Why Appointment Scheduling Is One of Freight’s Sneakiest Bottlenecks

In this episode of Everything is Logistics, Blythe talks with Tom Curee, President at Qued, about why freight appointment scheduling is still one of the most stubborn problems in logistics.

Qued focuses on appointment scheduling for brokers, carriers, and shippers. The platform connects into existing TMS workflows so users can automate scheduling, manage exceptions, and build trust through visibility instead of forcing teams into another portal.

They cover:

• Why appointment scheduling creates so much back-and-forth for logistics teams
• How many times a single appointment usually gets touched
• Why user trust matters when automating freight workflows
• How Qued uses audit logs to show every step of the scheduling process
• Why the best appointment is not always the appointment a team thinks it wants
• How natural language rules help Qued scale complex scheduling logic
• Why logistics companies should prioritize tech that improves the customer experience

This conversation is part of the CargoRex AI Use Cases in Logistics guide, featuring real examples of how logistics companies are using AI across freight, warehousing, procurement, visibility, and operations.

Read the full guide here:
https://cargorex.io/research/ai-use-cases-in-logistics/

LINKS:

Qued:
https://qued.com

CargoRex AI Use Cases in Logistics Guide:
https://cargorex.io/research/ai-use-cases-in-logistics/

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Transcript

SPEAKER_02 0:05

Welcome in to our Cargo Rex Guide series for AI use cases in logistics. And we are joined with Tom Curry. He is the president over at Qt and we're going to be talking about the issues around appointment scheduling and how Qt aims to solve that problem. So Tom, welcome in.

SPEAKER_00 0:23

Yeah, thanks. I'm so glad to finally connect. I know we've talked about doing it for a long time. So we did it. That's a victory right there, right?

SPEAKER_02 0:31

Likewise. Well, you're we are just getting started. We haven't done it yet. So I'm hoping, you know, with this conversation, we will knock it out of the park for these AI use cases because that's where you know the industry sort of finds ourselves in, where we have over the last handful of years, tech has entered in on the scene. Not entered in onto the scene, but it's really the mass adoption of it. And so as we start solving some of these problems, more problems start to pop up. And that's where a company like QED could come in and solve those problems. So give us a general landscape of the main issues that QED is is created to solve.

SPEAKER_00 1:07

Yeah, so so in our in our world, all we're here to solve is appointment scheduling. Um we're fortunate in the fact that we became very committed to the problem as opposed to committed to the solution. A lot of these players that come out here, they get very committed to the solution and then they try to figure out which problems they can apply it to. That's not our approach. Um, Prasad and I early on, we were very committed to the problem of appointment scheduling. So all we focus on is how do we go deeper into the problem. So we work with brokers, we work with cares, we work with shippers, we work with everyone who touches appointments at some level so that we can get connectivity to those platforms or those uh locations, but we can actually get better appointments. Um, there's a there's a lot that goes into that. There's a lot of challenges, there's a lot of things that we're learning on the dock as we continue to get deeper into that problem. But all we do is appointment scheduling. And so the nice thing for me is when people say, Can you tell me about all your different products? I can say, Yeah, it's appointment scheduling. That's what we do.

SPEAKER_02 2:04

And so for a typical is there a typical shipment or a typical load? Let's think that there is a typical load or a typical shipment. How many appointments are are regularly scheduled for that shipment?

SPEAKER_00 2:15

There's a lot of different things that can happen. Most of the time, there's a pickup on both sides. Okay. Every now and then, right, you've got some first come, first serve facilities where you may not have to schedule, but you might have to give them a heads up that you're gonna be coming in that day. Even our drop trailer scenarios, um, there's typically some sort of notification that has to be sent out that says, hey, we're gonna drop on this day. So we typically say if you're talking about a standard shipment, there's usually two appointments. Now, where it gets a little more complex is of course in the multi-stop or the consolidated freight world that we do a lot of. But the other side of it is how often team members actually have to touch a single appointment. We'd love to say that, hey, you schedule an appointment, appointment is confirmed, that's the end of it. And then you got to remind everyone we're in trucking. Um, it's never the end of it. Um, there's always changes, there's always updates, there's there's things that happen in transit that you have to engage with that. And so our customers typically tell us they typically touch an appointment around 2.8 times. So it's not just that one appointment, right? It's that it's that back and forth. It's oh, I've got to add a PO now to that appointment because the the PO's changed on the shipment and all of that that continues to stack up. And that's what creates so much of the bottlenecks is the back and forth on all these different changes and such.

