:22):
And it's actually an easier process.
It's an easier sales process.
It's an easier, and it's taking just as much time as it has been or would if I was selling a, you know, a 15 million dollar broker.
Speaker 2 (14:33):
Yeah.
Speaker 3 (14:33):
So those are kind of the challenges.
So.
Yeah.
I mean is there.
Speaker 2 (14:38):
Do you think that in time there will be somebody who kind of comes like I'LL call it.
Not that the Toyota Camry is a bad car but like you know how the Toyota Camry is just, it's reasonably priced, it's nice and it's very reliable.
Do you think that in due time technology will kind of expedite up there to where it's like hey man, we have an, like this account.
(15:01):
We're gonna, we've developed the technology, we've ironed out a lot of this stuff.
It's gonna cost 500 bucks a month, hypothetical example ladies and gentlemen.
But 500 bucks a month, there's your AI.
It's going to come in and do all that.
Do you think that's going to happen?
And if so about how far out are we from something like that happening?
Speaker 3 (15:16):
Yeah, that's, yeah that.
I mean it's absolute like we're there now, we could be there now.
I mean there are so many of these companies to your point like I was actually talking yesterday, I was at the Freight Waves AI symposium or what have you and you know every week I hear about two new companies minimum that are working on this problem and so they're all going to need to find product market fit somehow and some of these solutions are going to struggle with more complex use cases.
(15:52):
But yeah, I mean absolutely like and there are companies now that again will sell down market.
I think that some of it is, some of the other part of it is I think that smaller brokers and carriers they don't need as robust tool set as bigger companies do.
(16:13):
And yet they sort of like they misunderstand and listen again or for everybody who's listening who may not know my background.
I've started three brokerages in my career.
So like I've had to build a company from nothing.
Like I know what it's like to be a 5 million dollar 10 million dollar 20 million dollar 50 million dollar broker.
And so you know you, I did the same thing and did I see everyone doing else doing which is overestimated the complexity of my business and how robust the tool set I needed at any given time in my business was.
(16:48):
And so those exist today.
Looking at more point solutions as opposed to platforms would be a good place to start.
So folks who are focused on a specific use case and then look at other things for AI that aren't agentic or generative really agentic as such like look at back office situation like look at things, look at your P and L and identify areas where you're wasting money.
(17:13):
A quick story that and then I'll stop for a second.
But you know there was one year where it's probably, you know, it was the first or second year of one of the brokerages I started and we did 15 million in top line revenue.
We did a million and a half in gross profit and I took $20,000 to net operating income.
Only $20,000.
And I looked at my, you know, P and L and I was parsing at the end of the year, God, where's the money to grow, you know.
(17:34):
And I had spent $200,000, excuse me, $500,000.
I had spent a third of my overhead, my over, sorry, my GROSS PROFIT ON SGNA 4HR Track and Trace, carrier compliance and onboarding and billing.
(17:55):
Billing and collections.
Yep, that was third of my.
Like there's real ROI there and it doesn't need to be this sexy carrier sales, it doesn't need to be customer acquisition.
Like that was real money that if I could get access to, I could use to grow my business, I could use to invest in sales, I could use to grow revenue.
(18:16):
So look in some of the non sexy places, Chris is where I think that the low hanging fruit is for, you know, smaller brokers today, down market brokers today.
Speaker 2 (18:24):
That is like, I mean you are honestly listing out like kind of my strategy of implementing technology and automation into my operations here.
Ryan is.
It's a lot of the stuff behind the scenes like, and I say this on the show often, man, I'm like 95 of my day as a broker should be automated.
The 5% that I will never automate in my company is the customer experience and the carrier experience because they want to talk to real people.
(18:48):
So if you're one of those AI people in freight who are trying to do automated carrier sales, you're not going to get it from me.
I'm not, I'm not doing that.
And I.
Speaker 3 (18:58):
Perspective, sorry.
Go ahead buddy.
