Modernizing through Data for Literal Growth with Paul Grissom of PAR

Rob Collie (00:00:00): Hello, friends. Today we welcome Paul Grissom, data systems specialist at Pacific Agricultural Rentals or PAR, now that they've expanded from the Pacific coast to the eastern half of the country. PAR is a customer of ours at P3 Adaptive and their business model is fascinating to me. Think about big tractors for a moment, the kind that are used on large farms. In the course of a calendar year, the agricultural industry doesn't require a consistent level of equipment on-site. For instance, if you took the average number of tractors required over the course of an entire year all blended together for a particular farm, that might be like two. It might be the number that comes out. But when you drill down, most weeks of the year that lead up to that two average might require zero tractors. And then there are the occasional sharp spike weeks where they might need like 10 or more on-site, maybe even 20 depending upon the farm, the crop, the specific week of the year, and even weather conditions.

(00:00:57): In that situation, economically, it makes very little sense for a farm to own its peak level of equipment need, only to have it sitting around idle most of the year. That ties up a lot of capital, obviously, requires a lot of upfront investment, and then the storage and maintenance becomes an ongoing cost too. It's way better to have someone else own them, store them, maintain them, and then deliver them just in time in response to your dynamic spikes in need, and that's what PAR does.

(00:01:25): This episode meshes very well with a lot of the things we've been talking about lately. The disproportionately high ROI of Microsoft's modern data tools when applied at mid-market companies, for instance. You'll hear those themes echo strongly here, but the other and just as compelling parallel theme you'll hear is the value of data modernization for businesses which operate in the "gritty" real physical world.

(00:01:51): We first touched on that theme in our episode about the manufacturing industry. And even though PAR isn't a manufacturer, the dots really connected for me. PAR's business shares something super, super important with the manufacturing industry, and that there's a tremendous amount of real-world physical material in motion. And that real-world physical presence actually increases the ROI of data modernization, because even the slightest optimization like 1% becomes instantly heavily leveraged across all of that physical, real-world footprint and complexity. And while we don't typically think of these real-world businesses as the "tech industry", these same real-world businesses are discovering, like PAR, that they do benefit disproportionately from embracing this particular corner of tech and that it's far more in range than it was even like say a few years ago. I really, really like this intersection of data with tangible, real-world businesses.

(00:02:53): I grew up in the construction community. Justin grew up in the farming community. On one hand, we're high-tech people in a sense, but we came from grounded, real-world roots, and the blend of the two is very much in our blood. In fact, I'm realizing how tired I am, a bit of the industries which are detached from the real world like software and finance, and how they get so much more than their fair share of attention and admiration. We all live in the real world, and most companies are real-world companies. So why does social media fixate so hard on the virtual/intangible industries? Let's put a pin in that particular thought. To be continued. In the meantime, let's go talk about a real-world business. It's well on its way to data modernization, and along the way, please pay attention to the kind of person that Paul is.

(00:03:42): He's at the front of the train for PAR's data efforts, and tell me if you've heard this one before, he comes from a non-technical corner of the business. Leaders like Paul are the future of data success, not just for these real-world industries, but indeed for most industries. And when we also talked about drones with freaking lasers on their heads to quote a beloved movie from what is now, unfortunately a long time ago. So let's get into it.

Speaker 5 (00:04:08): Ladies and gentlemen, may I have your attention, please?

Announcer (00:04:12): This is The Raw Data by P3 Adaptive podcast with your host Rob Collie and your co-host Justin Mannhardt. Find out what the experts at P3 Adaptive can do for your business. Just go to pthreeadaptive.com. Raw Data by P3 Adaptive. down-to-earth conversations about data tech and biz impact.

Rob Collie (00:04:42): Welcome to the show. Paul Grissom. How are you today?

Paul Grissom (00:04:45): I'm doing wonderful today. Thank you.

Rob Collie (00:04:47): I love your backdrop. It looks like you're out in the fields. We've already discussed backstage that you're on Starlink internet. You're out there with the earth. I like it.

Paul Grissom (00:04:58): Very much so. The industry also is out in the earth, so not an urban environment, but definitely we are centric to the ag community, which is connected to mother nature and the ground.

Rob Collie (00:05:07): Yeah, it's amazing, right? For example, satellite-based internet, you're not going to run fiber out to all of your locations. I mean, heck, they're still installing fiber optic in our neighborhood. Our neighborhood was built in 2013. If it takes that long to get to my house, probably not going to get to the agricultural networks out in the field. So speaking of agriculture, let's get your job title and where you work.

Paul Grissom (00:05:30): I'm Paul Grissom. I am the data system specialist for Pacific Ag Rentals out of Salinas, California. We specialize in renting equipment to our end users, farmers and growers throughout the country. A lot of hands-on equipment-based type of operation that we run, albeit the data side of it, and technology is a quickly emerging market inside of agriculture itself. We've been evolving over the years to better handle this technology and data information segment that's into the ag industry in general.

Rob Collie (00:05:58): Interesting. If I understand correctly, there's both using data to make your long-standing core business more effective. Are you also saying though that there's almost like a diversification opportunity in your business now, where data is almost part of a product or a service?

Paul Grissom (00:06:14): From an industry perspective that I've witnessed is it's being plastered on top of the agricultural community. And the agricultural community in general. You can think of the stereotypical farmer out in the Midwest that owns 100 acres of ground and farms with tractors that his grandfather had. And that still exists today, but those farmers are aging out and there's a lot of rotation happening with the owners of these farms. Younger generation obviously is coming into power, and the data model is starting to embed itself into the ag sector in general. I like to have a joke about when I talk to people from Silicon Valley and other technology sector areas that if technology is a hockey stick, agriculture is the bottom. We're still touching the puck. You guys are at the top of the stick and we're trying to get to where you are.

Justin Mannhardt (00:07:02): And a hockey reference.

Paul Grissom (00:07:04): There you go. Love it.

Rob Collie (00:07:06): Love it. So we have seen from multiple angles this revolution and slow motion that you're talking about with data in the ag industry. First of all, we've had one of the earliest guests on this show, Gordon Rowe III, is in the agricultural industry and using data directly in commercial nurseries, growing plants for landscaping and stuff. I also remember an ad on football like in the 1990s, about precision farming. They were trying to invent this new term in the way that business intelligence kind of got coined at one point. It was like a deliberate branding decision by someone. Precision farming. I don't know if that term stuck, but I remember being a nerd in the nineties and going, "Ooh, precision farming, that makes farming sound like something I might actually be involved in." And then the last thing I wanted to comment on, first of all, there's a similarity between the agricultural industry and the manufacturing industry in that it's constrained by the real world.

(00:08:03): Agriculture and manufacturing interact with the real physical world in a way that most businesses do not. You have to deal with mother nature, you have to deal with the fact that these organisms take a certain amount of time to grow, all kinds of subtle chemistry and all of that. The thing that really jumped out at me, and I wanted to take a moment on this, talking about the industry is being sort of slow to uptake technology. I actually think that all industries are. You tend to be really familiar with your own industry. You tend to be familiar with your own sins and shortcomings, et cetera, right? You don't see everybody else. This is something I've been saying to people for years, Paul, is that everyone that I talk to says that their organization or their industry is somehow uniquely behind.

(00:08:46): And I just want to tell you that I've heard this now from every industry, every company, it rounds to like 100%. We're all still in a way kind of huddled around the starting line is my experience of the world. You're in good company. Does that feel good to hear or nah, I don't believe it.