SPEAKER_02 3:33

And so, how do you tap into each of those different ICPs? I mean, you mentioned brokers, carriers, shippers, and so with all of those different ICPs, I imagine that that's different processes for for each of them.

SPEAKER_00 3:44

Yeah, there there is. There's a so there's a few different things that we've kind of always said to our team is that we need to know more about our problem than we know about our solution. And so we spend a lot of time with problems. You know, when I talk about being on the dock, I mean, just a few weeks ago, I was on a dock, I was sitting with their schedulers who were who are handling with requests from carriers and brokers and and private fleets who are who are bringing these inbound in, and then they're figuring out where do I want to place them, how do I want to stack my slots and being at the in the trenches, like right where they are. Like, I'm a big guy about being in the trenches. Like the the closer you can get to the floor, the closer you can get to what's actually happening, the better you are. You learn so much more about the people who do that. So that's how we stay committed to that is because we're constantly working with end users, not always the C-suite who probably hasn't scheduled an appointment in 30 years, right? But but literally the people that are executing on complex shipments every single day, those are the people you want to talk to because you can learn more about the problem. And then you can talk about okay, what does that solution really look like?

SPEAKER_02 4:55

And that was one of your case studies listed on the CUDE website is uh uh forgive me if I'm mispronouncing this or if it's GIX or GIX. Is that the G I X, yeah.

SPEAKER_00 5:05

Yeah, yeah, okay. G I X, yeah, yeah, yeah. You're good.

SPEAKER_02 5:08

But you saved uh the study showed that 22 hours were saved per week per person. Now, is is that a best case scenario, or is that what you're seeing across different ICPs?

SPEAKER_00 5:20

I I will tell you, um, that was uh an early case study from early Q days, which means that's conservative, um, which is great, right? Um, and so most people will say, hey, if you can give me 22 hours, you're crushing out of the ballpark. Well, most of our customers, we see 90 plus percent adoption. So if you think about the time that a user has spent, especially if you've got people that are devoted to just scheduling, where they could be devoted to more revenue-producing work or impactful or getting closer to the customers in these scenarios, it can cause a pretty significant shift. And we're talking, you know, when you start talking about 90% of their work um being able to be transitioned through connectivity to these just platforms, it's pretty significant. So I've always been a uh a bit of a uh underpromise, over-deliver person. And so, yeah, that's a very realistic view of what can happen, but significantly even more through that, through across our customer base today.

SPEAKER_02 6:20

And so when it comes to, I guess, pitching these uh this efficiency, what does uh is there any pushback generally from this in the trenches staff that as you mentioned? Is it is it is there uh I guess a hurdle that you have to cross to get people to kind of change their ways or to get them to think about things a little bit differently?

SPEAKER_00 6:42

Yeah, I think if I was a really effective salesperson, I would say, no, it's always really, really easy and everyone loves it and everyone immediately does it. And so it's a it's a huge win. But I'd be lying to you, right? There, there are there are certainly pockets of that. Um, we have pockets where we have customers that they have team members that have been doing this and they hate, they hate spending the time going out to these different platforms, trying to figure out how to schedule. And so it becomes a very, very quick win, easy win. There's other pockets of people that say, I've been scheduling appointments for 20 years. This is what I do, this is what I know. That comes with a lot of fear. And so we spend a lot of time building trust with users. Um, like I one of the things I'd always say is you can't trust what you can't see. And that's typically the way it works for people who've been doing something for 20 years. They're used to seeing it, they're used to touching it, they're used to feeling it. And so when you take that away and you say, no, no, no, no, trust Q. Cute's gonna automatically do it. That's not there, right? They're used to touching, seeing, feeling. And so for us, we try to do a lot of things in the process to help them come along that journey. Sometimes that means being on-site with them. I was just planning an on-site with a customer here for next month where we're gonna go and we're gonna sit with those end users who have been scheduling for 20 plus years to help them get comfortable, but also bring in executive leadership to help them feel very comfortable about what that means for them as they continue to adopt this new piece of technology.

