Wednesday, July 7, 2021

Episode 115 - Route Planning with Parker Woodward


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Route Planning with Parker Woodward

Ever wondered how route planning apps, well, plan routes? In this episode, we navigate through this fascinating topic, a field as data-driven and systemic as it is magical and compelling. 

Joining us is Parker Woodward, Route Expert and Marketing Director for Route4Me. We discuss how route planning works, the intricacies behind it, and how services like Route4Me perform complex balancing acts between machine learning and user-generated feedback.

This episode touches on the following key topics and ideas:

00:00:23 Introducing Parker

00:01:54 Becoming a Route Expert

00:04:22 Getting started through smaller startups

00:12:41 Leveraging technology for the greater good

00:14:36 The magic of route planning

00:23:30 Homomorphism and satisfiability

00:31:18 Geocoding

00:33:06 User-generated feedback

00:37:08 Importance of statistics knowledge

00:39:34 The degree of automation in route planning

00:42:54 Inverse decision-making

00:48:47 Operations Research

00:53:42 Dwarf Fortress

00:56:40 US vs European routes

00:57:51 What Route4Me does

01:05:38 Working at Route4Me

01:10:26 Route4Me API

Resources mentioned in this episode:



  • Sapiens by Yuval Noah Harari



Reach out to Parker via email:

Catch Parker on LinkedIn

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Programming Throwdown Episode 115: Route Planning with Parker Woodward

Patrick Wheeler: Programming Throwdown Episode 115, Route Planning with Parker Woodward. Take it away, Jason. 

[00:00:23] Jason Gauci: Hey everybody, so this is one thing that I'm sure a lot of people are wondering. I've always wondered it. I feel like I'm going to learn a ton today. I'm really looking forward to it. But when you do something like use Google Maps or Waze, or any of these, even people who remember MapQuest, it generates this path. And that is just really fascinating if you think about it. 

[00:00:45] I mean, there's an unbelievable amount, like an enormous network of roads, right? And it manages to figure it out how to do that. It takes into account like speed limits. And it just seems like there's extraordinary complexity there.

[00:00:59] And we're actually going to not only cover that, but even take it to the next level, where in this case, what if you were driving, let's say a UPS truck or something, and you have a whole host of places that you have to go to, or even maybe you have a list of errands you need to run. How do we actually do that efficiently?

[00:01:18] And I think it's a fascinating, fascinating topic. We're going to dive deep into it. And I'm so lucky that we have Parker Woodward here, who is the Route Expert at Route4Me, and has a ton of experience in this field. So thanks for coming on the show, Parker. 

[00:01:31] Parker Woodward: Yeah, thanks Jason. And don't worry. People still actually use MapQuest.

[00:01:34] Jason Gauci: Oh, really? I was wondering actually, when I said that. So, so it exists, right? 

[00:01:38] Parker Woodward: Well, I've seen it, it exists. People are still using it, and people are using a host of other things to plan the routes. We had a customer who actually plan the routes on cocktail napkins at happy hours. So we've had, we've seen a little bit of everything.

[00:01:52] Jason Gauci: Oh, nice.  (laughter) Very cool. That's awesome. 

[00:01:54] So yeah. How did you, I think this is going to be really interesting because a Route Expert is a title that seems to be one that, like, is out of reach for a lot of people. A lot of people don't see, what is the path that I can take from maybe my Algebra 2 course right now, to Route Expert?

[00:02:14] And so it would be amazing to hear your kind of story, how did you kind of get to where you are and what was that, that whole path like?

[00:02:22] Parker Woodward: Sure. So I took maybe a non-traditional path and I was in the entrepreneurial world and studied in college, actually, something totally different. And it was more about conservation and biology and animal behavior and different types of systems, in comparison to route planning. 

[00:02:41] And I was always fascinated with energy and conservation and efficiency and happened to really stumble across this opportunity with Route4Me. And at the time I was doing, kind of transitioning into the fascinating world of the web and software and building software. 

[00:02:59] And so I just found Route4Me and got involved with the two co-founders. They started in 2009. And really interesting story there as well. Very entrepreneurial. One of them was kind of looking for an apartment and they didn't really have, you know, an app back then that would help them on the mobile phone to kind of build an efficient route when you're going to see 5, 10, 15, 20 places. So you're spending a lot of time going around. 

[00:03:26] So our CEO and founder, Dan Khasis, built the first, web or sorry, mobile app that would optimize and plan a route for you. So it could be efficient. 

[00:03:37] So he was apartment hunting at the time. And his buddy from college, George Shchegolev, he got involved, and they took it to the next level, and they just started listening to customers more and more. And I got involved and, next thing you just start to learn about this.

[00:03:52] So it's sort of a burgeoning field. It's if someone's interested in becoming a, a routing expert, a lot of it is about dealing with people and product and also processes. And you'll be amazed at these companies that, they're trying to figure it out too. And so, as you get exposure to more and more about how to implement these solutions and how to really make efficiency gains, you just learn along the way.

[00:04:18] So I think that's the best, best way to learn anything is to just go out and do it. 

[00:04:22] Jason Gauci: Yeah. That's, that's really, really good advice. And that's, it's super interesting. We have a lot of folks who have a variety of different degrees, or maybe didn't go to college and have a different background. Maybe they have a trade.

[00:04:35] And so they feel like, how do I really get started in this field? And one thing we tell a lot of folks is, a startup or a smaller company is a really good way to get your foot in the door because many of them will have a real person look at every resume. 

[00:04:52] Whereas if you send your resume off to, some giant tech company, they probably have some automated system, your resume may literally not be seen by a human eye, right? But smaller companies that are in your area, you, you will get a chance to really impress them. 

[00:05:10] Parker Woodward: Yeah, they definitely have systems and software in place. And I think there's even software that you can actually engage in kind of beef up your resume. So it gets beyond the bots. 

[00:05:20] So it's an interesting world and it's one of those things. If someone's really looking to get started in this, there's nothing really holding you back to kind of say, Hey, I want to go do this. And don't be afraid of the nos. Like you might get 10 nos from even a small company, says, Hey, we can't do that right now or anything like that. But try to look to provide value. 

[00:05:37] If you want to learn routing and route optimization, which I think is a wonderful space because I really truly believe we're helping to save the planet and save the world. Especially as more and more carbon emissions are being admitted, more and more vehicles are going on the road. Hopefully we're getting towards electrical fleet, and more and more electrical fleets. 

[00:05:58] At the same time. If someone wants to learn this, just go out and do it, start contacting companies and just say, Hey, I want to kind of learn the process and start adding value. And there's no reason someone can go out and just find other companies that need these types of solutions to help them implement them.

[00:06:14] So it could be almost your little company that you could start just off the top of my head, just to get some experience on your own. 

[00:06:20] Jason Gauci: Yeah. That makes, that makes a ton of sense. So, so you were studying biology, which actually gives me a lot of hope. My older son is really, really into biology. Actually. I take it back. Maybe hope isn't the right way of saying it. 

[00:06:31] If he wants to be a biologist, that's amazing. I'm not going to hold him back from that. But there, it seems like there's a chance that he could study biology and still end up in tech. So I'll, I'll, I'll hold out for that.

[00:06:40] But yeah, you're studying computational biology. Can you describe a little more detail how that got into Route4Me? So, so did you graduate, and then you started the job hunt? Or while you were studying this, you met those folks. Like how did all of that work?

[00:06:55] Parker Woodward: Yeah. So as I was studying through college, I was, I was doing things like, consulting on the side. I was actually building websites. So I was just finding work actually on what is now Upwork.

[00:07:06] And so that was really kind of my side hustle. I was even bartending through college and everything like that. And I actually got the opportunity. I saw something to do a little consulting work for Route4Me. And I made a quick video resume just to try to stand above and sent that off and just said, Hey, I'm really interested in the work that you're doing and we'd love to be of assistance. And next thing you know it was a startup. 