Paul Grissom (00:09:04): I totally do believe it in general, so I'll break it down from a end user standpoint and then more of a agronomic business standpoint of technology. So I've been involved in sales and engineering, manufacturing side of the fence as well in some prior jobs that I've been in, and technology definitely has been part of the equation. My startup was working with GPS guidance systems on tractors where we're able to steer the tractors hands-free with a accuracy of plus or minus an inch over, I think it's six miles is what the air factor was, but that was technology that was baked back in the eighties and it took time for that to be adopted inside the ag industry in general. Farmers in general are reluctant to new things. It's such a cyclic business. I plant today, I harvest X amount of days in the future, wash, rinse, repeat.

(00:09:53): I do the same thing over and over and over again. And technology, while it does help them out with their time of the process and reduction in labor, reduction in overall costs of things, it's a building block approach to integrating that technology into A, the farmer, but also B, we're a part of that farming process. Even though I'm not directly a farmer, I've seen technology build upon itself and I can see where we're going to full automation of systems out in the field where there's work being done in a field without anyone being present, which we're on the cusp of that today, but it's taken 20 plus 30 years, 40 years to get to this point, and it still has a long ways to go and especially when we get to the legislation part of that equation as well. It's all about the perception to the grower and how they're seeing technology be applied to them.

(00:10:42): And back to my hockey stick reference, we're on the stick now and things are quickly moving because the technology sector moves at a much more rapid pace than what the ag world in general, in my opinion has experienced in regards to technology.

Rob Collie (00:10:56): Do y'all refer to yourself as PAR at all or P.A.R?

Paul Grissom (00:10:59): It's PAR with regard to, let's call it the country, but locally here in Salinas where the foundation started, it was Pacific Ag Rentals is how the legal entity name. That's how the foundation was, and a lot of the memories are Pacific Ag, but PAR is definitely a countrywide name.

Rob Collie (00:11:13): You're making the KFC transition.

Paul Grissom (00:11:15): Exactly. Well, and it's for good reason too because we've made the leap to the East Coast, which Pacific as an issue on the East Coast, it doesn't make sense.

Rob Collie (00:11:25): Isn't it funny how company names that make sense in a particular context, as you grow, you kind of outgrow the name, so I totally get it. Trust me, I get it. This company started out as Power Pivot Pro and then Microsoft changed the technology from Power Pivot. We're like, "Uh-oh." So PAR is a customer of P3. We help you with some of your data projects. And can we jump in the rewind a little bit and go back to the point when our companies first met? I kind of want give the listeners a little bit of a before and after of your journey and I know that we're not really in the after, it's still in progress. It's always in progress, but psychologically and culturally, where was PAR at with its own sort of internal data at the beginning of this journey, and was there explicitly a theme of let's go modernize?

Paul Grissom (00:12:18): Most definitely. So when I came into the company back in 2018, I came in as a sales manager. Prior to that I was a salesman for a different company. But when I came into PAR, it was very manual, it was very paper-oriented information. Being a salesman at a large company beforehand, I understood the whole process of we got to get information quicker so that we can manage the process, make corrections before we run into an issue down the road where right or wrong, the company at that time, we got the answers at the end of the season.

(00:12:49): That led us manage the next season, but it gave us no opportunity to make a correction mid-course to get to a different result that we may not be happy with when we hit that end point. So when it started was getting the information out to our people quicker, and being as I was the sales manager, I was more in charge of revenue management and getting that information to my sales team, which was only 12 people back at the beginning. Today we have 32. Trying to process that in a manual fashion was arduous. It took days upon days to generate the information but B, also to distribute it. And I knew going into it that this was only going to be a short-term solution and didn't know what the answer looked like for a better distribution method, but we happened to get connected with P3 and immediately figured out that this was the right path to solve the quantity problem and the mass distribution of things.

Justin Mannhardt (00:13:45): Great progress. You got 12 to 32 salespeople. Surely that speaks to growth, not just some chaotic, let's have more people in sales, right? That's exceptional where you're telling that story, describing your previous experience, knowing you needed to not only have the information and to distribute it. That's so important. It's great if some analyst in a corner can understand everything that's happening in the business, but if that's not getting out to the people that can actually influence and do something about it, you're not going to get anywhere.

(00:14:16): And then you use the word immediately. What made it so clear that you would use that word: we immediately knew this was the path/ Most people don't expect to feel that sense of immediate confirmation. They're still sort of wondering, "Oh yeah, we're going to wait until we get to the end of the season and we'll know if Power BI is good." What was the difference for you there?

Paul Grissom (00:14:36): We went through the modeling phase of getting our information flow correctly, which was in our world, that's where I spent most of my time worrying about things because at the same time, I hadn't been exposed to ERPs and basic data flow. I'm not a career data person. I'm a weird person that was ag systems management and ag business and had nothing to do with Excel and spreadsheets and data management in general, but I had a knack for spreadsheets and that's where it all started was Paul and his spreadsheet, building it out, hitting print, and then move on to the next person hitting print, so on and so forth.

(00:15:12): But I spent all my efforts with the modeling of the information that we were to push out to people and realized that the bigger problem was the distribution method and through coincidental meetings of people that how we got connected with P3, I was more concerned with learning about Power BI and watching videos and self-learning, just kind of figured out about the distribution solution that it presents, and no longer worried about that because once we saw it in action for the first time, it was lights out. That was the solution for us on how to get this distributed out to the team out of the gate on our first project. And obviously we're on our second and third projects at this point in time with Power BI and with P3 as well.

Justin Mannhardt (00:15:54): What would you say some of the main differences in either your life or the lives of your salespeople are? Because that first project has been baked... And I'm sure it's been iterated on some, but you're living in this new world now. What would you compare and contrast?

Paul Grissom (00:16:10): We would have to have had hired probably four to five times more individuals that would manage this type of information just to continue down that path of manual harvesting, manual distribution, manual printing. And then the end of the year come back and let's recompile all those snapshots and let's figure out what the roadway that we went. It's definitely been such a transformation that it quickly spidered out into other needs that we identified afterwards, down to our financial statements, down to our variance reporting that we do with our different branches that we have across the country. As the company was growing, area was getting bigger, adding more people obviously to the team. We need to make the central process be familiar, but also handle that distribution issue, and that's where Power BI and P3 came into play.

Rob Collie (00:16:58): We have a bit of an internal theme that we've been, I wouldn't say focusing on, but we've sort of been orbiting it for a while, which is this theme of now you can. All of this really traces back to Microsoft changing the rules of the game, changing the accessibility of data technology, and making it a lot more affordable, not just in terms of software costs, but in particular in terms of implementation time and implementation cost.

(00:17:23): Kind of want to get your reaction to this idea that without these tools which didn't really exist and they weren't popular or in the broader self-awareness much at all until very recently, without these tools, you wouldn't know even what was possible. And the only way to know what's possible is to try them out. You mentioned things like spidering out. That's the good kind of spidering out, right? It's not like discovering additional problems. It's saying, oh, okay, now we get it. The world has changed and we can apply this to so many different things. You have to take that first step before you can really even imagine what kind of impact it has. And I just wondered if that story that now you can and the technology unlocking this and having to discover it, if that resonates with you or not.

Paul Grissom (00:18:05): 100%. Our CEO, Bart Walker, likes to say a lot of times with data, once you have that data, it leads you to more pathways of more questions. And we have to be cautious of that though because more data streams doesn't always mean more information. We try to manage that information flow, because you can get data off tractors or business processes, or billing cycles and all kinds of different things. But at the end of the day, "Am I happy or am I sad?" That's what we bake it all down to. Is this information, is it valuable to the next choice that we need to make, or is there a discovery of another problem? Which data can also lead to discovery of additional problems that one may not know until you start tracking it, managing it, having smart goals and smart measuring activities.