Speaker 2 (19:04):
From my perspective, there's a lot of stuff behind the scenes where I can automate to grow smart.
Right?
Because like that's ultimately.
At the end of the day, Ryan, I need to build a war chest of funding while I'm scaling my business.
I, I'm not, I don't have investors.
I don't want to take on investors because I want to do this on my own.
You can call me, people can call me wrong, whatever they want, but it is a lot more important for me to own 100% of Chris than it is to get a capital investment to possibly expedite five years of my life.
(19:35):
And I look at it as, there's a lot of roles behind.
Speaker 3 (19:37):
I see it very similarly, for what it's worth.
Speaker 2 (19:39):
Yeah.
And I, I just look at it, Ryan, as is.
I'm like, man, there's a lot of stuff that I can automate behind the scenes where it's like, hey, instead of hiring three people for this role, I can hire one, make them more accurate, and I can actually pay that one person more money than I would be able to if I needed to have a manual task and have three people in that role.
And I look at that as.
(20:00):
It's not.
Chris is trying to not hire people.
On the contrary, I'm trying to hire the right people.
So where if there is a down market, I don't have to look at you and be like, hey, I'm paying you too much money.
You're out.
Speaker 3 (20:14):
Yeah.
So I would.
Chris, I think you're painting automation with a little too broad of a brush and talking about automating the carrier experience and the customer experience because they want to talk to a person.
They do.
Sometimes what they really want is their problem solved quickly, like, and they want to be met where they are.
So I'll give you an easy example.
(20:34):
If a driver, it's three o' clock in the morning, the driver shows up to a delivery facility and he's like standing in line to check in and he goes, I don't know what my delivery number is.
He doesn't really care if he talks to a person.
He just wants his delivery number really quickly.
But he also wants to be met where he is.
(20:55):
Right.
Which is why, like, kind of the Download my driver mobile app doesn't work.
So that driver's ability.
And again, we're talking too much about, we're talking all about agents and generative AI, but that ability for that driver to call in quickly, get somebody on the, get a bot on the phone to, and it gives him his delivery number and he can move on with his life like that for sure, is a significantly better experience than they call, he calls you've got to get out of bed.
(21:21):
I actually, there's a transport topics article that came out this week that quotes me saying this exact same thing.
It's.
It's better.
And then you having to get out of bed, turn on your computer, get into the TMS, call them back, it's 15 minutes.
Like, everybody's better off for that experience.
I got to stay asleep.
And the driver got the information answered for him.
And you know, and so I do think that painting automation with too broad of a brush, that there are things that we aren't going to automate or that we shouldn't automate.
(21:48):
Right.
Which is like I used to call my customer, there was one customer, you know, he's still a good friend of mine to this day.
And like I would call and do an NFL pick in with him every week.
Like that's, we literally would do that.
That's.
That's the real relationship.
I'm obviously not going to automate my NFL pick them with him, but I can automate the rate core quote, you know, that is I can automate that if he wants that if he opts into it.
(22:10):
If he doesn't.
And if he doesn't opt into it, I can, I should price in my time.
My time is very valuable, right?
That's why you're paying me to be here.
We talked about this out like, yeah, you know, that's why you're paying me seven grand a year just to bring that joke back.
But you know, it's.
My time's really valuable and it should be paid appropriately, right?
(22:31):
It should be, it should be compensated for.
So if you're going to make it difficult to do business with you, if you're going to require me to call you on the phone to give you the rate quote, if you're.
Those types of things need to be priced into the freight opportunity because I actually do pay for it.
I pay for it below the line.
Brokers P. Ls are deceptively simple in ways that actually hide a lot of the cost of doing business with a shipper and in ways that I think are really damaging if you don't really dig into it.
(22:57):
But yeah, Chris, I think I agree with you.
There's parts of it or I agree with you in part, right.
There's parts of it you absolutely don't want to automate.
Shouldn't automate.
Never automate.
But I do think brokers, I see brokers frequently rather paint automation with too broad of a brush.