[00:07:32] So I'm wearing a lot of different hats, helping out in a lot of different areas. Really making an impact I felt, which was amazing coming out of school. I think you always wanted to make an impact really, really quickly. And so it was a little bit of a non-traditional path, maybe even a little, what some might consider risky, working for this company that wasn't this big name brand company.

[00:07:54] But it's been growing more and more, and it's a leader in its space and it's just been wonderful to work for a company that really has that family company feel. And so that's how I got started. 

[00:08:05] And then I just rolled up my sleeves and went to work. So that was my experience, was just how can I help and make things better? And that's really what Route4Me is about, is making routes better, making them more efficient, making businesses better, making people's lives just easier.

[00:08:20] You would be amazed at how many people are literally pulling their hair out, just trying to get routes planned for their drivers or even themselves. So it's a really, really great feeling to go home at the end of the day and say, Hey, I help people. I help the environment and we all were profitable. So it's really, really cool. 

[00:08:40] Jason Gauci: Yeah, yeah. Totally makes sense. 

[00:08:41] Parker Woodward: I feel like I'm just plugging Route4Me right now.  (laughter) 

[00:08:44] Jason Gauci: No, no, it's fine. I think, oh yeah. I think one thing you really touched on that's super important is, I have a friend who kind of told this joke. He said, I have a PhD from Princeton. And now I just hit up Enter, because it's like, it's like we have this mathematical simulation and if it doesn't give you the result you want, you run it again. And so he's like, I got, I spent all this time, so I could come here and hit up Enter. 

[00:09:10] And  it's true. You can kind of feel like so separated from any type of real world impact when you work at a giant company. And it's so nice to, you know, putting on the different hats is a, is a double-edged sword, right?

[00:09:24] I mean, you might not want to spend your day trying to find another janitor for the office, but someone has to do that, right? But on the flip side, you, you do get to see something really cultivate and, and really grow something. Whereas something so, so giant is moving at such a glacial pace. You don't get that same feeling.

[00:09:46] Parker Woodward: Yeah, there's not that red tape, which I think really enables the product to evolve, and enables you as a person in the company to have a voice. And you have to realize that your voice, even though it's heard, it may not go in the direction that you want it to. And so there's always that learning portion of kind of coming out of school and getting into a job and realizing that you kind of have to get along with people, which is a wonderful thing.

[00:10:13] And at the same time, working at a company where basically they say, Hey, if you want to make an impact, do you want to go do this? Like, go do it. You know, get dry results and just drive it. So it does take a lot of, especially being a company that was born in the cloud. We, almost 95% of us work from home and have, which was kind of taboo prior to COVID, and now it's very normal, but I used to almost not mention it. And now it's kind of, I can mention it to folks and they're getting along and figuring it out. 

[00:10:46] We had it figured out a long time ago, but to have that motivation to say, Hey, I'm going to go do this. I'm going to drive this project. I'm going to actually run with this. And it becomes my little baby. It's a wonderful thing to have. And I think that's rare. And you do see it in a lot of organizations. And I think those are organizations that thrive and do really well, and kind of figure out how to get beyond certain inflection points in the business to kind of really take either the product to the next level and serve their customers better.

[00:11:14] Jason Gauci: Yeah. Yeah. I think totally makes sense. That's a, it's a huge challenge to keep that drive and that energy as things get really gigantic and do it in a way where you're not totally federated where there's at least some kind of organization. 

[00:11:29] Parker Woodward: It starts with why, why are we doing this? And that's, is a Picasso said and Steve jobs stole, "great artists steal". And I'm stealing that from Simon Sinek, you know?  (laughter) So you have to believe, you have to believe in what you do and why you do it. And then you know how you do it and what you do is important, but people buy into that, and the why is really important. 

[00:11:50] And so I'm probably a very annoying person at a party to talk to because I'm always talking about like routing and route planning and they're like, what is this?  (laughter) And I'm like, no, we're saving the world. It's like really exciting stuff. Like, this is amazing. Like, we've saved the emissions equivalent of 87 million trees. I mean, like, who gets to say that? 

[00:12:09] And, coming from my background in conservation, I've made such a huge impact. And I'm just so proud of that or to be a part of that, not like I've been the one that to save the trees, but there's so much opportunity out there too.

[00:12:23] Jason Gauci: Yeah, it's interesting how that fit. And people get so wrapped up in the tech that they look at it in this very one dimensional way, but in your case, you were able to see, oh, this is a perfect fit for me, even though most people consider that like an entirely different career, right? But, but for you, it's obvious that these things kind of belong together.

[00:12:41] Parker Woodward: Yeah. I mean, from the perso-- at least my personal perspective is that technology is wonderful. It's just, what do we do with it? Like how do we truly, take it into something that's going to make our lives better? And we have to be careful a little bit, right? 

[00:12:54] Like one of my favorite books is Sapiens. So anyone out there listening who hasn't read that one, it's a brief history of humankind. Yuval Noah Harari, I believe? 

[00:13:04] Yeah, that's right. He talks about something called a luxury trap, which is really interesting that, eventually every luxury becomes a necessity. And if you think about that from the perspective of just like having email, everyone has to answer email, but at one point that was like a huge luxury.

[00:13:20] So all these luxuries become necessities. I mean, even just in the COVID world we live in today. The luxury of like having goods, whether they be Uber Eats or just Instacart, or any of the services actually bring you food or just basic necessities, that was a luxury. And now it's become this necessity. And so people are using it more and more. 

[00:13:42] And so it's just interesting how we have to take that technology and balance between, okay, well, how do we make sure that we're also not doing things like killing the environment? 

[00:13:52] And so I really see like that being on the forefront of, Hey, we know we need to get to renewable resources. We know that Electric's coming. But how do we make sure we're efficient and get to that point? So technology is really interesting and how we can leverage it and so many different ways for the greater good. 

[00:14:09] Jason Gauci: Yeah. That makes sense. I think there's this similar thing in robotics where you say, once a robot is a necessity, it's called an appliance, right? So it's like your dishwasher. You don't call that a robot anymore. It's now just an appliance. And a Roomba probably become an appliance. It's just a matter of time. 

[00:14:25] Parker Woodward: So I've got a five-year-old and are you telling me that, if he doesn't have to learn how to drive, because there'll be self-driving cars, we're just going to call them an appliance, not a car?  (laughter) 

[00:14:36] Jason Gauci: Yeah, or, yeah, maybe at least we won't be calling it a robot. Right? But we'll call it. Yeah. We'll call it just a car. Exactly. 

[00:14:42] Yeah. I told my son it's a robot car when we pass it by one of those Waymo self-driving cars. And yeah, I think that now it's not going to make sense to call it a robot car. You'd have to just call it a car.

[00:14:53] So let's talk about like jumping into the, to pivoting to the tech a little bit. So, or even, before we get to tech, just kind of going top down. So someone, opens up and I'm just going to pick something in Waze, right. Or one of these apps and, and they, just a single point destination, they say, I want to go to the grocery store. 

[00:15:14] There's a whole search to find the grocery store. We'll leave that aside. But you get the coordinates of the grocery store. What actually happens that generates that single path for somebody from their house to the grocery store? Like what magic is actually happening to make that show up?

[00:15:30] Parker Woodward: You know, it's a really great question that I would say that I don't necessarily even totally understand the magic myself. I'm sure if I pulled, our co-founder into the conversation, he would have a pretty good answer for you and understand the different data sets that are involved. So I'd say that one's a little bit beyond my, even my own technical know-how, but, I do know that it's a lot about just big data, right?

[00:15:54] And that's probably a term that's thrown around, but what actually happens is just, there's a lot of computing power that happens to make that very simple thing actually come to life. I know that because if we talk about one point on the map, now let's talk about, just eight points on the map and the actual number of possible variations to build that route starts to become exponential.