(00:18:49): We were living in the wild west in the world of data management itself, but that spider effect, that was the spark that the platform itself can help revolutionize how we as a company operate internally, but also it's getting that information out to our clients in that same timely connected and distributed manner that I had no experience on this whatsoever when we started. Still today, probably couldn't put together an entire report on my own.

(00:19:15): That's why we lean on experts like you guys to help us with that part of it. But one piece also that did happen just recently was that we decided that we needed to have a Power BI individual expert in-house as well. So back along the way, working with Adam on your team, he explained to us that P3 loves to self-enable the end users, and that was probably a big shift in the way that our management team looked at data was say, you know what? There is a lot of value to this. There's a lot of information that we want to understand, but there's a lot of experimentation that we want to do along the way as well. And so this year we decided to bring on an additional individual to help play with that experimentation in-house a little bit more as we continue our evolution with this.

Justin Mannhardt (00:19:58): That's so great, Paul. That's just so great to me, because you come from a place where you just assumed you couldn't do it, it was too hard, it was out of reach, it was too technical or you were the type of company that did it this way. And then you realize that's not true, and then you realize the spider effect. You can do so much more than you were. It's like, "Hey, this is a thing for us. We can totally do this and we should invest in this capability." not only did you avoid the, I think you said four to five times more staff to support the old way, we're going to bring on the right type of staff.

(00:20:33): And that journey has happened, and when you think about it's not really a lot of time in the context of a company. Two, three, four, years, you've improved your reporting, you've built other systems out and you look back, "Wow, that's a lot of progress," that you would maybe think, "Oh, that should have taken us a decade." And it doesn't. That's so cool.

Paul Grissom (00:20:54): And the company's relatively young too. I mean, it started in 2001 with Bart Walker and his father Charlie Walker and Louie Ray and Carrie Bohr, our controller today. It's grown exponentially since then, so the ERP talk is even more fun to hear, but it literally has started from a single tractor and a kitchen table with the founders and it's ballooned into this giant company. Now that we continue to evolve that pathway and need those data channels to help us shift from a $50 million company to a $200 million company in a matter of 30 years is a pretty great organic discussion.

Rob Collie (00:21:32): In the movie version of this, I can see that in the beginning. They're like, "Well, what are our assets?" "Well, we have a tractor and a kitchen table." "Perfect. We've got them."

Justin Mannhardt (00:21:42): Well, rent the tractor and keep the table.

Rob Collie (00:21:45): Yes. There was briefly a faction that wanted to rent the table and keep the tractor, but they decided...

Paul Grissom (00:21:54): If it's an asset on the books, it's for rent.

Rob Collie (00:21:57): Paul, you mentioned having come from a larger organization prior to PAR. How much larger?

Paul Grissom (00:22:03): Significantly larger. An equipment dealership here in California I was at before, but worked closely with the manufacturing side of it as well, but not really employed by the manufacturing end.

Rob Collie (00:22:13): This is one of the other themes that we've been exploring lately under the Now You Can banner, is the idea that larger organizations had the resources to at least attempt to do it the old way, the really, really expensive way, because there's eventually a point where economy of scale allows you to do things. And so in a weird way, mid-market firms have been kind of priced out of data projects for a very long time where larger organizations, as you move up the spectrum of size had greater and greater access to those sorts of capabilities. By the way, those capabilities weren't great. The new stuff from Microsoft is better. But at least they had something that they could do. My ears perked up a little bit on that.

(00:22:52): You'd seen a higher level of data maturity at the previous organization, but now how would you contrast where you're at now after a couple of years working on it? How would you compare that to where you came from? My assumption is that you might actually be ahead of that organization even though they helped inspire you to get moving.

Paul Grissom (00:23:11): Spot on. I think that the larger the company, the more resources they can throw at it. Efficient or not, it's up for debate. This technology that's available today, at least in the data sector, it's allowed smaller companies to come up to that level, if not, like you said, eclipse that, because those larger companies, they don't turn on a dime, typically. We're a slim company where light people, light overhead and we try to stay nimble with the market at all times. Bringing Power BI into the equation really it took those theories that I learned.

(00:23:40): Actually those theories were pressed upon me. I was a sales rep. I didn't like them back then, but coming into the management sector, they always say, "Step out, step up." But seeing the need for the theories to be employed definitely was something that needed to happen. That was one of the reasons I think what I was accepted into the position I was currently a PAR. But getting those theories stood up and moving was a daunting task at first. How on earth am I going to deploy it? And getting that data model distribution figured, hands-down, it was the solution that we could do. I mean, I can whip together a spreadsheet. I built countless deal calculators that would help us price out equipment with matrices of different programs over time and just all kinds of just crazy things that would happen inside it, but I always call it my palk and brute force his way through a spreadsheet, but when it comes to displaying that, again, don't ask me to rebuild this again.

Rob Collie (00:24:28): Yeah, spreadsheets don't gain momentum.

Paul Grissom (00:24:30): No.

Rob Collie (00:24:30): The sweat equity that goes into producing one doesn't make the next iteration even of that same spreadsheet really any easier. It's peddling a bike up a mountain as opposed to having a powered vehicle.

Paul Grissom (00:24:42): 100%.

Rob Collie (00:24:43): I wanted to take a moment to just salute. You mentioned you're not a lifetime career data professional. You're the right kind of data professional. You're ingrained in the business, you understand the business. You've shown a penchant for spreadsheets, which most people don't. The future of data is more business-oriented and not so much tech oriented.

Paul Grissom (00:25:03): I've seen it happen multiple times where that data individual comes into our sector of ag. And the claims of, yes, we can do this. Yes, it's possible or it's already done. Those claims come through pretty freely, in my opinion, from a lot of that sector, until they come and meet what a dirt quad looks like. And that's where things go just in opposite directions after that. But it happens in the sector all over the place to the physical technology that comes out to the market, to the data side of the fence. Controlled environments are easy to build inside of. The real world out there in dirt and mother nature and rain and mud and diseases and pests and crop conditions and all kinds of different variables that affect our market, there's no clean environment to manage for those.

Rob Collie (00:25:49): Most real world data. No matter what industry it's in, it's not a clean room. It's chaos out there. And the tools better be prepared to meet that chaos and not expect the clean room scientific environment, which is again, a huge difference between this recent wave of tools and even the previous tools from Microsoft, the previous generation, were very much academic clean room tools, and so much of the implementation cost was compensating for the fact that the tools were built for some sort of frictionless world that just doesn't exist.

Justin Mannhardt (00:26:21): Yes, you can have the fun things, Paul, but first we must build you a clean room. Show me to your clean room.

Rob Collie (00:26:27): Where is the positive pressure room that is capable of assembling satellites? By the way, I have been to one client who did have a clean room. I did work for NASA JPL back in the day, which strangely enough operates kind of like a mid-market company. They just happen to be the mid-market company that has a big clean room where satellites are being assembled. But even they have a test yard out back. It's meant to simulate the Martian landscape. So they have it all. They have the dirty and the clean. The whole spectrum of JPL.

Paul Grissom (00:26:59): This is probably a great segue into it, but I think that that chaos in ag in general, but also in probably other sectors as well, I think that's where AI can start coming in to help start smoothing out some of this chaos, instead of having an expert that has been involved in those periods or those cycles of non-measurable information, but be able to see those signals in the noise and start smoothing out some of the roughness of information that's flowing into these different models that we're all trying to come up with.