SPEAKER_02 8:05

Yeah, because that's what we hear for a lot of different AI use cases as well. I don't want to train my replacement. I don't want to be put out of a job. And I think in in some industries, that fear is legitimate, especially on the you know, the marketing side of things. But on in this area, it feels like this is something that nobody really wants to do unless it's those, you know, those exceptions that have been doing it for 20 years. And and how do you handle sort of the the conversations to approach those people to adopt and instead of, I guess, the the the pushback that you get. Are there any, I guess, maybe common questions or common concerns that that you've seen with talking to customers of their how they fear this technology and maybe how you're overcoming that fear?

SPEAKER_00 8:50

So one of the things that we've been really intentional about is targeting those employees first. Um it seems like a lot of companies, when they're bringing a new piece of technology, they want to take their poster child, their champion, and oh Jane, Jane loves every she she loves trying new things, she loves figuring things out. That's great. But what about Joe? I want Joe. I want Joe who's like, I've never used it, I don't want to use it. Because if I win Joe over, guess what? Everyone will follow what Joe does. And so we've kind of taken the approach of give me your your most challenging team member who has struggled to adopt technology. Let me win them over. And as a result, the whole team ends up coming along, right? I'm gonna maybe date myself a little bit. There's uh there's an old serial commercial, uh, the life serial commercial, where no one wants to try it and they they pass it over to Mikey and Mikey likes it. Oh my gosh, Mikey likes it. So then everyone likes it. That's my approach, right? Like, let's find the people who actually really struggle with that. And we have customers who have literally said, Tom, I'm not gonna lie, this is gonna be very difficult for you. This person does not like anything. And I'm like, please, I love that challenge. And if you can win, like, look, you've got to build a layer of trust. So we talked about what are your fears? What are your concerns? One of the common questions, uh, it's almost the last question. Several of our customers have probably heard me ask this is when we're on a call with the ops team and they're first looking at Q, they're trying to feel it out. You know, I'm I'm the one that's always saying, Hey, please get me to your ops team as fast as possible. I appreciate you that you want to sign and this sounds great. I want to talk to your ops team before you make that final decision. And the last question I typically ask the ops team is I say, okay, this is your chance to tell me my baby's ugly. So tell me, tell me why my baby's ugly and tell me why this won't work for you. And that breaks down and we have an honest conversation about what won't work and why it won't work. And then we can be honest enough to be able to say, you're right, that's going to be super challenging. But let me, can we dig in a little bit more so I can understand that? Or we can say, hey, good news, you're the fifth person to bring that up. And let me show you what we did with these other five. If you can address those fears as quickly as they come up, as opposed to waiting a week or two weeks or three weeks, it just changes the perspective for the users that you're working with.

SPEAKER_02 11:21

And so you've mentioned uh working in the trenches. You mentioned working and talking to the executive team. I I'm curious, before the conversation ever starts, what are maybe some things or red flags that a company can notice that will make them think I should probably reach out to Q'd?

SPEAKER_00 11:40

I think one of the things that we typically see is as companies continue to scale and grow, um, if they find this problem where they're continuing to add headcount around the scheduling problem. We have customers that we've worked with that um actually some of the the moment that they started working with cued was because they had a team member that leaved or a team member that was being promoted. And that was their trigger event to say, okay, I don't want to backfill. I want to fix this problem. And so the people component is one side of it. The bigger component, and the reason why a lot of our customers are coming to us today is they're getting stuck with bad appointments. We all know that if you have a load and it's a Friday for a Monday delivery, that's wildly different than a Thursday for a Friday delivery, right? Those are two very different shipments. And when it comes down to the RFPs and being able to accept lanes, your ability to secure prime appointments, it makes or breaks these shipments. We often tell people you can't control rates as much as we want to believe we do, you can't control capacity as much as you might believe you do. The only thing you typically have influence on on a shipment is the appointment. And it's wild that it's one of the things that we've done the least with in our industry is that we really haven't touched it. We really haven't evaluated, we haven't tried to figure out how do we solve and make this better. And so if you find yourself struggling with some of these shipments that you see your competitors moving, you have to figure out a way, how do I secure these faster than the way my team's been doing it today? What does my scheduling duration look like? Like, how long is it in my TMS before I'm actually initiating and scheduling these appointments? Because your customers expect you to be able to get appointments on an RDD, right? They expect if you come back and you say, I can't deliver when it's supposed to because there's no appointments, and they say, you've had this shipment for three days and you're just now telling me this, that's a tough conversation to respond to, right? But if you're immediately triggering as soon as the stops come into the TMS, well, then you've got a pretty solid case and you can work collaboratively with a customer to come up with a long-term solution.