[00:16:18] So if we start building that, the actual number of calculations starts to become mind-numbingly high, to the point where my simple brain starts to not understand how it is that that all works and how those algorithms are applied. So it's a lot happening behind the scenes that even I don't understand.

[00:16:37] So maybe that gives hope to others to understand that you don't have to necessarily know how to build an engine if you want to drive a car, for example. Like driving a car, you really just need to learn, okay, here's the gas pedal, here's the steering wheel, here's the break, very important piece.

[00:16:54] You don't have to know exactly how an engine works. You just, learn to drive the car and you trust it. 

[00:17:00] Jason Gauci: Yeah. I think it's a really good call out because, you could just, let's say, get the data from, like there's this thing called OpenStreetMap, I think it's called. And they have all the streets and they'll even tell you, is it a major road? Is it a highway? 

[00:17:14] And so if you have a point, like I have this grocery store at this location, you could find, let's say the nearest street, which that itself could be a problem because maybe the parking lot is not actually the nearest street, but let's put that one aside, right? So you say you can find the nearest street or at least some place on a street where you need to go.

[00:17:34] And then you could treat all the little streets as lines. And just similar to solving a maze, where, you try one route. And you have to do some backtracking. Like maybe you, you try to go close to the grocery store, but you hit a dead end. And so I have to back up a little bit. 

[00:17:54] This is in the planning. So you're not literally doing this with your car, but in the planning is they have to back up a little bit and try something else. Just like you would erase a line in a maze while you're trying to solve it. 

[00:18:04] And, and so you could eventually, kind of get that path, but then it gets really complicated because, in a maze, you're not too concerned about the path itself. Like, no, one's really holding like, like no one's expecting see you to find the shortest path through the maze. And the maze also is just kind of spatial. So, so every direction is  just going as fast as your pencils. 

[00:18:28] But, in the real world you have different speed limits, some roads have traffic lights, some don't. I know for me, Google Maps always seems to take me on the highway. And maybe it is faster, but it is kind of a pain, just get on the highway for two stops, when I could +have just taken a straight line, you know? And so that's the one where it's like, it's not even about the fastest time. It's about the best experience for the driver.w

[00:18:55] Parker Woodward: Yeah. I mean, if you think about Waze, one of their unique advantages was being able to build that data set, and that data set was user generated feedback. So that user generated data where someone could go into a really easy, clean interface that was easy to use. And start to report things. 

[00:19:15] And so, I still use Waze myself. Am I allowed to say that, working at Route4Me?  (laughter) 

[00:19:22] Jason Gauci: Actually, yeah. We could interject a little bit. What is Route4Me, does Route4Me compliment something like Waze, like, do you do...

[00:19:29] Parker Woodward: It does.

[00:19:30] Jason Gauci: Oh, okay. Got it. 

[00:19:32] Parker Woodward: We don't consider ourselves really a navigation app, necessarily. We're more before on the route planning for more complex, high volume or high number of stops with advanced constraints.

[00:19:44] I mean, you mentioned a few of them, there's one way streets, there's stoplights, there's weather, there's time, there's all kinds of different constraints. So planning routes can get really complex really quickly.

[00:19:56] And navigating routes, once you have the sequence, navigating is wonderful to use something, if you're able to use something like Waze and that user generated feedback. I love using those navigation applications. And, maybe it tells me there's police ahead, or construction, or it tells me to take a path that in real time is generating that data from other users who unfortunately, maybe  got stuck in a little traffic, but are kind of helping me, following behind, to make sure that I don't make that traffic worse.

[00:20:27] So it's a wonderful thing to talk about technology, kind of solving problems, as they're happening. 

[00:20:35] Jason Gauci: Yeah. Yeah. That makes sense. Yeah. So I think, yeah, and, and I mean, one thing that's always struck me is how expansive that space is, right? I mean, think about when you're, when you have Google Maps on your dashboard, and you're driving someplace, all those roads that you see on the map, and they're all passing by you at 50 miles an hour, or maybe more than that, if you're on the highway.

[00:20:57] And all of those are directions that you at least somewhat have to consider when you're figuring out this path. I mean, there's probably a lot of rules that you can follow that helped us a lot, like get to the highway as quickly as possible or something like that. But even then, it's just the amount of computation to fetch all of these paths must be absolutely extraordinary. I mean, it's mind blowing. 

[00:21:22] Parker Woodward: It is. And it's interesting because you're, like, skimming the surface in a way too. Like, to kind of think about it from this perspective is, we're just talking about like Waze a little bit. Like there are many, many different rules of the road for what are commercial vehicle restrictions.

[00:21:40] So if you have, you've probably seen these on the road, even through the highway, if you said, okay, no, no trucks through this certain highway or through a certain town. And that's usually due to a weight restriction, potentially a hazardous material restriction. So certain vehicles, depending on their, cargo or capacity or vehicle constraints, actually can't go on certain roads and they can't use navigation applications like Waze or Google Maps, because they might send them down the wrong road. 

[00:22:10] And it's maybe not the worst thing for many things. If you're a little overweight, it's not good for the road, not good for the infrastructure. At the same time, this happens all the time that a vehicle runs into the bottom of a bridge. So low bridges are a major concern. 

[00:22:28] So imagine, imagine you're a business owner and you've planned this route and your driver get, you get a call. And next thing like half of, the truck has been kind of, like a can opener, and that's not a fun call, nothing fun to deal with. And insurance goes up. Cost go up. Customers are definitely not happy. So there's so many things to take into account, even from that commercial perspective where certain applications, they, they don't take that into account.

[00:22:57] So those data sets, there's all these different datasets to tap into in which, you know, it's kind of solving the problem or trying to solve what is a P versus NP problem, which if anyone solves that, I mean, it's like, if you can solve P versus NP, you can cure cancer, apparently.  (laughter) 

[00:23:15] Again, a lot of this going over my head, but like, we're still trying to deal with the problems we have with whatever data sets and solutions that we actually can access.

[00:23:25] So it's interesting that more and more data sets are being built, for example, with Waze. 

[00:23:30] Jason Gauci: Yeah. Yeah, totally makes sense. Yeah, actually, it's a really good call out. I think there's, there's a lot of these sort of commentorial problems. A lot of people, they would see, say protein folding for, studying cancer treatment and figuring out the way to get to Starbucks as like totally different problems.

[00:23:46] But from a mathematical standpoint, you can actually find a homomorphism. You can find a way to morph one into the other. The example I give a lot of people is Sudoku. So, you look at Sudoku. which is just for people that know it's this game where you have a nine by nine grid of squares, and then the squares are also grouped.

[00:24:09] So you also have this sort of three by three grid of groups, all on the same grid. And your goal is to place the numbers one through nine, multiple times on this, I guess, nine times on this grid. So that every row only has one of each number. And every column only has one of each number.

[00:24:31] And every, every cell, every group only has one of each number. Now, like if you had a blank Sudoku, that would be easy, but, but usually the Sudoku has some numbers already filled in. So every time you, you go to one, it's a little different. And that seems like a pretty abstract problem if you want it to solve it using computers.

[00:24:53] But actually it's very similar to another problem which is called graph coloring. And so graph coloring is a problem where you have a graph, let's say this graph is representing a map. You have a node for every intersection on the map and you have an edge for every street that exists on the map. 

[00:25:13] And graph coloring says, I want to color all these intersections, so that two intersections that have a street between them don't get the same color. So if I pick green for this intersection, then all the ones that that intersection can reach immediately have to be other colors besides green. 

[00:25:34] And it turns out you could actually think of Sudoku as a graph where every one of those cells is a, is an intersection. And there's a road connecting that cell to all its neighbors. And if you do that, then it just becomes a graph coloring problem. So that's a way you can morph something that seems pretty abstract into something that has like a bunch of solutions you can just download off the internet. 