Rob Collie (00:27:30): There's a lot of precedent for that, even setting AI aside. I remember when we were working a lot with Nielsen retail data, Nielsen didn't have access to every cash register at every retailer in every place. They had a representative, sampling, but no one wants to know what the 3% sample totals to. They want to know the size of the market, et cetera. So Nielsen had to prorate and extrapolate from their sampling to come up with a more volumetrically accurate picture of things. That was all carefully guarded secret sauce. And I was always wondering, how good is the sauce? How accurate is this sauce? That's something that's evolving constantly behind the scenes. But it's a similar problem, right? There's going to be holes. The real world isn't going to be reporting accurately all the time. Like a sensor goes down, what do you do?

Paul Grissom (00:28:23): And it's not just the sensor. If there's rain on the forecast, A, what is the repercussions from this event coming in the world of agriculture specifically? But B, what can I do to prepare for that, or is there some change that I need to make in my planting cycles? And this is where the farmers, I'll fight back a little bit with them about their pushback on the technology and agriculture. They have their entire seasons strategically planned out at the beginning of each cycle that they go with in a year. In the ag world in general, and every farmer sits out with a plan and that plan might have a single crop in the ground for a year, or it might have two to three crops in the ground for a year. But they're using that data to help plan their output. When do they need to have product harvested?

(00:29:05): When does product need to be in the cooler? When does the Costco's and the Walmarts and the targets? What's their expectations? And it all gets driven both ways from that. The buyers are more in control of, Hey, I need X amount of cartons on this day, and the logistics part of it is where a lot of their data is being applied to, but it's slowly migrating its way into that actual; what job do I need next? What tool do I need to put in the ground next? What's the most efficient way to go do this? Oh, I have a rain projection in my forecast in the next seven days. That's going to affect my schedule. Therefore, I need to shift this personnel around to be able to still meet my delivery requirements.

(00:29:45): There's all kinds of data flows now that are coming back from more than just our sector that PAR deals in, but the grower in general has to deal with this on a huge basis from logistics to people management to laws and regulations, and that's another huge nutshell to break into, but I'll digress on that one.

Justin Mannhardt (00:30:03): You said something then earlier, Paul. You used the phrase, I wrote it down, I loved it so much, the perception of the grower. It fits a theme we've also been talking about, which I think is true pretty much for every sector, every industry is the future is AI-powered. It's sort of fantastical to think, oh yeah, we're going to have the autonomous tractors and robots picking the crops out of the ground or whatever, but it's the people in agriculture, the farmers, the growers leveraging these systems to help them make better decisions, react to things that are happening in real time. I related to the other statement you made about, "Oh, we'll get answers at the end of the season." "Well, how's the harvest going to be this year, dad?" "Oh, we'll know when we get there." I grew up in a small town in Iowa. I kind of relate to some of these mindsets. The way you're describing these things, it's not in this, here's how we're going to replace farmers, how agriculture and growers can be more effective, more efficient, contribute more effectively to society as a whole, right?

Paul Grissom (00:31:01): 100% agree with you, and there's all kinds of conceptions of farmers in the world, but at the end of the farmer's probably the most concerned about his piece of ground. He doesn't want that to be something that's overworked, oversprayed, over-applied with fertilizers. They are stewards of the ground first and foremost because that's their livelihood, that's their generational ground that they've had to manage, and it's a piece of pride that goes along with them and data is introduced to them to the level so that way they can manage those controls a lot better and not go too much of this product or too much of that product. They're applying just enough, becoming more efficient with the processes that they're doing. In California, we have a big labor problem. Obviously, a lot of our crops are harvested with hands in the field, not necessarily with combine harvesters in the Midwest.

(00:31:50): So the problems compound, when you start adding people to the equation. More and more controls, more and more issues. And I always hear it from farmers as they get introduced to telematics information or just general billing processes of things. They want to be able to drive by a field and know whether or not either A, are they on track? Are they off track? What are the issues? What I need to do, or who do I need to contact? And I need to move on to the next field. That's what those growers, that's what their lives are all about. They want to grow. They don't want to manage all this information. They want someone to present this in a reasonable fashion that they can quickly look at it, play the red light, green light, yellow light game with them and they move on with life.

Rob Collie (00:32:29): On track, off track is more important even than the actual number. But you have to know the number in order to know if you're on track or off track, but you also then need to know what the prorated version of that number should be to indicate whether you're on track or off track. You work through detailed calculations of actual metrics to then ultimately arrive at on track, off track. And if we're off track by how much, what would we need to get to in order to get back on track? That's what it's really all about over and over and over again in businesses of all shapes and sizes.

Paul Grissom (00:33:01): 100%.

Rob Collie (00:33:02): So that steward of the ground thing, I want to take a quick segue just for a moment. In the 1990s, I remember reading all kinds of horror stories about how we were losing our topsoil and there was going to be a point in time where we didn't have any topsoil left and we weren't going to be able to grow food. Paul, I'm going to ask you, are we losing our topsoil still? Is the sky falling, or is the soil flying upwards? Are we going to be okay, Paul?

Paul Grissom (00:33:24): I am not 100% an industry expert in that, but I think in general the farming culture has changed so many different ways over the years by what institutes have pushed out that they're regenerating soils these days. In general, that's where it's leaning to. It's not the dust bowls of the 1930s, 1920s. There's talk in different areas. I know that's a big problem out in Europe where they're worried that their soil conditions are diminishing to the point where they're going to be unfarmable in the next decade to 20 years from now.

(00:33:53): That need has evolved the ways that the farmers are engaging soils or managing animals, and they're really conscious of, I need that soil healthy and it needs to have long legs. And if I can create more topsoil or more healthy conditions, then that's going to be for the future generations moving forward, but tillage practices have changed. Yes, it's data-driven, but it's more of a cultural practice change of things on how tools touch the ground. But a lot of the data world has shifted when it comes to chemical application or pest control or disease avoidance. That's where a lot of the more scientific applications of a lot of this measuring, reading, going back and getting results driven changes to happen out to the farmer.

Rob Collie (00:34:37): I kind of had surmised that this particular doomsday scenario, we weren't on course for it anymore, because I haven't been hearing about it. So it's super reassuring to hear, but it's also kind of heartwarming too. So many industries now are optimizing for absolute short-term gains, short-term profitability to see any industry that is taking care of its future self. Let's look at what the ag industry is doing. I didn't even know until maybe, I don't know 10 years ago how important the United States agriculture industry is even on a geopolitical level.

(00:35:13): The United States' ability to grow food is like a strategic advantage for the United States. One of the reasons that's been surmised for Russia's invasion of Ukraine is Ukraine's grain fields, their ability to grow food. It's just like, whoa. Imagine invading another country to take their farms. Yes. United States and its agricultural capacity. We are really, really blessed as a country to have it. Most countries don't have the ability to grow food at the scale that the United States have. If you grow up in America, you're never really aware of this, right? You just kind of take it for granted. No, it's a big deal.

Paul Grissom (00:35:49): Oh, 100%. It's funny too, as in my area over here in little Salinas, California, they call it the salad bowl of the world. It's 70 miles long by about 30 miles wide, and that's where the vast majority of fresh vegetables come from that gets distributed out throughout the world. And just a small spot like that when it's lettuce, strawberries, celery, cauliflower, Brussels sprouts, you name it, if it goes on a plate and it's a vegetable, chances are a lot of times you're going to touch it from the ground that's out here in Salinas. The farmers have realized that they need to diversify as well because that small spit of land, they're not making that ground anymore, because of the climate, the great environment that it takes to grow a good head of lettuce. They're trying to figure out ways in other places to be able to still grow that product and have a more constant stream.

(00:36:35): In the event that something happens, a pest comes down. We had this big fire in the mountains around Salinas about four years ago, and no one really thought too much about it from the farming aspect of it, because it was up in the mountains where there's brush and trees and this big wildfire. Well, the consequences of that is that it pushed a bug down from the trees in the brush, came down into the valley of Salinas and it started decimating the lettuce fields. It's called thrips. And it's something that's here to stay now, so they're constantly working on trying to keep that pest. It is a bug that just pokes the lettuce plant, and then once you poke a lettuce plant, you've all seen it in your refrigerator as it starts turning pink and then it rots out.