SPEAKER_02 13:45

So what does the, I guess, the the next phase look like? So you've right, I'm a I'm a customer, I've recognized I have a problem, I I want to solve this problem. What does maybe the onboarding process look like? What do I have to prepare on my end of things in order to hit the ground running?

SPEAKER_00 14:01

Yeah, so we're really fortunate. I mean, we've integrated with the majority of the TMSs that are out there to date. Um, most of our customers can actually be live scheduling within a week or two. Um, it's not a very long process for us. And what happens is on our side, you know, we've got a full team uh devoted to customer success. And that group, what they do is they pair up and they they analyze your entire freight network and they're able to identify where are you scheduling, how often are you scheduling, which platform should we be connecting to, where are there gaps in your scheduling today that maybe you don't even recognize, you don't even realize that that's it's happening every single day, so that we can kind of aggressively attack those. When we start working with customers, it's uh I was on a call earlier today, and you know, customer went live, I think it was this week, and they've already scheduled hundreds of appointments fully automated. And the speed can go fast. I think the the problem that we have in technology is a lot of people don't want to commit to a solution. I think when we find people that are committed to solving problems and they commit to a solution, they they fully engage, right? They're not kind of like it's it's not a side project, it's not something they're thinking about doing. They're they're playing with it as they have time. No, no, no. They're putting resources to it. They're saying, no, no, we want to ramp this up, we want to get the full value out of this product, and then they move on to their next thing. And so I think that's what we continue to see is people who are ready to engage, they can really ramp up at a much higher speed than someone who who wants to um, what's the word I would use? Uh they want to tinker, right? There's there's tinkers who like to play with things and do things, but then there's doers who really want to execute and want to fully ramp up and and scale their organizations.

SPEAKER_02 15:47

Now, for a lot of folks who have used you know LLMs, ChatGPT, Gemini, Claude, uh all of those main players, you know that well, historically they have hallucinated. Sometimes they they make up things. And uh and so when people hear AI, it's either the fear of it's gonna get something wrong or it's gonna take my job. Now, when I hear a number like, you know, a hundred loads or the a hundred appointments that they they've scheduled in a week, how do you know that all of those are actually efficient and are gonna get the job done?

SPEAKER_00 16:20

So one of the things, and and I mentioned this earlier, I'm a strong believer of uh users can't trust what they can't see. Users, um, it's the same thing with any of these AI platforms that exist today, is that there is an element of trust that has to be built, but it has to be earned. Um, think about a new employee that comes in your team. Um, I don't immediately trust them to go meet with my largest client, right? They earn that respect by working on other accounts and learning the business well enough to say, yes, this person should go in front of this client, right? That's naturally what we do. And so the way you learn that trust is you see them doing, you see them performing, you see them acting. You don't just put them in a back corner and just wonder, are they really doing what they do? So we we make a lot of this stuff visible to them so that we get that user trust up front. In our world, um, a part of that is like a really, really successful audit log where you can see every single screen, every single digit, every single button. You can see everything that happens through that process. And this is also a nice little protection for our customers because we've all been there. You show up to a facility, you have a scheduled appointment, and the facility looks at you and says, You don't have an appointment here. Well, nice. I I've got cued, so I can actually go back and show you the entire audit log and every screen and everything that we've ever done to be able to confirm those appointments, right? And then they say, Okay, yeah, we'll make it happen, right? Uh and so like we have to we have to help people trust these systems. Um, and I think organizations who just expect blind trust from people, they just don't know how people work. Um, people just don't do that, right? They have to that you have to earn that respect. And so we give a lot of visibility to that. The other side of it is we have a lot of validation built into our system. So imagine an appointment comes back today, it's confirmed, it's dropped in the TMS. We do a transit calculation on every single appointment we get. Um, and we validate and say, is it feasible for a driver to be able to accomplish this? And we have customers that have been able to prevent service failures because of that transit validation, right? That transit validation is gonna say, whoa, whoa, whoa, whoa, whoa, you got the appointment that maybe you wanted, but there's no way this driver's gonna be able to execute on this. And here's why. The users can make an impact on that before that there's an actual service failure, which then costs you revenue and all the things that come with that. So uh for us, it's all about you you've got to present the information to users so that they can have that level of trust. Otherwise, in the back of their mind, they're always gonna wonder is Qt really doing what it's supposed to be doing.