And you really need to break down what's the situation and what are we trying to accomplish and what's the best way to do that and where do people want that and then how do I make sure I meet them wherever they are, if they want it by email, if they want it by phone, if they want it by SMS or they want to be, you know, if they want to be top.
(23:29):
If they want to buy carrier pigeon, like great let's meet them where they are and get them that and price it in.
Speaker 2 (23:34):
Do you think people in freight are painting AI with too broad of a brush because they've been told that it is way more capable than it actually is out there in the market?
Because like I see where you're coming from, Ryan, 100%.
And like you do bring up a good point, right?
Like that automated, hey, what's the delivery number?
Stuff like that.
Like we don't have enough time.
But I could go down the argument that like a real broker would have made sure that driver had that information prior, you know, yada, yada in form.
(24:01):
But I look at it is we're, we're at a point where I think one of the big struggles that AI companies are going to see over the next two to three years is they are going to have to fight against AI tools that are out there in other facets of a person's life and they're going to instantly make that correlation.
(24:22):
Because a lot of people, when, you know, if you've ever worked in sales, your prospect tends to kind of make up their own story on what they think you're saying is.
And I feel like it's on you as a sales rep to make sure your messaging is crystal clear on what your product is actually able to do.
Speaker 3 (24:38):
Right?
Yeah.
Yes.
I mean, I like, no, I guess I agree with your underlying point.
Yeah, I don't think that I really push back on the over promising piece of this because it really again, like the biggest reason that brokers struggle, the number one reason, as I said earlier, it's like business strategy and business logic.
(25:03):
Like these companies, I mean even the biggest companies in the space, they struggle to pull out the business.
The complex business logic that goes into their decisioning, it's what you would call implicit, right.
Like it's that institutional knowledge that's just like, well, I just know what to do.
Okay.
But you know, to think about, you know, agentic and generative AI like, and then actually really like any types of machine learning, like there's, you have to know the information to get good outcomes.
(25:34):
Like you have to train.
Literally like everybody talks about training models but like you have to train a human just like you have to train a, you know, like an AI model and the information has to be available.
Like imagine I came to you and I was like, Chris, I want you to quote me on a shipment.
Okay, well what, where's the pickup and where's it deliver?
(25:56):
I can't tell you.
Okay, well, when does it pick up and when does it deliver?
I can't tell you that either.
Well, how long of a transit is it?
Yeah, it's like, I don't know, it's somewhere between like 600 miles and 6,000 miles.
Okay.
What's the commodity?
What's the equipment?
If you can't answer any of those, like, you know, if you can't answer, the more of those questions you can answer, the better I can get better results I can give you.
(26:19):
And when I talk about things being implicit, sometimes things aren't available to these applications.
That goes to data connectivity and data density and some of the other stuff.
Some of these things aren't available to the applications in a way that allows them to deliver the business value you're describing.
Now, I do agree that at some level, like as a salesperson, if you really kind of, or like as a company, like you want to disqualify customers as much as you qualify them.
(26:49):
I walk away from customers sometimes that I don't believe will be successful working with me and with Metaphora and with other businesses that I have.
But at the same time, like, Chris, if you bought some, you got sold.
Like, that's on you.
Like, their responsibility is to try and sell like you're, they're trying to sell their product and like, they should care, quote unquote, that you're going to be successful, but really, like, the world doesn't work on should.
(27:17):
This is capitalism, as a lot of people like to point out all the time.
So, like, it's on you, bro.
And so, yeah, man, do your own due diligence.
Are you in a position to articulate the business logic that's required?
Probably not.
Or the business strategy.
Like, how do you decide when to take a 9pm appointment, delivery appointment, you know, when you wanted 9am like, sometimes you'll ask for a reschedule, sometimes you won't.
Speaker 2 (27:40):
Why?
Speaker 3 (27:41):
In what scenarios?
You know, if you don't have, if your systems can't connect to each other, do the due diligence to figure out what these applications need to be successful with you when talking to them and then figure out if they can do that.