(00:37:13): That's happening out in the fields today, and it's been better control of it because we've been blessed with much more rainfall over the last two or three years, so the pressure's been pulled away, but the pest issues just compound when other events happen from a geographic perspective. Similar issues happen in the Midwest and corn and soybeans and wheat. In a very hyper-focused zone out here, it's very interesting to watch the cycles of things. Those measurements that aren't predictable and you can't record them until they happen.

Rob Collie (00:37:42): It's like this biological, almost like single point of failure type of fear for the food supply. In an Old Testament sense, you hear about plague, okay, that's disease for people, and then it's pestilence and locusts, right? It's like...

Paul Grissom (00:37:59): That's farming.

Rob Collie (00:38:02): Wow. We haven't talked about the core of your actual business yet, so I think people probably have been listening so far. I could probably start to surmise it, but what's the core business for PAR?

Paul Grissom (00:38:11): So we provide at the basic level, equipment. No matter what type of equipment it is or what brands it are, we provide equipment to growers. Our specialty is growers who have high demand usage over peaks of time, where it doesn't make sense for the grower to own everything that they'll ever need all at once. We like to coin ourselves as we like to be that supplier of that equipment when they hit their peak busy times. We buy and rent and sell and rent to own equipment, tractors, implements, all kinds of different services when it comes to managing and maintaining the equipment, you name it, but we are the cornucopia of equipment that we try to offer to the growers. Where we go, we try to find out what is it that the growers need? What could we introduce to them that's going to either help them learn a new way to do something that we might pick up in one region, bring to another. But at the core business is buying tractors and then renting them back out to growers throughout the country.

Rob Collie (00:39:06): What a cool business model. I like that. I knew obviously you rented agricultural equipment to farms, but I didn't understand the market forces that made that business model so important and so valuable. It's that peak usage. Sometimes I need a tractor, but every now and then I need five. So do I go and buy five and tie up all that capital? Do I even have that much capital? The ability to operate a farm that requires peak surges in equipment without having to own the max level of equipment, that makes a lot more farming possible. It probably makes a huge difference in how much food costs eventually all the way down the line at retail. What a cool thing. I love it.

Paul Grissom (00:39:46): It's never boring, I can tell you that much.

Rob Collie (00:39:48): What's the fastest turnaround that you've... Just anecdotally, someone discovers they need a tractor or they need a piece of equipment. Sometimes you might discover when something breaks, we need replacement or whatever. I'm almost imagining like, "We're helicoptering it in the 60,000 pound piece of equipment."

Paul Grissom (00:40:04): Sometimes we'll get the phone call that something's broke down or even our own equipment. I mean, they're tractors, they're built by people and they break down. Well, we swap them out and they'll be same-day delivery or same-day swaps, or machines broken down on the back of a semi-truck is when we'll get the phone call and we have to spin up another machine to be able to get back on that same truck that's going back to the field that that broken one came from. Our speed of service is what... I talked about that in both size of business. Well, the core of the business is built on being fast response.

Rob Collie (00:40:31): This isn't delivering pizzas, right? Talk about physical constraints, which also means that you have to have some buffer of equipment like bench equipment essentially in inventory, relatively close to your end customers. It's not like a tracker is going to get there. If it's 500 miles away, it's not going to get there same day. It's not going to get there overnight. What an incredibly complex problem. I can understand where data might be helpful.

Paul Grissom (00:40:56): It's very much like the airline industry. We always want to be overbooked, but at the same time, we only have so many seats.

Rob Collie (00:41:03): Operations like this and sort of like the optimal way to conduct them. Have you ever heard the rule of thumb for a restaurant? The ideal open number of tables is always one open table? It's not zero because you want the new customer to be able to come in, but you don't want more than one either because that means you're not at capacity. Such an odd paradox that once you think about it for a little while, it totally makes sense. You always want one open table. Precisely one. That is perfection. It sort of reminds me of what you were saying. Oversold but not really oversold.

Paul Grissom (00:41:36): Again, that's back to something that you guys are helping us with is being able to track a metric KPI that's incredibly important to us is our time utilization on the assets. And we intrinsically know we have a lot of people who've been career long rental equipment people in the company and have come from other large companies, but we all know that once you get a certain percentage of utilization, it's not healthy, positive or negative during your seasonal swings of things.

(00:42:04): We're right now building out some KPI dashboards for our shop management and our leadership to be able to measure those time utilization metrics on a live basis so we can better understand are we about to hit a problem, or are we coming into an off time. And being able to measure that and see it without feeling it is the key to our growth outside of the realm of what we can see out the window. When the company first started, when it was just one branch, it was easy to measure time utilization because you just look out the window and is there tractors on my fence, or is it just bare fence? It's hard to do in California when your tractors are sitting in Georgia.

Justin Mannhardt (00:42:39): Thinking about the situations you were describing, I am sure there's some amount of your business that's planful, and the Owens are going to need a rig in this month or whatever it is. But it is so live action, understanding what's happening in real time all the time. And so obviously, better reporting, better data, better distribution of that has been a big benefit to you. But you've also then stepped into the world where you actually collecting and modifying data in your Power BI environment as well, which is something that I don't think people naturally think of. I'm just curious if you might describe what that planning project has been like for you guys where people are actually sending signals back, inputting forecasts and things like that.

Paul Grissom (00:43:22): So that one, we stood up Acterys with P3. And it was the first tool that we're putting out into users' hands that is getting feedback. And today I think we're still at the foundational steps of that on getting that feedback approach inside the tool, but that process also monumentally shifted because again, it was one of those processes that was done with Excel spreadsheets, where I send this branch manager gets a spreadsheet and that branch manager gets a spreadsheet, they make their notes, make their inputs, and then everyone sends it back in and then someone's going to recompile all that to a central point and then redistribute that back out again as the final product and then go fix the errors and blah, blah, blah.

(00:44:02): Just solving that process alone with Acterys and P3 was a monumental shift and it gave back our controller mountains of time. She can better spend now on managing the business functions, not necessarily just the flow of spreadsheet land. That was getting out of control really quickly, especially as we add more branches, add more people.

Rob Collie (00:44:22): Justin, isn't that one of the phrases coined by another one of our customers? Let's get it straight. We don't save time. We create time.

Justin Mannhardt (00:44:30): Yeah, we create time. We created time for the controller. I think that's an important way to think about it. I even think about this when people say like, "Oh, don't you want to save money?" "Yeah, but for what?" You want to save some time, but for what? I want to create time to do something more valuable. That's fantastic. I remember being in some of those meetings where... I was on a couple of those meetings where I forget her name, the controller was-

Paul Grissom (00:44:51): Carrie Bohr. Yeah.

Justin Mannhardt (00:44:52): Yeah. Carrie explaining the hell that was her life in that process, and just be like, "Yeah, we should fix this." Not simply because the process could be better. I think that's just an important thing, like creating the time for the team to better understand the information, to be more effective in what you do about the state of things. I mean, if all you're doing is shoveling dirt around, it's like what am I going to stop and think? Is this a tomatoes year or an onions year, right? I don't know.

Paul Grissom (00:45:23): No, definitely, we like to say we need to get away from working in the business. We need to work on the business. It's been a fundamental shift in the way that the senior management team is. We've shifted that focus of the company and becoming more process-oriented from a company's management perspective versus even three years ago how we were on the senior leadership team, but we were also cogs in the wheel at the same time. And stepping up out of that realm of having my hands on every single cog in the company, it doesn't scale. And we need tools in place to be able to step back and step away and have that perspective of working on the business, not in the business at all times.