SPEAKER_02 18:58

Walk me through what the, I guess the the user process looks like through a user dashboard. So you you've onboarded, you're you're already a customer, you you've set some appointments. What how are you managing exceptions? How are you managing maybe new features? What does, I guess, sort of the the tab or the dashboard look like if I'm a user?

SPEAKER_00 19:18

So here's what's what we love about what we've tried to do in this space. We are not trying to be the portal of all portals. If you pull a hundred uh transportation professionals and you ask them, how many of you would like another portal? The hands aren't going to be like waving that yet, right? And so we actually integrate completely into the TMS. The users work where they work. Uh, I'm a big believer of stop trying to send users to another, another dashboard, another widget, another login, another thing, right? We don't need more things. We just need to be able to execute, right? And so what we've done is we've built our workflow to exist 100% within that TMS. So it feels very natural. It almost feels like we're a part of the TMS. I mean, think about EDI. You don't go to anyone today and say, hey, show me your EDI. What am I gonna show you, right? It's all it's it's in back into the system, all that data's flowing through. So that's the way that we've tried to build it. So it's right in the TMS workflow for users. You're gonna have exceptions, right? Those exceptions can be handled in a couple different ways. Sometimes they're directly within the TMS. We have some customers that handle their exceptions through Slack or through Teams or through email or through some other sort of chat functionality that they like to use. So we really believe in like go where the users are. Um, we don't want to say, hey, we're gonna send you here. We like to go to them and say, well, where do you go today? What do you do today? What does that look like? Because if we can find the most natural process flow for them and we can just fit right into that same natural flow, user adoption goes through the roof because they're not they're not fighting some new process and trying to learn some other things. Oh, it's it's just like I was already doing it. It's just instead of me jumping and doing these other 16 steps, it's just one button or one trigger right here on my TMS.

SPEAKER_02 21:07

And so how does that, I guess, sort of uh how does the AI layer filter on top of that? Because I'm imagining a dashboard where I can, you know, view the exceptions, I can view maybe some improvements or some things to think about a little bit differently, all of the successes, which is great, maybe the failures as well. How does AI layer into that to make me more efficient on an ongoing basis?

SPEAKER_00 21:32

So it does a few different things. The first layer is it handles, so in our world, it's not just scheduling in web portals, right? You're scheduling via email, you're scheduling via phone call. You're every possible mode of scheduling is what we do. So in that scenario, right, we are leveraging AI to automatically form emails and then respond to requests and respond to details, read those emails and push them back into TMS. So all that back and forth that a user would do, like a typical A typical appointment will require about four to six emails to get confirmed. And I count those like thanks emails because guess what? Your team's clicking at a thanks email and they're moving it somewhere and they're what what it's still work. It's it's it's wasted work, but it's work. So all of that our AI is able to do in the background. Uh all that communication, all that, all that, all those updates. The other side is, of course, a voice making those phone calls, right? We have voice agents that actually can go out and schedule appointments. We do it multi-stop deliveries all day, 15, 16 stop loads that we're scheduling for right now. The other side is using your data to inform what's really the best appointment. Because today, the way it has always worked is Jane tells me I always want a 9 a.m. appointment at this facility. And so whoever Jane trains to the day they die, they want 9 a.m. 9 a.m. is all they've got in their head. I want 9 a.m., 9 a.m. Well, what they don't know is that 9 a.m., there's actually a shift change that takes place. And that 9 a.m. truck actually takes 30 minutes longer to unload than the truck at 9:30. So you're better off taking the 9:30, or you're better off taking the 8:30, or whatever it is. So we learn these patterns. And so instead of just automatically taking 9 a.m., where maybe you've had a little more service failures or maybe you've had a little bit more delays, we're able to adjust that so that we're actually confirming for the right time, not just the time you thought was right.

SPEAKER_02 23:26

And then how are those, I guess, that that feedback delivered? Is it in the app of choice or is it maybe some summary reports? How how do they know what to get better?