[00:25:57] And it turns out, almost all of these problems, whether it's route planning, protein folding, most puzzles you see in the real world and online, almost all of them can be reduced down to the same problem which we call satisfiability, and it turns out, solving any of those is really, really hard. So what you have to do is make a lot of really good guesses. 

[00:26:24] And so for example, this idea of let's get on the highway as quickly as possible, and then let's take the highway to our destination, and then let's go to the destination, that allows you to avoid a lot of decisions. Like if you're on the highway and you're 80 miles away from your destination, you don't really have to worry about, should I take this exit or not? Because you're clearly not there yet, unless the exit is another highway. And so using a lot of these tricks, you can take these problems that otherwise you can't really solve, and you can make them much more practical. 

[00:26:59] The thing that's really interesting about protein folding is, unlike the highway where you have a lot of common sense reasoning, you don't really have a lot of common sense reasoning about proteins.

[00:27:10] And so the thing that was amazing about the protein folding was the work from DeepMind, where they actually just, again, as you said earlier, you used a ton of data to build up kind of machine common sense reasoning, and then use that reasoning that the machine has developed from just looking at a lot of proteins being folded, use that information to discover kind of new protein combinations that were really effective.

[00:27:40] Parker Woodward: It's interesting you say that, too. What's interesting to me is relating it back to routing is, we can take, for example, let's take a thousand stops and just imagine it's like your job to go route 10 drivers, or how many drivers do you actually really need to go visit these 1000 stops? And we see this all the time.

[00:28:01] And so, with a program like Route4Me to kind of, with these set of rules, looking at these datasets, we can go solve that problem the best that we can. And time is a really critical component here, could we solve the problem better with more time? The answer is yes. And what I often see is, when we give you a result to say, okay, I took your thousand stops and you've got a number of advanced constraints. You've got time windows at them. Maybe you got priorities, you've got different weights and all kinds of different other problems with it. I took a thousand stops and within less than 60 seconds, here's the eight vehicles or eight routes that you need. And they're all sequenced in the right order. 

[00:28:47] And so it's really easy as I think a human being to kind of spot the flaws, and to that point, to your point of like, well, should I take the highway or, why is it always send me the highway? Or is there a better route? And the answer is yes, you could actually beat the system, right? Like you could refine it, but I guarantee you, there's not a human being in the world that could take a thousand stops and route them to the fewest number of vehicles in 60 seconds. I would like to meet that person if possible.  (laughter) 

[00:29:15] So it's funny how as human beings, like we spot these walls and say, well, you gave me out eight routes, but I could've made this stop a little bit different, you know? So it's about time to actually solve the problems too, which is really critically important, especially in a business scenario where you actually have to get out the door, and like I mentioned earlier, I have a five-year-old, I got to get them dressed and ready to get out the door. And if there was a, a software solution or some, some solution that could help me get them dressed faster, I would absolutely engage with that appliance.

[00:29:46] Jason Gauci: Yeah, that's right. Yeah. It's a really good call-out. So. Yeah. So, so we talked about doing a single route. Now, imagine, just getting from point a to point B is really hard, right? I mean, it's people look at it as magic. We tried to unpack it, but there's so much depth there. I mean, we barely scratched the surface. It's hard.

[00:30:04] Right now, imagine you actually don't want, just to get from point A to point B, you're at point A and maybe there's a hundred, maybe a thousand people who are at point A, point A is some distribution facility. And then as you said, there's a thousand other points, and these people have to cover all those thousand points in a day.

[00:30:24] I mean, imagine Amazon. So Amazon has this massive distribution center and they have a whole list of people who want packages delivered, on this day and they have an army of trucks and, and so they have to figure out how do we get all of these packages to all of these people before, before the clock runs out for, I think it's 10:00 PM or something, is when they say your package will be delivered by, right? So, so that, I mean, that is, and even just getting one of those routes, like even, or one of those paths, like even just saying, take this package from Amazon to this person's house. That is really hard. And the problem that Parker just described is, just needs that as like one atomic piece of it.

[00:31:11] I guess all of this is just say, route planning is really, really hard.  (laughter)  It's really difficult.

[00:31:18] Parker Woodward: But it's so necessary, and it's interesting 'cause you mentioned that, like, one piece, even before you can get to route planning is, and you kind of mentioned it earlier, is geocoding. Just the process of geocoding in, in saying, okay, well when you type in, 1, 2, 3 Main Street, that could mean anywhere in the world.

[00:31:38] So giving it and filtering that data down a little bit further and getting a really confident idea of where we're going is critical. And because if you, in that same scenario, if you're a delivery driver and you have 50 stops, a hundred stops, 200 stops to go to in a day, if you don't geocode to the right address, it kind of reminds me of Michael Scott, and Dwight running into the lake with the GPS system. 

[00:32:05] Jason Gauci: Oh yeah.  (laughter) 

[00:32:05] Parker Woodward: Really, it really throws you off course. And, and it's a huge time investment. It really a time waster, not just to mention the carbon emissions to waste, but if you don't go to the right person, now you have to figure out, okay, I didn't go to the right address. What is the right address? Who can help me figure that out? Do I have to call the customer? 

[00:32:23] And so that geocoding process is really, really critical, and that happens before you can plan the route. So you mentioned something earlier as, well, how do you geocode? Do you geocode based on the curb side, latitude-longitude coordinates? Do you geocode based on the rooftop, and how do you measure that rooftop?

[00:32:41] So there's so much that goes into just geocoding and finding the actual locations before saying, okay, now let's plan the route. So it's really, really fascinating to go through that process. And what's important, at least from our perspective at Route4Me, is just to make that really easy, and make it magic.

[00:33:00] You know, again, you don't have to know how the car works, but you do have to drive it. 

[00:33:06] Jason Gauci: Yeah, that totally makes sense. I think that we should spend a little bit of time talking about crowdsourcing. So as we talked about at the beginning, finding a path from A to B without any sort of, let's say, hacks or cheats or whatever you want to call it, assumptions let's say, is not tractable, right?

[00:33:25] But if you really want to consider, maybe I need to. So right now I'm in, I'm in Texas. Maybe to get to the grocery store, maybe I need to go to Florida and come back. I mean, maybe, but we know that from common sense that that's not true, but in the complete abstract, like you would need to search everything.

[00:33:45] Um, so then you can say, well, let's, let's kind of make some assumptions. Now. Some of the assumptions are obvious. So for example, the speed limit is not going to be the speed of light. And so going to Florida and coming back is almost for sure not the right answer. And so, you can make assumptions about just how fast could you possibly get from point A to point B and use that to say, I'm done looking, I've got this route, and when I look at the ways I could change it, all of them just make it mathematically impossible to get there, let's say significantly quicker. 

[00:34:19] So then, but then some of the assumptions become things that you have to learn. So for example, maybe your system that does the geocoding. 

[00:34:29] Actually this happened to me. My wife and I do a lot of hiking, and my family, we do a lot of hiking. And sometimes we'll put in a name of a hiking trail or a hiking park. And I remember one time specifically, we put in this place called "the Dish", which is a hiking trail with a lot of satellite dishes. That's on the Stanford campus. And so we put in "the Dish", and Google Maps actually took us to the border of the highway and the Dish. 

[00:35:02] So we're going, 70 miles an hour on the highway and maps says, you're here, done. And so...

[00:35:09] Parker Woodward: I did my job. 

[00:35:10] Jason Gauci: Yeah. Thank you. I can see the Dish. I can see the dishes clearly, but no, we wanted right was a way to park, so that we could walk on the trail. And so that's an example where, what we did was what anyone would do. We got off the highway, we found the way to get to the parking lot or to the street rather than, and we parked there.

[00:35:29] And so what maps can do, and I'm sure what they are doing is, they're looking at that. So every time, you purposely, or every time you don't go to the destination that map's told you to go to, but you actually go somewhere else, they're tracking that. If they see, 60, 70% of the people who we sent to the Dish actually parked over here, then that, they can use that signal later on to fix,their geocoding and their other systems.