(00:46:00): Again, that's where a lot of this reporting time creation has come from by implementing Power BI into the simple stuff, the simple KPIs of things, getting that plastered into shops so they know here's my inflow of equipment, here's how my shop is doing on key supplies, expenditures at this point in time for this month and year-to-date and my full year cycle of things. Just getting those simple fuel gauges that we put together, it just frees up everyone from having to remember. I can quickly look at those things and then go back to working on the business rather than inside of, am I happy or am I sad?

Rob Collie (00:46:39): This is something that studying the disruption and the opportunity posed by AI has actually helped me understand about kind of everything. It's been a valuable lesson to learn even if AI wasn't such a big hot topic these days, which is there's so many jobs, tasks, roles, whatever. If you think of it as like a cloth, as like a fabric for a moment, most of the threads in that cloth are manual drudgery work, but it's interwoven between it, the super intelligent, the savviest parts of the process. So for example, with your controller, when you're doing it manually, you're doing these big processes manually, the intelligence and the experience is unique. If there's going to be a manual process to do all of this, it's going to fall to them.

(00:47:24): Because things are so interwoven, each individual task that's being performed, that's the manual drudgery in that process. Sure, that could be done by someone else, but that other person wouldn't know to do it and when and how. The only way to pull it off when it's manual is to saddle one of your most important knowledge workers With that drudgery, again, AI kind of helped me to tease these things apart. And so when you're able to implement the right software, the right technology solution, it allows you to encode a lot of those business rules. If you can encode them once and have them run forever like that, then it's actually worth it as opposed to turning around and telling someone else what all the rules are, you have to be telling them the rules over and over and over and over again. It would never be efficient and it would collapse, which is why it ends up falling all on the controller or on the CFO, or we've seen this over and over again where people in roles like that end up being the center point for all these really complicated typically spreadsheet different processes.

(00:48:27): I think it's been really enlightening to me to say like, "Okay, this drudge work almost by definition, it's going to fall on some of your most important thinkers and drag them off target from the places where their high leverage brains would make the most impact." So it's really always gratifying to see, again, when we create time for those people.

Justin Mannhardt (00:48:48): Paul, I'm just curious, even in the abstract, you're a great story of a company that you've grown a lot in the last few years. You made a lot of progress on your data maturity and your capabilities. What's next? I'm sure there's no shortage of things you could do better with data. It's true with almost any company. You mentioned AI earlier in our conversation. What are y'all thinking about with how AI might impact your business directly, your industry? What's next for PAR?

Paul Grissom (00:49:15): We're always looking, I'd say firstly at product offerings and how that technology can be applied to the ag world in general. Even today, AI is already making its impact. Weeding systems is something that I never would've thought five years ago that's where technology was going to start being applied to, but we already have in our fleet tools that go in the back of our tractors. And we rent the tractor and the tools that goes out and travels up and down the fields and just takes thousands and thousands of images and is comparing those against the core data sets of things that are good and things that are bad.

(00:49:49): We were one of the first ones that imported some of this AI-driven technology to be able to help identify weeds in the field, so that way instead of bringing out busloads of people with mechanical means of removing weeds in the field, it's a single person on a machine effectively weeding mechanically, or even today we're using lasers. There's laser weeders out there today. We try to get them to play Star Wars theme song, have the Darth Vader sound come on when it starts this process. But AI is starting to figure out what a plant is, and that's where I think the core from an application standpoint of where it's leading to.

(00:50:27): And big companies, the John Deeres, the Agcos, the Case New Hollands of the world are really driving on their rendition of AI in ag as the autonomous machine, which I think is part of a greater picture to the farmer. I was a sales guy for 12 years, and so I can say it, we sold power units. The farmer, at the end of the day, with tractors, it's all about I need power in a package that's sized to this that has the capabilities of fitting in X, Y, and Z dimensions. And at the end of the day, that doesn't do anything. That's horsepower. That's all that we consider the main piece of the focal point of farming.

(00:51:05): The business end is always on the back. It's the implement, it's the work that's being done where the tools meet the ground. And fortunately and unfortunately, the big dollars in the industry I think are being spent on things that are going to protect market share for those large corporations. But what's more meaningful in my opinion, is what's going to happen on the back. That's what speaks to the farmers, that's what speaks to the growers, and I was really happy to see a lot of these innovations coming out in Salinas and vegetable industry took this on pretty quickly and we're shaping Salinas as kind of being an Ag tech sector of the Ag world where we're bringing a lot of students from schools and really trying to create an environment where they can help create some of these technologies that are going to apply to the farmers directly in a quick manner.

(00:51:51): But going back to the AI side of the fence, that AI technology integration, it is starting, it's here already. It's already applied into the field and it's already touching dirt. I mean, I can take you out to a field and watch a giant machine, slowly move through a field and watch little poofs of smoke come off the ground because the images are being taken and it's being compared to a mass set of images and deciding whether or not that's a plant to keep or a plant to kill.

Rob Collie (00:52:16): Google tricked me or enticed me to install their just Google Search app on my phone strictly because I can point it at a plant now my camera and it'll tell me what the plant is. It's so cool. Of course, it's just the obvious next step to attach a laser.

Paul Grissom (00:52:34): Why not.

Justin Mannhardt (00:52:35): The story there Paul was saying about the tractor and the implement or the front and the back, I actually think that's a powerful way to think about innovation in general. What does the tractor do? Well, it drives up and down the field. Whether it's got a farmer behind the wheel or a robot or a computer, it drives up and down the field. But when you ask what is the tractor doing? Is it helping us get weeds out of our crops? Whatever might be happening, and so I think you could translate that same idea to AI implementation. I'm a believer, yes, there's going to be things that get replaced by AI. The tractor's driving itself, what's really changed for the world. Farmer can have more land and more tractors, but now he's got more places to go fix the robot tractor. I don't know.

(00:53:20): What are we actually innovating? What are we doing? There's a lot of thinking today about how could we automate things or replace the knowledge worker? How can we make it more effective? What are we actually doing with what we're innovating on? It just struck a chord with me, Paul. That's such a brilliant way of thinking about it.

Paul Grissom (00:53:38): My passion has always been what happens on the back helps drive the sale on the front. And if you can become that voice of confidence to the growers about: hey, have you thought about this? Have you tried to do something different? That's where you can start making changes to the effective way that the growers are operating. But there's so many different things being tossed out there in the marketplace that it's extremely complex to be efficient at your choices. And something that's I think coming and we're attempting to build at the same time is trying to get the raw data out in the field. What am I doing? What am I doing it with? What times am I doing it? How much fuel is being consumed by doing this job? Trying to get that into a centralized point where something can read all that information and make a best guess as to make suggestions.

(00:54:28): Ultimately, that's what data, and I'll speak to telematics, it's another one of my pet projects that I work on all the time, is trying to get that digital information of what's happening out in the field to the equipment. How do I tell the computer? How do I tell the data of is that job being done effectively or not, or is there a better solution for it? That's how the growers are going to reduce their input costs, their CapEx.

(00:54:49): Everything's going to change based on how technology impacts the actual physical size of machines to what implements are on the back to what the capabilities are of these things. Talk about swarm technology with farming robotics. There's a lot of different companies that figures better. Well, back in the '80s and '70s, there were studies done that yes, absolutely bigger horsepower, bigger tractor, more coverage with one person because that's me as a farmer. I'm a one person operation. I can do more. Well bring technology, bring ai, bring automation into the game. Now we're talking. Well, why do I need one tractor? Why does it need to be so big? Let's clean slate the whole thing about what is a tractor in general and let's start talking about what am I trying to accomplish, number one? And let's work our way back from that end back to the front, not from the front to the back.