SPEAKER_00 23:36

What happens for us is our system can automatically do that within a tolerance range. So our customers, they set tolerance ranges with us and they say, hey, this is an appointment I want, but really I want within X amount of range of that. Well, that range, what it does is allows us to dial in their appointment selection without users having to get involved. So you think about, you know, we've got customers that we're scheduling, you know, hundreds of thousands of appointments for. If we were always triggering them to say, hey, you really should have thought about 930 instead of nine, they're not, they're not gonna tap into that, right? That's gonna be way too much work, way too much user engagement. So that's why we use that tolerance band that we are able to say, okay, we can do whatever we need to within this ban as long as we determine what's the best appointment for them based off of the identity of that shipment.

SPEAKER_02 24:22

And so as you're thinking about, you know, sort of what comes next in your platforms, is it is it really just coming directly from the customer itself, or is it kind of the overall sort of AI landscape of, oh, this, you know, Chat GPT just dropped a new model, maybe we want to integrate that? Or how does the, I guess, the speed of the adoption and of the evolution of AI fit into the the cued roadmap?

SPEAKER_00 24:49

Yeah. So one of the one of the biggest things that we've done with our customers that we just rolled out in the last month is our ability to leverage natural language prompting to create customized rules. So if you think about transportation, there's a lot of complexity in the appointment scheduling process. I think uh the reason why a lot you don't see a lot of competition in the space is because it is crazy complex. Most of these tech companies that are VC backed, they want a simple, repeatable process that they they can rubber stamp this thing and then push it all the way out. Well, appointment scheduling doesn't look like that. Um, and so what we've done in the way that we've built our product is we've allowed users to use natural language to build customized rules. So, for example, we have a customer that every time you go to schedule at this Costco facility, what you have to do is you have to look at the commodity. And if the commodity uh is blank, then we're gonna automatically assume that it's meat. If it's not blank and it's and the PO starts with a 1052, then we're gonna mark it as a palletized load 1052. That sounds stupid, right? That's a lot, that's the stuff that people are looking at every single day. And so in the past, what would happen is if you were trying to automate scheduling like this, you'd have to reach out to a developer and you'd say, Hey, developer, here's this really custom rule. We would detail it all out, it would go to them, it would go into a sprint, takes a couple weeks, gets on the back end of the sprint, gets deployed. Then you take it out to the user and the user gets to test it, and they say, Yes, this works. So you're talking three weeks or so to be able to get a rule like that deployed. Now our customers actually have the ability where in our back-end system, they can just type a rule the way I just said it. Every time I get this load, if the commodity is blank, we want to we want to schedule for a meet door. If it's not meet and the PO starts with 1052, market has a palletized load, 1052. They hit test and it immediately writes the code to create the rule, and it can be deployed in a matter of minutes, right? So this the way that we're able to scale scheduling for customers, that's the real problem that we're solving. People can build automation to automatically send an email. They can write it write an RPA to be able to go out and automatically say what they can't do is scale it, and that's what we really bring when it comes to how do you fix scheduling? You have to be able to scale it across your organization. And leveraging AI to be able to write these natural language prompts to then code into the system is a significant shift in how we can deploy and speed up this.

SPEAKER_02 27:21

With all the companies that you speak with, what does, I guess, sort of the modern scheduling department look like when they're using Q'd? And then how do you layer in all of the different cost structures that seem to fluctuate? There's some examples of what I'm hearing where developers are asking for a salary and then they're asking for a certain amount of token budget. How are companies, in in your experience, kind of adjusting their hiring for those different economic units?

SPEAKER_00 27:53

So there's a few things that we're saying. First off, a lot of these employees are switched to exception handling work, right? You're really focused on the exceptions, is what you're trying to do. Um, and that that changes the conversation you're having. What we what we see a lot of appointment schedules getting engaged with now is let's say because they're not having to go out and manually schedule all these anymore, they have a time to actually now look at your your scheduling book. Uh, which locations are your problem child? You know, we can identify, hey, here's a location that every time you submit an appointment request, it takes up to 32 hours to get a response back. Well, those are the things you want to bring into a QBR with your customer, right? You want to be able to sit down with your customer and say, hey, look, we're trying to be really aggressive about this lane. We like this lane, it works well for our network. The problem is we have such a turn time on this specific location. How could we get these appointments back faster? Right. These we're taking them into deeper layers of conversation around scheduling that they've never had before, and to the point where a lot of our large customers are now inviting us to come to their customer advisory meetings and saying, no, no, no, we want you to talk about this with them so that they understand more about this. They understand where we want to take this. And so it really is all about um creating uh additional visibility to scheduling that before you didn't have because you're just executing. You're right, you're just trying to keep up with the madness of what is going on every single day. Now you're able to actually look at how does my network work and then where where are there gaps on the scheduling side that could make my network a lot stronger for my carrier base.