[00:36:00] Parker Woodward: Yeah. It's user generated feedback, right? And it's something you see, and it's so funny that you mentioned that because we tend to have a blind faith, or I do, maybe some others don't, but we have a blind faith in technology and in those data sets already being there. And I think it's easy to make that assumption that they are, and they're still being built. Google is still building things. I think, anyone who's-- the roads change. So you'll see the maps change. You'll see satellite images change, things are constantly in flux. 

[00:36:33] And what's fascinating from that perspective, from a route optimization perspective is, you might find many businesses say, well, I'm okay, my routes don't really change. And what we find is that they do, there are so many variables at play that it will change and those data sets are continually being updated. And so, you're contributing every so often when you take the wrong path, it sounds like. So that's, pushing humankind a little bit further, which is a good thing. So the next person, hopefully won't get lost seeing the dishes.  (laughter) 

[00:37:08] Jason Gauci: Yeah, yeah, right? Yeah. And so I think you'll harnessing all of that data. And this is, this is one thing we've mentioned on the show several times, but it's a good, good point to just, just really drive it home is, is how important statistics is.

[00:37:22] And it's one of those, those areas that, it's really interesting. Statistics is... there was a time actually when machine learning was in the statistics department, and at that time machine learning didn't actually, didn't get a lot of recognition. And so the people who were studying AI, and so I'm thinking about maybe the sixties or seventies, the people who were studying AI were actually looking at the human brain and trying to effectively reverse engineer it, right? And so they're taking a very biological approach. And meanwhile, the people who are saying, well, I have this class of problems that I want to solve, like route planning or like protein folding. 

[00:38:04] And I think that these sort of numerical methods like neural networks could be used to solve those problem. These people are like relegated off to the statistics department, and it was difficult for them to get funding. And so it's, there's always this joke, like the statistics department is kind of like a second class citizen to the math department.

[00:38:22] But it's actually, I hope that, when I was going to college, it was a different department. I really think we need to have some sort of unification here because what I see is a lot of people graduating from college with a ton of engineering knowledge, but missing a lot of the core statistics knowledge. And then when you have a problem like this, where it is stochastic by nature, right? 

[00:38:45] Like, in our case we saw the Dish, we needed to park there. And so we left Google Maps on, and we found the parking spot, but there's a lot of people who will just shut the Google Maps off. Maybe they'll turn the app off completely so the data isn't collected afterwards. There might be some people who even park on the highway.  (laughter) And I don't know, maybe they... I don't know what they do after that.

[00:39:05] But the point is, there's uncertainty, and with everything, it's all fuzzy and uncertain, and having that statistics background will allow you to sort of separate the signal from the noise, where you can automatically, without a person in the loop, you can say enough people have made this class of mistakes. You could build sort of a space around that mistake, and see a lot of density there and automatically corrected. .

[00:39:34] And so, actually one, one kind of question along these lines is to what degree is this automated? And, and to what degree do you have, an army of people, fixing things all over the country, or all over the world?

[00:39:49] Parker Woodward: So I think what's important about Route4Me is we're similar, in the sense that we're hooking into those data sets. So we're hooking into data sets from, many of the vendors that you mentioned, and we also build our own proprietary data sets. 

[00:40:05] And so much of it's automated in terms of what we do, from a route planning perspective or route optimization perspective. And we've just try to make it simpler and easier for users, because imagine, if you were going to that same hike and you actually had to go research out of a book and learn how to program some code into, your computer in order to kind of get the result. You probably wouldn't go do it. You'd just probably go find the place and a little trial and error. Maybe ask some people stop at a gas station. 

[00:40:39] So from the question, most of it's automated, what we do. And we're just looking into vendors, solving with our proprietary algorithm, our routing engine, so to speak. And let people use that engine to plan their routes and optimize for the best sequence of stops across a large group.

[00:40:59] So I don't think we would be able to kind of, in the background, reminds me of an old telephone operator being like, oh, someone just put an input in with a thousand stops. We got to go figure it out for them.  (laughter) 

[00:41:13] Jason Gauci: Yeah, that's right. 

[00:41:14] Parker Woodward: Impossible. So most of it's automated to a point, at the same time, there still needs to be an operator. There is still someone today, for example, in businesses that, they don't often have, at least from my experience, they don't often have a background in computer programming, logistics, or anything like that. They just, they started in the company and they ended up in that role because maybe they had a natural tendency to it. I sort of, lovingly refer to the people in those roles as having that Russell Crowe, a beautiful mind brain where numbers float across the screen and their brain just naturally kind of are good at that. And so they fell into it. 

[00:41:55] And when they come across a solution like Route4Me, suddenly they just made their lives so much easier and better, and that's, because they're going to operate it. They're just going to operate with more efficiency. They're going to be able to do more with a lot less and doing a lot faster too.

[00:42:12] You know, what might take them four hours to do? They can now do in 20 minutes or less, sometimes less, we've seen it even like less than five minutes. And so now they can do other things that they were supposed to be doing anyways and actually get things done, increase efficiency. 

[00:42:27] So I'd say most of it's automated, but there still has to be an operator, someone at the wheel, so to speak, to make certain decisions. Because, like you mentioned earlier, just because you decided to go to the highway, maybe that's not the right decision for whatever reason. So there's that internal tribal knowledge, which is its own dataset, very unique to the organization or individual that actually is going to go and perform the action.

[00:42:54] Jason Gauci: Yeah. Yeah. That makes sense. Yeah. I mean, one really fascinating area and it's, it's a brand new area. Well, nothing is brand new, right? Everything is incremental. But it's an area I think that will grow tremendously, is this idea of inverse decision-making, right? 

[00:43:10] So for example, let's say you just had a large data set of people who drove routes. Maybe they use Google Maps. Maybe they were just using their own memory, right? But you just had a large data set of routes and you don't necessarily know where they came from. You just know that people were driving these routes, then you could ask yourself, okay, let's assume that these people, again, in aggregate, were doing the right thing. Well, then what is the algorithm that can match that?

[00:43:43] So in other words, what is the algorithm that would do something the same way that these people are doing it? And so, you can clone their behavior. So in other words, let's say everyone who gets to the stop sign and wants to go to the grocery store makes a left. And so you can memorize that. You can say, yeah, I have this algorithm. And when it gets to the stop sign, you go to the grocery store and makes a left. 

[00:44:06] But what's even more interesting is saying like, okay, I want to trade off, the headache of driving to the highway versus going just straight to the grocery store, but hitting a bunch of stoplights. I have a threshold, imagine like a little knob, and when you turn it to the right, you just send people to the highway, no matter what, if you turn it to the left, then you avoid the highway. It's like checking the avoid highways button on Waze or Maps, and you just send the person in as much of a straight line as you can. 

[00:44:37] I think MapQuest used to call this the shortest route versus the fastest route. But imagine you had this little knob that could decide which one to favor. And the question is, given a lot of routes that people took, what should the setting of the knob be such that you kind of match their behavior?

[00:44:57] And so when they choose to take the extra step of going to the highway, your algorithm does the same. And that's actually a really, really hard problem to solve. 

[00:45:07] Parker Woodward: Very.

[00:45:07] Jason Gauci: And it gets way harder when you look at sequential. If you're looking at a single decision in isolation, then there's a lot you can do, then I think actually, when you look at one decision isolation, then copying the person's behavior is the same as inverse decision-making. When you have a whole host of decisions and you actually want to copy their strategy, that is a very, very hard problem. 

[00:45:34] That's actually an area of research that my job, my day job is, is trying to crack some of that. And I can tell you firsthand, it's a super, super hard problem, but ultimately it's really important, because there's value in doing something that a person would have done. If a person would have made a right and then a U-turn, I mean, maybe a left is like 1% safer, but at the end of the day, like if that's what people want, then there's value in giving people what they want. The customer's always right, you know. 