Rob Collie (00:55:37): I love stuff like that. When there have been factors that have shaped an industry forever and then those factors change, it takes a little while to realize that, wait, all the things we've assumed and just sort of held as key principles forever were because of that other assumption, that's no longer true. Really nerdy example, like when we switched from in software, the AI software in particular, when we switched from being hard disk based in all of our storage of analytical data to being in memory, we realized all the things that we had been doing only because of the disk with a physical mechanical head that had to seek back and forth to find the right track on the record.

(00:56:18): And so many things like, oh, whoa, we can store data in columns now and not in rows and oh my God, we can store data in columns. That means X, Y, and Z. We can compress better and everything gets faster. It's just like some of those rippling changes are some of the most exciting and gratifying to be a part of. To hear that happening, again, I just used a hard drive versus RAM analogy, which again, by the way is physical world. It's the physical world impacting the way computing works, right, and so we're talking about the physical world again here. Do you think we're going to end up with a bunch of mini tractors like drones?

Paul Grissom (00:56:51): Jury's still out on that, but yeah, I keep waiting for the hover tractors to show up.

Rob Collie (00:56:55): Yeah, I don't know. That might be... I mean, but you could imagine a flying drone weeder that's packing the laser. I mean we're getting closer and closer to Terminator here.

Paul Grissom (00:57:06): It's getting crazy out there. Not only Amazon package delivery, but we go out there and spray a weed.

Justin Mannhardt (00:57:11): Are you renting drones?

Paul Grissom (00:57:12): Not flying ones, no. We do have the swarm technology in our fleet today too though. It's a company called Burro. They're out of South America. It's a wheelbarrow. It's an automated wheelbarrow that can take an image of a person and then play follow the leader with that person to help them carry something. It's just got four wheels and it's a flat top device, but battery powered that drives and just follows the person, which helps in the fields for picking table grapes is one of the biggest applications that we use this one in for, but there's also other applications for it. Think of it as a team of them can become a mobile conveyor that you could set up in no time flat and then pack it all up and drive down the road and then unpack it and then create a new mobile conveyor from point A to point B. Nurseries use these things. There's all kinds of applications for this type of technology that's quickly hitting us square in the face.

Rob Collie (00:58:03): Yeah, I remember Boston Robotics with their, what was it? Something dog? Was so terrifying a while ago, right? Its original purpose was to be basically like a pack animal for soldiers carry their gear across all kinds of terrain. So neat.

Justin Mannhardt (00:58:20): Call us back when you get the laser drones. We're going to have a episode two.

Rob Collie (00:58:25): I want drones with fricking lasers on their head.

Paul Grissom (00:58:30): You're going to laugh, but there are ones with essentially a paintball gun attached to them that shoots in the tree industry. If you don't harvest all the fruit, the pits left on the tree and they have to shake those. It's almonds. They have to get those husks off the trees before the next cycle of blooming and growing almonds. Well, there's technology out there that I've seen with my own eyes that there's a flying drone with basically like a BB gun or an airsoft gun attached to it and it moves in throughout the tree canopies and targets those husks and knocks them out one at a time.

Rob Collie (00:59:01): So neat.

Justin Mannhardt (00:59:02): Yes, sir. Let's go.

Rob Collie (00:59:06): Five years ago, my neighbor brought out a drone and it flew my roof inspecting my roof for hail damage. It's not pre-programmed for the shape of my house. You just let it go and it figures out its search pattern and just traversed the whole roof and I'm sitting here watching it going like, "All right, yeah, this is cool and scary."

Paul Grissom (00:59:27): There's always a counterbalance to it. The light and the dark side of the force.

Rob Collie (00:59:31): We've got to lean into the light side. I'm not the one that says we shouldn't have these things. Can these things identify weeds at night?

Paul Grissom (00:59:38): Oh, yeah. It's all NDIR, the camera systems that they use, so we actually put shades over the cameras and then they have high intensity lights that match the camera's capabilities and so it can get a better contrast of plant versus ground number one, but then looking at... Because it's a top-down view, then it's taking those identified plant zones and then trying to identify what type of plant it is. And there's different AI models that will look at either plant identification to keep and kill, or size-based as well because a lot of times, at least with our growers that we over plant the field mainly so that we can ensure that we have a good harvest at the end of the day and then we come in and thin the field out at a certain point. Well, once you come in and create the beds that the plants grow on, you still have weed pressure no matter what you try to do.

(01:00:25): Soil is never sterile, it's never a fully controlled environment, so you stand up the lettuce on top of this bare dirt and then take the image over the top. Well, you can start being able to see the contrast between the plants and the non plants. Some of these AI systems that are out there today are even to the point where they can identify in a fully weeded-out bed, totally covered with weeds. It can find the kale plant in the middle of that and then kill everything else around it and just keep the kale plant alive. It's pretty wild.

Rob Collie (01:00:53): And that system, these systems you're talking about can now operate during the half of the day when the sun isn't shining. Even that huge change to fundamental assumptions in the entire industry, how long does it take to weed this field? Even if you didn't have automation at all, but you were able to work at night, the number of days require?d half as many days, right? It changes the logistics of everything.

Paul Grissom (01:01:15): Top to bottom. And then the swarm technology side of it compounds even further. Okay, I have a broken tractor. Well, would I rather have a small one of swarm based machine broke down or a million-dollar piece of equipment broke down sitting on the side of the field? Well, if I had 10 of the small ones, well I can repurpose, reorganize, reshift my application to be able to still continue work for it, versus the other model of I have one of and that has failed, therefore no work is no longer being exerted.

Justin Mannhardt (01:01:43): When I was in high school, the way we'd make money to go to sports camps as we would go out and de-rogue the cornfields. Just walking to the cornfields end to end with a little hook cutting out the rogue plants. Yep, they do those with drones now. Back in my day, we had to walk both ways in muddy boots, in the rain.

Rob Collie (01:02:06): This is a terrible blow to the American culture. De-roguing those cornfields built character in you, Justin.

Justin Mannhardt (01:02:11): It sure did. These kids aren't going to know.

Rob Collie (01:02:15): Did we close the loop on the budgeting and forecasting tool? Because I think that's a really cool story. I know that we told probably two thirds of it. I wasn't sure if we got all of the texture there, though.

Paul Grissom (01:02:26): We're still in process of flushing that completely out. The main core goal of mine with deploying the Acterys platform inside of our financial department was to free up time not only to our controller but also to all the other staff that needs to view this information on a more timely basis. It gave us a lot of different insights to doing exactly what we were doing before. And as short of a scope as that is, that was the goal number one. The second part of that though comes in, okay, now we have this centralized connected source of information financially, and we can start drawing KPIs off of that in a connected manner. Now we're creating dashboards utilizing this centralized point of financial data to start driving operational changes down to the shop level, down to the technician level, down to the tractor, to the asset level.

(01:03:18): Do we need to increase fleets? Do we need to decrease fleets? Well, what type of machine in the fleet? Do we need to categorize everything in the fleet in its own category and class of things? And we're starting to translate a lot of our financial KPIs, the good and the bad of the finance world, which I'm definitely not an expert. I'm not a CFO. We just hired one earlier this year too. So he's taken over a lot of that realm of it, but getting that to the operational level has always been a trick because at the end of the day, if I'm happy or my sad is based on everything in the same bucket, where now we do have the capability to start segmenting down, are we buying too many Kansas WD40? Are we starting to need more wrenches for this branch in this district versus waiting for the final result to come through and seeing if we're on budget or off budget?