SPEAKER_02 29:27

And then that way that that translates into what the company can deem as appropriate for the positions that they're gonna hire, whether it's an AI ops role or only dedicated to exception management. Um, so it sounds like it you guys are, you know, kind of at the front lines of of building what that new department looks like inside of logistics companies.

SPEAKER_00 29:47

Yeah, and look, I think um in our industry, we're gonna constantly be learning about that, right? I mean, I've been I've been in the space for 20 years, and I I would like to say that you know, we reach a point that we figured it out, but I'm sure in the next 20 years I'll still be saying the same things that we're learning, we're figuring out, we're trying to understand how this all works. Like that it's just it's a part of that. I think the thing that matters most is that a lot of this comes from experience of doing. That's why I talk so much about being on the front lines, being directly with users, understanding their rural workflow, not creating things in a vacuum, because when when you can engage at that level, you can solve problems. Um, if we left our engineering team in a back room to solve these problems, what would be delivered to the transportation industry wouldn't necessarily fit the mold. And that that's what's really important for us for as you look at these tools and you look at different different products that exist in the space, you have to figure out how close are you gonna be able to be to the end users who have control over that roadmap so that you can make sure, hey, is this problem gonna, is this problem gonna come back in a few months when my users don't want to engage? Or is it gonna get stronger? Where's it gonna be and how how much am I gonna end up depending on it going forward?

SPEAKER_02 31:03

Now that that that's really well said and and sheds a lot of light on a problem that I didn't know was this extensive, which I I imagine for a lot of your customers, they are finding that out as well. All right, Tom, uh anything else that you feel is important to mention that we haven't already talked about?

SPEAKER_00 31:19

No, I think um look, I think that um as people are evaluating new pieces of technology, one of the things that that I always encourage you is make sure that you're investing in things that impact your customers. When I was running a brokerage, when I ran a fleet, um it's it's it's very easy to get distracted and all the different AI that's coming at you and all the different technologies that's coming at you and try to figure out how to prioritize. I always encourage people to go talk to your customers and ask them, hey, we're thinking of investing in another layer of technology for our team. Here's some of the things that we're looking at. Which of these are interesting to you? And when you talk to your shippers about that, if there's products that excite them, then you're coming to them as a partner, you're you're coming to them as someone who understands their business and values their input. And that becomes incredibly valuable. And it's it's not uncommon for me to be on a call with a potential customer or a customer and their shippers that they're working with because they want to have this collaborative conversation around what would this do if we did this for your business? And so just don't lose sight of your customer in the journey of trying to leverage technology.

SPEAKER_02 32:29

That's a mic drop moment for the conversation. And so, Tom, where can folks connect with you, learn more about Q'd? We can put Qed uh com in the show notes just to make it easy for folks, uh, but anywhere else we can send them.

SPEAKER_00 32:41

Yeah, yeah. Feel free to hit up our website um or find me on LinkedIn, shoot me a message on LinkedIn. Um I'm usually uh uh pretty busy out there as well.

SPEAKER_02 32:50

Awesome. Or on the conference circuit, as as we discussed before we started recording. Thank you so much, Tom.

SPEAKER_00 32:57

Thank you.

SPEAKER_01 33:02

Thanks for tuning in to another episode of Everything Is Logistics where we talk all things supply chain for the thinkers in freight. If you like this episode, there's plenty more where that came from. Be sure to follow or subscribe on your favorite podcast app so you never miss a conversation. The show is also available in video format over on YouTube just by searching Everything is Logistics. And if you're working in freight logistics or supply chain marketing, check out my company Digital Dispatch. We help you build smarter websites and marketing systems that actually drive results, not just vanity metrics. Additionally, if you're trying to find the right freight tech tools or partners without getting buried in buzzwords, head on over to Cagorex.io where we're building the largest database of logistics services and solutions. All the links you need are in the show notes, and I'll catch you in the next episode and go jet.