Because if they lie to you, that's fraud, right?
But if you didn't do your due diligence, which is what I see more frequently than not, when people are upset about how they, the outcomes they got with technology, it's that they didn't do their homework.
(28:07):
They didn't ask the right questions.
They didn't ask the right depth and level of questions.
And.
And so then they didn't get the value out of it.
So, I mean, I'm sorry that I'm pushing back so much on this concept of, like, technology is not there.
Speaker 2 (28:19):
Because, Ryan, here's the thing.
Speaker 3 (28:21):
This stuff, it largely is.
Speaker 2 (28:23):
Yeah, this.
This needs to be said because, like, nobody's asking these questions out there, man.
And then they find themselves in.
In that exact position you're talking about right here where they feel like they got.
And now they're sitting there and they're on.
Like, they're blaming other people because they never stop to take five seconds to be like, hey, where am I at in the business?
(28:44):
Do I actually need this?
Why am I signing this contract?
And, you know, again, man, you're.
You're right in your.
In your stance here of, like, hey, sales reps are there to sell.
If you got sold, that's on you.
But again, that, like, that.
This is the entire premise of the show, Ryan.
This is where real conversations need to be had.
Because, like, we need people to think about this stuff outside of how they're currently thinking.
(29:05):
Because otherwise, man, one thing that.
Again, it's not my responsibility to feel bad for people, but I'm a human being.
I feel bad when I hear from people, like, yeah, man, I got out of $30,000.
And, you know, like, as a business owner who's bootstrapping, it's easy to hear that.
And that's why I'm like, I want to have these conversations on this show because hopefully somebody hears this, Ryan, and.
(29:25):
And they think about it differently when they go into that next demo.
Speaker 3 (29:30):
Yeah, I.
So, you know, bro, like, it's not just about AI, man.
This is like Beauty and the Beast.
It's a tale as old as time.
Like, this is.
This is.
This is the story of people picking technology for quite some time.
And admittedly, like, it's the entire reason that I have a business, because people need help picking technology.
They need help building technology.
They need help implementing technology.
(29:53):
So, I mean, the key is part of what you just said.
Why do I need this?
Why do I want this?
What am I trying to get out of it?
Chad, you talked about.
We talked about Chad Olson earlier.
Chad and I have this conversation frequently that, like, he'll also walk away from customers that he doesn't believe will be successful with this product.
Because, you know, there is a.
There is a FOMO element in freight tech where it's like, everybody else has this.
(30:16):
I should get it now.
I think that, I think that people also go the other.
Excuse me, I see people also go the other way of like rejecting.
Rejecting stuff just for the sake of it because they don't need to do it.
Because I still use fax machines and.
But like, you know, but.
(30:38):
But the reality is I also feel bad.
I give a lot of.
I give away a lot of free advice.
Like I, you know, I give away a lot of free work of.
Because I want people to be successful.
Number one.
Why are you doing it?
Ask that question, what the business problem you're trying to solve.
Speaker 2 (30:54):
Yeah.
Speaker 3 (30:55):
Don't not what's cool technology?
There he is.
You know, there's.
What's the business problem you're trying to solve?
Why are you trying to solve it?
And how do you.
What's the best way to solve it?
Here's the thing, here's the other thing about AI actually that I want people to take away that they're missing.
It's actually the worst.
(31:18):
It's the worst is the wrong way to put it.
It's the.
It should be the last solution to many of these problems as it relates to technology.
It's incredibly powerful.
I love is.
It is.
It is incredibly powerful.
And it's so powerful that actually there's.
You should have tried everything else before you get to artificial intelligence or machine learning or whatever else it is because, you know, we see it in reporting a lot.
(31:45):
Like, you could do a lot with machine learning, but you have to be able to ask really interesting questions that are different than you could get from a BI dashboard.
And, and so it's probably the wrong way to solve the problem.
It's just cool and sexy and seems neat and also seems easy.