(01:04:04): Well, now we're able to dive deeper down into those results to find out where's the signal in the noise? Call it transformational, but it's more evolutionary, getting that pure hardcore financial world to start stepping out into the operational world to understand if we're meeting our net income goals, well great. Where's that signal in the noise? We can always do better. Where am I happy? Where am I sad?

(01:04:28): Getting Acterys stood up and getting operating to repeat exactly what we were doing before was monumental number one, because of the time savings, but I still think there's a lot of runway in front of us about where that's going to lead us down the road. I don't know where we're going to go yet, but we're already starting to connect the KPIs and display that to employees, specific ones, not all the financials, but specific financials that a department's in charge of or a core group of individuals that oversee multiple departments of this.

(01:04:56): Getting the right information out to the right people so they have that information in front of them to make those operational changes has been probably one of the biggest changes that we've seen so far. But there's so much that I can see coming down the pipeline of having this interconnected abilities now we didn't have before. It was a spreadsheet waiting for it to be published.

Justin Mannhardt (01:05:15): Acterys is a cool tool. The way I like to think about it, business intelligence is a loop. A lot of times it operates as a one-way street. Data comes out in the form of a dashboard and somebody reads it and okay, now they've learned something, but there's a return process too, that completes the loop and I think what Acterys has allowed our customers who are using it to do is to get into a situation where you can almost actually see the future. It's one thing to sit around and say like, "Oh, Paul, what do you think your sales forecast for the next quarter is?" But to get your team where they can input assumptions and input their forecasts and their plans at a similar or the same fidelity is what you're going to get in your actuals?

(01:05:55): Oh, we can see the future and if this is the future, we need to order more of this and less of that, or we need to staff here differently or we need to reposition some of our assets. It's such a different way of thinking about integrating your BI with your planning, and creating a full application life cycle that's not just regurgitating information, but it's a whole cycle of collaboration that very inspiring to me anyways. When you think about a company like PAR, similar size team, similar size company within a couple of years can modernize their BI and their reporting and their planning and analysis. Now you can. You can totally do this stuff now. It's very in range. It's accessible, it's affordable. The tools are there. I think it's just awesome.

Paul Grissom (01:06:41): I wasn't around obviously when the company was founded, but I can only imagine the iterations and the time involved to get the manual process to the point where it was that it was working, but when we stood up Acterys, it was over a matter of I think three to six months. I can't remember exactly, but we basically fast-forward to that entire process that was done to build those financials to that point, and then be able to get that exact same functionality out in that shorter period of time with someone who wasn't at the helm of doing that process before. I was not integral in building of the books, but I can take that model, work with P3 and with the Acterys folks and be able to replicate that process and be able to get that distribution checkbox done, be able to get deeper dives into the information.

(01:07:28): There's just so many more different abilities once you get a centralized point. I always like to call it the single source of truth that in the manual world, there is no single source of truth. Once you establish that philosophy, then management becomes more effective. And we touched on it earlier too, about having those processes locked up in someone's core way of doing business. That's all fine and dandy until I always play the game; Paul's not here today. Now what? And without having those documented processes down either on a piece of paper, written out or coded into something that's more integrated or more complex like a financial model is just an absolute must in today's business. There's no ifs, ands, or buts about it. We've got to be able to have that process be not just stagnant, but have it moldable. Let's not manage the work, let's manage the process.

(01:08:15): If something's wrong with the process or something's wrong with the SOP or whatever it is, let's make the change there. But the KPIs give us those signals of whether or not something is good or bad and having those financial controls in place now with Acterys gives us that ability to; let's standardize our distribution of cost. Let's standardize our flow of building the budgets with the branches moving forward. And if we get to the point where it doesn't work anymore, great. Instead of reinventing the wheel, let's go back and remold the Acterys model to fit the business needs.

Rob Collie (01:08:45): When we were preparing to record this episode with you, Paul, Adam and Leanne, we talked to them a little bit about the work at PAR that we've done with you. And one of the things that jumped out at me was this notion that in this forecasting process, just having people participating in the process, in the form of annotations on their individual forecasts, even if they weren't providing their individual forecast yet, if they were kind of being sort of like top-downed a little bit.

Paul Grissom (01:09:09): The process you're describing, we call it variance reporting, and we give those responsibilities to those branch managers or those cost centers or revenue generation sites. We want them to be the masters of their story. We want them to be able to read the information, read the results, and understand what's happening, what needs to happen moving forward, good and bad. It's not always just about the bad side, which everyone thinks. It's all, let's just focus on the bad, focus on the bad. Well, with us, we try to make sure that we're talking about the good as well to understand what those impacts are too.

Rob Collie (01:09:37): Yeah, fix the bad, but replicate the good.

Paul Grissom (01:09:39): Yeah, fix the bad, replicate the good, but also understand what is the good going to do for other things that it might be interconnected. The trickle-down effect happens quite often, at least with our business model, and it's a lot to do with just how the farming sector is. And if we knock it out of the park this year, we need to be able to, A replicate that, but B, understand, is it a nature of the beast? Did we do great because a market was hot and growers needed everything? Hemp came in two years ago, three years ago, came into the market in California and it felt like it was going to be a gold rush boom. We sold tons of equipment, we rented tons of stuff. It was gangbusters for about six months, and then that went away, but with the financial history and be able to recall that really easily back to the branch manager level, they can understand that was this an anomaly or is this a repeating pattern that we need to prepare for?

(01:10:29): Having them have that ability to record their results and their commentary against those results helps give that accountability level back to the owner of those systems and then also, I'm as guilty as the next person. I can't remember what I did yesterday. I can't remember what I did a year ago. But being able to have this centralized system where I can go back in time, I can go review those results, I can go review my commentary, and our process was awesome, but the recording and record-keeping, and that's where we used to be weakest on, which I think that we've absolutely solved that issue moving forward.

Rob Collie (01:11:03): I love the human factors of that. Echoing back to Justin's point of turning it into a loop, also the point that information is worthless unless it turns into improvement, and then you're about transitioning to being a process-oriented organization. Well, you can't be a process-oriented organization without this individual accountability and that you can't have that without the individual access to data and the individual access to the ability to add the annotations and explanations and all that kind of stuff.

(01:11:29): It gives people a hand on their own steering wheel. And you need that. You need to be able to cascade that out through the entire organization at multiple levels to be effective, and so it's always a mistake to be distracted by the technology. The technology is there to do something for you. But measure its impact purely through that human lens and don't miss out on the important changes that are happening that are kind of, again, enabled by the technology but have nothing to do with it. That's where the real benefit is.

Paul Grissom (01:11:56): We coined that one as Don't get distracted by the shiny spoon.

Rob Collie (01:12:00): Well, listen, Paul, thank you so much for your partnership in business. Specifically, thank you so much for spending these couple of hours with us today. Again, time is super valuable. We really, really, really appreciate you being here to tell your story.

Paul Grissom (01:12:14): No problem. It's been an absolute pleasure working with you guys with P3 in general. Today has been an awesome time to be able to talk and tell our story and explain a little bit more about who I am and the crazy world that we live in that isn't in the middle of Silicon Valley, even though we're only 30 miles away from there.

Rob Collie (01:12:32): Well, listen, I just want you to emphasize again the idea that you and your organization are now ahead. And I see so many companies, I see so many industries in my day to day. Yeah, welcome to the leader. You're at the front of the Peloton.

Justin Mannhardt (01:12:49): You're up on the tape, man. Up here on the tape.

Announcer (01:12:53): Thanks for listening to The Raw Data by P3 Adaptive Podcast. Let the experts at P3 Adaptive help your business. Just go to p3adaptive.com. Have a data day.