[00:46:07] And so, understanding what people want and being able to have a human-first strategy, that is a phenomenally difficult problem, but I think extremely interesting. 

[00:46:22] Parker Woodward: Yeah. I think that human-first strategy is, is really unique and really important, because, you can solve a problem, but if people can't understand the problem or understand how to apply that problem, that's a different problem. You really haven't solved the problem. 

[00:46:39] And you talked a little bit about what I would call the moment of fine tuning, and because one human being wants to solve a problem this way, because the way in which they've grown their organization or their operations is extremely unique. I call them snowflakes, just 'cause they're all unique and wonderful and amazing. And that's the opportunity, too, is to go into an organization and say, you have this beautiful snowflake and we want to make it better and what's unique to you. So you have to have a solution that's very flexible and still really easy to use because there are human beings involved here. They're operators.

[00:47:21] Imagine, you're talking about, knobs and turning people left and fine tuning that, imagine if the,  probably the first cars were very difficult to operate, even today. Most people, at least here in the US, they, this probably isn't a shock to some of the world, but if you're driving a stick shift, people in theUSmay not be able to actually operate that vehicle due to the high complexity, right? Or the non-user friendliness. 

[00:47:50] And inside of our routing solution, as an example, we have the ability to fine tune what you're talking about in terms of optimization. But it's really where art meets science. And like you can prioritize distance, then prioritize travel time or waiting time. So for example, if you have time windows where you have to be at a customer's location between like 9:00 and 10:00 AM, and that's the only time you can go there. Just, that is such a difficult problem to solve already. You know, that it can have cascading problems down the line. 

[00:48:24] So if you don't find tune or prioritize other things or deprioritize them, then you're going to have inefficient routes. I mean, you're already going to introduce an inefficiency, like a time window to a route. So how do you still try to be efficient with all of these constraints and do so in a way that's friendly to a human operator? Like that's the real problem. 

[00:48:47] Jason Gauci: Yeah. Yeah. I think, stepping back a little bit, I think this is a problem that's challenging the entire field. If you look at a lot of planning, algorithms and systems, a lot of them work through search. So you know, search-based methods, and there's a variety of different things that, people out there, if you're interested in this, check out, the field is called operations research, and there's a whole host of different things. 

[00:49:16] There's, there's this thing called branch and bound, which is where you try to predict the best- and worst-case scenarios. And so you take a guess, you're saying, well, I'm in Florida, I need to go to Texas, best case I'm going to do it in, I don't know, 14 hours, right? And so, you also say kind of, what do you think the worst case is going to be? And then based on that, you can search in kind of a smart way. And that's where you do something, right, if I'm on the highway and the grocery store is also right off the highway, but 10 miles away, I'm not really going to think about all the exits along the way. I'm just going to go as close as I can, and then get off the highway. Because you've founded a lot of those, like getting off the highway early, you just assume that those are kind of bad ideas. 

[00:50:07] And so for a long time, just kind of circling back a little bit, for a long time, like these two fields are totally, totally separate. So,the thing we talked about earlier, about kind of statistics, and kind of copying the way people do it, that people being very random, having very random behaviors. So you're also inheriting all of that randomness. That's one area. 

[00:50:32] Then you have a separate area over here, that's a really pristine, that's kind of searching, and you have these bounds and you have all this theory that tells you how amazing you are and how all your error is going to like approach zero so quickly. 

[00:50:47] But then it's like, the real world has both, like you can't just not plan, and just at every single step say what would a person do? Because people are planning, right? And so, if you don't have some kind of planning... Yeah, this is kind of like, if you have a modern iPhone or Android, when you go to type something, it'll have suggestions, right? So you can actually type like the, and then hit a space, and it'll actually suggest things to put there, like words to put there.

[00:51:16] And one thing my son, one of my kids loves to do is to just hit that over and over again, like even with no content, they'll hit it and then it'll end up generating like sentences, but they don't actually make any sense, right? It's like the parts of speech all fit together, and you can read it, but it's totally incoherent. That's what would happen if you had just taken the statistic approach, it's kind of like doing the same thing, but on a, with your car, right? 

[00:51:43] And so marrying these two things together, right? The higher level planning and the strategy, which expects things to be really kind of pure and clean and deterministic, you're marrying that with all of the messy statistics and the human reasoning, that is totally unsolved area. As you said, it's in the realm of the arts. I mean, it's, it's a lot of empiric trial and error. Nobody really knows how to do that in a, in a good way. And even the brightest minds on the planet have really no idea how to marry these two disciplines, despite the fact that like the entire world runs on doing exactly that. 

[00:52:25] Parker Woodward: Yeah, it's interesting. Just as an example, I, it kind of came from the resources of my brain somewhere, but something about landscape design of all things, but in terms of where, if you had to, if you had just a square piece of land connecting, one building to another, where would you put the path or where would you put the actual path for a human being to walk?

[00:52:51] And so marrying that art and science and, one school of thought is, well, don't put a path in whatsoever and the human beings will actually create a path. You'll see. And we've all seen this on certain paths, either through campuses or any location that has, a path between buildings, you've seen where someone took a little shortcut, and another people take that shortcut, it creates its own path, and it's not the original intended path, but it's what a human being would have done. 

[00:53:19] And so if you'd left that empty, and maybe walked and put the paths in where the humans would be a totally different thing. But at the same time, maybe you wouldn't end up with paths at all. So it's, I dunno, kind of making me think about that in that sense, just from a, you still have to put paths in, at the same time, you have human beings that are going to influence where they actually go.

[00:53:42] Jason Gauci: Yeah. Yeah. I remember, I'm a big fan of Tarn Adams who is actually a video game developer, but he's a, he's a very esoteric video game developer. He has a PhD in Math, and so he makes these really deep simulations. And actually for the past, I think like 15 years, he's been working on one game, the same game for one and a half decades called Dwarf Fortress, where you, at a high level you control, or maybe "control" is even the right word, but like you influence a whole army, a whole city of dwarves. And so, you need to sort of build homes for these dwarves and, it's a whole simulation. But one of the things really interesting is he was faced with this problem of, he has potentially thousands of units in this game and the units are very egocentric.

[00:54:39] In most games like imagine Doom, right? So in Doom, all the enemies are trying to kill you. And so you can actually just get your path to everything and just flip those paths. And now you have all the ways for the monsters to come after you. And it's very straightforward because they're only interested in one thing. But in Dwarf Fortress, as I said, you're not really, you're not really controlling any of these citizens. They're all doing their own thing, but their modeled at a very fine granularity. And, and so they're all egocentric and they all have different things they want to do at different times. 

[00:55:16] And he struggled a lot with route planning for his game. And the thing that actually, let's say cracked it for him, or made it to where he could move on to something else, was this idea of basically, almost like an ant pheromone trail type thing. Every time, a dwarf steps on a square, or every time a dwarf, walks a path, he increments some value and it makes that path more valuable.

[00:55:45] I think the ants might be a good metaphor here. Like imagine if you have a set of ants and they're just constantly leaving kind of a little pheromone, chemical trails. Well, if all the ants are kind of doing the same kind of routine, then certain paths, as you said, will emerge.

[00:56:01] Or even people on a college campus. If there are no roads, they'll eventually all start... If a lot of people are going between the math and the science buildings, they'll start to erode that terrain and a path will start to emerge that way. And so then you could say, well, okay, everywhere I see the grass eroded, I'm going to start laying bricks there, or I'm going to think that's the right way to go.

[00:56:25] And so using kind of that trick, Tarn was able to get the path planning. But again, that truck has problems as well. And so it's, it's still an art form, it still requires a lot of tuning, but yeah, even in, in simulation, it's, it's definitely not a solved problem. 