And there's ways in which it is easier than other technologies.
And I wrote like, I actually wrote an article for TIA about this like three or four years ago that natural language processing is the.
(32:09):
Is kind of like the easy but solution to certain aspects.
But like, and then, and then get into what do I need to be successful?
What do I need from a vendor to be successful?
I see this in TMS selection just as much as I see it in AI.
What do I need from a vendor to be successful?
I might need a vendor to help me suss out the business logic if they think I'm coming to the table with all of the answers.
(32:34):
Like the deep, deep answers.
Like, I know how my business works, but like, really be able to articulate again Why I might take this 9pm appointment but other times I might reschedule it because this carrier, because this customer, because I missed this load yesterday, blah.
All of those things that go into that.
If I need somebody to help me suss that out, I need to vet the vendor for how they're going to do that.
(32:55):
What does customer success look like?
What does implementation look like?
What are the activities that you are going to do?
How are you going to do this?
You know, literally walk me through.
Just like a job interview, walk me through a scenario where you did this with someone.
Show me this.
In production, I mean there is vaporware out there, Chris.
Like I'm not going to pretend that there's not for sure.
(33:15):
Even though I've been pushing back on you a bit where the technology is like.
But okay, walk me through.
In production, I mean we have a whole, we have a nine step.
We have a nine step technology, our framework at Metaphor.
When we do technology selection for people, there's a, it's a nine step process.
There are nine different areas.
Like we do a technical questionnaire, we do a technical demo, we do a, like we do, we have people, we give them a use case and have them walk us through in production.
(33:44):
Like an example of this.
Like there's a lot of things that we do to get to the right answer and a lot of.
But it all starts up front with business requirements, gathering at a level of detail that is way more than you think you need.
So you know, it starts with doing the self discovery.
Speaker 2 (34:01):
Oh man, I, I love that.
And I think that's a.
You're so right, Ryan.
You do.
You need to start with that self discovery.
You need to push back, ask questions.
Actually ask yourself, do we really need this or is that FOMO starting to set in there, man?
But hey man, I appreciate your time.
I promise I won't.
It won't be five more years unless Chad doesn't open up his wallet and pay for you to come back on.
(34:23):
But dude, how does anybody reach out to you to find out more about what you got going on or what you guys got going on at Metaphor?
Speaker 3 (34:31):
Yeah, always just find.
I mean LinkedIn's the best place to find me.
I don't do I have an X account.
But like I, I can never find myself finding the time or the space to use it.
So just find me on LinkedIn.
Ryan B. Schreiber.
You can always shoot me an email.
Ryan Schreiber, metaphor.net It's metaphor with an F by the way, metaphor.net and, you know, yeah, just shoot, you know, just reach out, shoot me any LinkedIn message.
(34:52):
And I'm always happy to chat.
I'm always here to help and, you know, and, or just message Nick Dangles and just tell them you're trying to get to me because he always likes when people do that.
So thanks for having me, bro.
Speaker 2 (35:02):
No, absolutely, man.
Speaker 3 (35:04):
Ryan, let me give everybody Nick's cell phone number.
Let me give everybody's next cell phone number real quick.
It's 2, 1, 7.
No, I'm just kidding.
Speaker 2 (35:11):
That's funny.
Oh, Ryan, thank you so much for your time today.
That's going to be it for today, ladies and gentlemen.
If you guys can't find Ryan or Metaphor out there, hit me up.
I'll gladly put you guys in contact with them, but that's going to be it.
As always, if you got value in what you heard, subscribe to the show, you guys.
And if you're feeling really ambitious after this one, rank the show on itunes and Spotify.
Because if you saw value, your network's going to see value as well.
(35:32):
I appreciate you guys.
I love you guys and we'll be talking to you.
Speaker 1 (35:40):
Came back with a bank window down Yelling out money in a Got the foot on the gas pedal to the metal when the lane moving fast hey let them all cross if they hate then let them made them make a bigger ball Hey.
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