[00:56:40] Parker Woodward: And it's about environment too. Right? So that kind of reminds me that, in terms of, at least in the, in the US, in most cities, you're actually laid out roads are kind of block by block. I mean, we have literal blocks. And, so you actually have the initial infrastructure or the initial map. Whereas if you think about European cities, and European cities didn't typically evolve with the automobile, and they didn't evolve with the city planning, right? So they didn't have that map.

[00:57:10] So it sounds like, that trail, if you look at an ant's trail is oftentimes not straight, it's not linear, it's not following that same path. So the European path in that environment is very different than the US environment. And it's always been funny to me when, if you start to talk to any European, I mean, even if you know nothing about route planning, you could probably have a conversation on how the cities are laid out in plan and how different they are and how they have to think differently in terms of, actually route planning or just getting around town is very, very different and versus our very highway-driven culture.

[00:57:51] Jason Gauci: Yeah. Yeah. It makes sense. Cool. Yeah, this is absolutely fascinating. There's so many directions, but let's take a low moment here and talk a bit about Route4Me. So what is Route4Me? Is it an app or a service? Or what is, is sort of the vehicle, no pun intended,  (laughter)  that you use to sort of deliver, deliver these routes. And what is that whole product like? 

[00:58:14] Parker Woodward: Sure. The vehicle is a web app in mobile, in both Android and iOS application. And so really it's a route planning and route optimization application. So anyone today can actually go onto the Apple store or the Google play store, download the Route4Me app, and plan a route, plan a multi-stop route. Of course you can plan just 1, 2, 3 stops. 

[00:58:37] And it is a free app. There is a paid version. So we have a lot of mobile users. And then for our business users, they're typically going to want to plan their, for example, next-day deliveries, same-day deliveries, or service-type businesses that will use it to plan their routes and optimize our routes for ultimate efficiency, so that they're spending less gas. 

[00:58:58] And at the end of the day that's really core to what we want to do and help with is, to help save the world, and make the world a little bit better place for our children and more efficient and save those trees. It's really core to my heart. And I'm really happy that the company's followed that path all along to make the world a little bit, a little bit better place through software which is something I never thought I would be in, but I'm so happy that I am at the end of the day. 

[00:59:26] Jason Gauci: Yeah. Yeah. That makes sense. What about folks who are enterprise, who might have their own app or something? Do you have an API for those folks or how does that work? 

[00:59:36] Parker Woodward: Yeah, absolutely. So our API documentation is at And if you want to go there, you can also check out even benchmarks against some of the, different world record, in terms of times of solving. If you've go to, that's a really great place to kind of see some data, but our API is available if you want to get an API key at a

[00:59:59] Jason Gauci: Cool. So, yeah. Explain a little bit about what the free version is like, like what's the pricing model like? And how does, how does that work?

[01:00:09] Parker Woodward: So we have a mobile-only subscription, and so that's where a lot of our users come in who are actually part of very large organizations, and they're kind of given tasks and they say, okay, well, I've got 52 deliveries to go to a hundred, 200. And they spend the time to actually input those into the system because they know that time upfront is going to make them actually much more efficient throughout the route than just kind of trying to figure it out.

[01:00:36] And so many of our mobile users come in and it's subscription-based if you want to plan more routes than the free version allows you to. And so there's the mobile-only. 

[01:00:47] And then the web is more for when a business recognizes that, Hey, you know what, my drivers are already doing this. I can help them be more efficient. I can also gain control back into the business to understand what they should be doing versus what they're actually doing. So we can hook into various GPS, telematics solutions, as well as the GPS telematics on the actual mobile device itself. So we can give a really, really nice plan on the web to say, Hey, here's what the drivers should be doing. And here's what they're actually doing. 

[01:01:19] So you can overlay the planned route with the actual route that's been performed, and instead of just us making assumptions that everything's getting done correctly, or when a customer calls up and you don't know what's happening in the field, you can actually make a decision very quickly by looking on the web in that screen, just to say, oh, it looks like they're running a little bit late and we've even built some other things on top of that, that kind of eliminate that problem. So you probably get a lot of notifications. 

[01:01:51] If you get any kind of deliveries or service done, you always want to know as a consumer, as a customer, when that's going to happen. If you order some new furniture, you don't want to sit around for the four-hour window that they give you.

[01:02:06] So the companies that are adopting technologies that are kind of making an Uber-like experience for customers to get a text notification, to be able to see the vehicle coming to them on the map. And that's kind of what we're doing in order to enable, small, medium, and large and enterprise businesses to do that rapidly at scale.

[01:02:26] So it's a very exciting thing. And I think just for everyone involved in the whole cycle, it's something that makes their lives better. 

[01:02:34] Jason Gauci: Cool. Yeah, that makes a ton of sense. So what is the app experience like? So someone says, here's my 10 locations, and Route4Me will find a route for them. And then do you, do you then hand them off to like their map's app of choice? Or do you also do all of the, the navigation along the way?

[01:02:57] Parker Woodward: So we want to present the user with the best experience and how they want to experience it. Because again, they're all unique, they're, they're my snowflakes, right? Every customer I've worked with, everything's a little bit different. 

[01:03:11] And you mention something, okay, we've got the data. That's usually the first step. And sometimes that's the hardest step, is to make sure that we get the data in a usable format. Oftentimes, the first step is transitioning from cocktail napkins to using something like a spreadsheet and getting them to a point where, okay, many companies are already there.

[01:03:32] Some are using different systems, ERPs, order management systems. And so it's just a matter of getting data in the right format that's consumable. And that can, once we're there, it's really just a matter of upload that, and get the settings that are needed for the actual route or routes, and allowing the user to make changes.

[01:03:54] That's really critically important because, just because we say, Hey, this is what is the solution. Well, you may have that internal tribal knowledge that says, no, I want to take these three stops and put them on this route, so I drag and drop. 

[01:04:09] And from there, you can just very quickly approve the routes and dispatch them to the mobile device. So when they're playing on the web gets dispatched right to the mobile device and the driver can follow it, again, a very easy to use application, go download it, check it out, let us know. And so the drivers can perform a number of other actions, from marking an address as visiting and departed, to adding a note, signature capture images, various other actions that they can involve.

[01:04:35] And then there's feedback as well. So we can automatically detect when a location is visited, departed, based on geo-fences around a location, so that we know that they're on time, ahead, behind. So it's giving that feedback to the rest of the people back at HQ to understand, Hey, are we actually on time? Are we doing what we said we'd do?

[01:04:55] And so it's a very simple transition for the driver and we really focus a lot on the drivers. That's, that's really our main focus is if we can create a really great experience for the drivers, that's critically important because, of course, the web is very friendly, but it's a very quick process of planning the routes. The drivers are the one that's actually doing it all day. 

[01:05:14] So if they want to hook into, so on the mobile app, if there's 10 stops for their route, and here's the sequence of the stops, all they have to do is click on a little icon, and they can save it as a default. If they want to use Waze, they can use Waze. They want to use our in-app navigation, they can use our in-app navigation. So we present them with choices because we think it's the right thing to do. 

[01:05:38] Jason Gauci: Yeah, totally makes sense. Totally makes sense. Very cool. And so what, jumping a little bit to Route4Me as a company. So you said that you've been, Route4Me has been sort of remote-first, almost since the beginning. And so, what is that like, do you have folks all over the world? Do you have, like, what, do you have a huge...

[01:06:00] Parker Woodward: Every time zone.  (laughter) 

[01:06:01] Jason Gauci: Yeah. So how, how do you navigate all of that? How do you deal with people who are, you know, you have a meeting with somebody in Sweden and someone in Tokyo, it's kind of, how do you kind of get be productive in that kind of global environment?

[01:06:15] Parker Woodward: It's a, well, I think there's flexibility. And so there's a give and take to everything. And there's also, I'd say there's more silos in terms of within the company itself, that you can't have just, all of the  product team necessarily all on different time zones. At the same time, it's really, again, using other software solutions to actually product manage it, so everyone can get assigned work and that work can get done. And, so it's just a matter of making sure that that's being done, from a project management perspective.

[01:06:52] It's kind of interesting because the whole idea of time zones, as long as the work's getting done, that's really what we care about at Route4Me, like do, do good work and do well and get the work done, and just move on. Like there's no need to necessarily have a meeting about this as long as we can clearly communicate. So I think that's probably the really big thing, is communication. And there are a lot of tools from Slack to Skype, to HipChat. There's, I mean, there's all kinds of tools for communication, to Zoom. As we've all found throughout this pandemic, there's many ways to keep in touch.

[01:07:30] And the time zones are one thing, and we do have some folks who shifted their time zones, and because they believe in what we're doing, and the work that we're doing, and it's great for them. So they may be in the European time zone, and working a little bit more in the Eastern time zone. So, it's just, somehow it works. People find a way. I couldn't, I couldn't give you the exact recipe or formula because I think it's unique to every, every business, and it's just what you find in what is so amazing about businesses and building products is that they're all unique the way we do, it may not work for another company.

[01:08:05] Jason Gauci: Yeah. That makes sense. So you are remote before COVID and one thing I've always been curious because, we, we weren't remote before COVID is, do you have like a, maybe like an all hands meeting in person? Like, do you all get together in a central place, maybe once a year? And how magical is that right? I mean, you get to see everyone, in the same room. I think that'd be pretty amazing. 

[01:08:32] Parker Woodward: It is magical. Funnily enough, when I started at Route4Me and I was working closely with some folks, and I actually didn't meet anyone for like two and a half years, like in person. 

[01:08:43] Jason Gauci: Wow. 

[01:08:44] Parker Woodward: Which seems crazy. And it's, it was partly the, the stage of growth we were at. And, but now people come into the organization and we do see each other in person a little bit. Now, obviously with COVID there's, that hasn't been the case, but I remember someone coming into the organization and meeting Dan and George, our co-founders within like the first week. And I was like, man, it took me like three years.  (laughter) 

[01:09:07] So, the pace, the pace of things is, and it's wonderful to see. It's just kind of, sometimes you sit back and, you can't, you can't really put that on someone, to kind of appreciate it, but I certainly appreciate it today. 

[01:09:20] Yeah, that makes sense. So, so for folks out there who are interested in, joining Route4Me, what are sort of the opportunities available?

[01:09:29] Do you have internships? Do yo have full-time  positions? And so what, what kind of folks are you looking for? 

[01:09:35] We do have internships. We are actively hiring. And I would say that that's, in terms of what we're looking for, in terms of folks, it's someone who believes in what we're doing. And I think that's just really critical.

[01:09:49] And, from our perspective, we really are on a mission to save the world. So if you want to join that mission, as much as it may sound, a lot of people may kind of say oh, that's childish or, oh, that's, way too big. I think everyone has an opportunity to make an impact. And so from the perspective of developers, we're always looking for developers. And then we're also hiring in many other roles as well from even just support. I think, that's a wonderful opportunity to get your foot in the door and start to understand, what are these problems that, businesses and people are facing on a daily basis and how can we help them? 

[01:10:26] Jason Gauci: Cool. That makes sense. I think a couple of things that we, we touched on was the API. And so I believe you mentioned That's a place for developers to check out API, but you also have, right? Unless it's somebody else. 

[01:10:44] Parker Woodward: Yeah, is our main website. So if you want to go start a web trial, you can start a free web trial, which includes access to the web and to the mobile apps.

[01:10:54] You can also just download our mobile app straight from the app store, either the iOS, Apple Store or the Google Play store, and start a mobile trial as well. Or just download the free mobile app and use that. I think it enables a certain amount of free routes per month and just play around with it if you'd like, just mess around. But Route4Me.Com is kind of our main site for the actual product, a service of the technology. 

[01:11:18] Jason Gauci: Cool. Cool. That makes sense. So yeah, everyone check that out. It's got a free trial. You could you try a different routes. You could play with the API. I think it'd be really fun. I think it's a good experience to, try out this tech and then even, if you're doing something simple, like figuring out how to route, plan out, as you said, different visiting different houses, if you're apartment hunting in college or something like that, you could give this a crack. And I think you'll learn a lot along the way. 

[01:11:44] Parker Woodward: Yeah. And one opportunity is there's so many really wonderful organizations out there that do a lot of work to underserved communities and underserved populations, I'm really proud that we partner with those communities to help them, get access to our software. And so from delivering meals to the needy, to, there's a lot of different programs and organizations, so you can always find a little niche if you want to get some experience and just kind of say, Hey, I've got this organization and we want to help them. And it's a really great cause, get in contact with us. We'd be more than happy to help. 

[01:12:20] It's really our mission to make the world a better place and save the world. And so whether it's through the API or even just the web platform, I mean, we've helped deliver a lot of Thanksgiving turkeys to people who otherwise wouldn't have them. And so we're really, really proud of that. So get your hands dirty, get involved, find a way to help people and we'll find a way to help you as well. 

[01:12:39] Jason Gauci: Cool. Cool. Do you have a, like a preferred sort of social media for people who want to reach out to you? Either like a Twitter handle or a LinkedIn, people should be able to try and find you on LinkedIn. What's sort of your best kind of POC, point of contact?

[01:12:54] Parker Woodward: Sure. I mean, of course you can email me, LinkedIn's probably the best place to find me. So I think I grabbed that one, and connect with me. I'd be happy to connect. And I don't tweet, I don't do the Twitter just because, I've got too many, too many luxuries becoming necessities nowadays. I can't keep up with it. 

[01:13:16] Jason Gauci: Yeah, you don't, you don't have the Twitter appliance.  (laughter) 

[01:13:20] Parker Woodward: There are, there are appliances aren't there. No, not yet. I suppose.  (laughter)  I'd rather have an authentic voice as long as I can. 

[01:13:27] Jason Gauci: All right. Cool. That's awesome. Yeah, this was amazing. We really dove in deep on, on how this stuff works. I think people, I mean, I'm sure people will get an appreciation for just like how incredibly complicated this technology is.

[01:13:44] And it's amazing that you've made it so accessible to so many people, but we've also given people yeah, the tip of the iceberg. So they can really dive in deep on the technology and, and, really learn a lot of those really niche skills, that I think are going to become even more important over time.

[01:14:03] As, as I say, software eats the world, and then AI eats software, and so, or machine learning, maybe eats software. And so this is right at the heart of some really cutting edge tech, I think is, is super, super exciting. 

[01:14:17] So thank you so much Parker for coming on the show. I really appreciate it. 

[01:14:21] Parker Woodward: Yeah. Thanks Jason. It was a pleasure. 

[01:14:23] Jason Gauci: And thanks everybody for supporting the show on Patreon and on our other platforms and checking out our books of the show when we do that.

[01:14:31] So, thanks for your support. I'm sure you've noticed by now we have moved to two shows a month, and so we're, we're able to sort of ramp up production, reach a whole bunch of new folks out there. And so if you're new to the show, welcome, you can always email us, you just go to and there's a link where you can, you can reach out to us, give us show ideas, connect us to people who would make for a fascinating interview.

[01:14:59] And just don't hesitate to reach out and say, hi, we also have a Discord with active chat going. A lot of people talking about, you know, jobs, announcing jobs, looking for jobs. There's, there's a lot of active discussion as well on Discord, but thank you so much for supporting the show and we'll see you all in two weeks.

[01:15:20] Patrick Wheeler: Music by Eric Barndollar.

[01:15:27] Jason Gauci: Programming Throwdown is distributed under Creative Commons, Attribution ShareAlike 2.0 license. You're free to share, copy, distribute, transmit the work, to remix and adapt the work, but you must provide attribution to Patrick and I, and sharealike in kind.