Connecting Farm Data to the Agri-Food Industry

In this episode, Thomas Slattery speaks with Rich Vecqueray, CEO of Map of Ag, a data business that connects farm data to the agri-food industry. Rich explains how Map of Ag brings together farm data at scale so that the industry can connect with their supplying farms.

Rich talks about his background as a vet and how he became frustrated with the lack of influence he had on improving animal welfare on farms. He then explains how Map of Ag evolved into a platform that brings together farm data at scale, enabling the agri-food industry to connect with their supplying farms and drive meaningful change.

Rich goes on to discuss how Map of Ag's platform, Pure Farming, collects and integrates data from various sources across many different farmers to provide insights and make better decisions at the agrifood business end. He also shares how the platform is being used to help achieve net-zero emissions and solve other problems in the supply chain.

This episode is a fascinating insight into how data can be used to bring about change and make a positive impact on animal welfare, the environment, and the agri-food industry as a whole.

Transcript

0:03

Hello and welcome to another episode of Seedling Sessions. Today I'm speaking with Rich Vecqueray, CEO of Map of Ag, who are a data business with the platform that connects farm data to the agri food industry. Good morning, Rich, how are you? Good morning, Tom. Well, good, thank you. Yeah, so would you mind, just for those that aren't aware of who Map of Ag are, maybe just giving a little bit of introduction to the organization yourself and what you do? Certainly, yeah. If I start off with myself, I'm a vet that sets out in the Lake District doing sort of James Herriot tastic stuff up here and I guess over the years got frustrated with the influence I was having on farm with respect to animal welfare, essentially seeing highly preventable problems. So I sort of tried to evolve then through my career to ways of having more influence, which has sort of to cut a very long story short, brings me to sort of where I'm sat today, really, which is managing Map of Ag. And sort of what we do at Map of Ag is bring together farm data at scale so the agri food industry can connect with their supplying farms. And we do that in the UK, New Zealand and Australia, and then increasingly into Europe. And bringing it back to sort of why I started in terms of that influence is sort of very much like we run with ethos. If you can measure it, you can manage it. So we try and then sort of allow almost consumer pressure and the ability to add value down through to farms, through the supply chain to deliver meaningful change, much more so than when I was a vet sticking my hand up cows backsides on farm. It's interesting to ask you the scale element that is an important part. And it's of course, where technology, particularly at scale, can be really helpful if it's amalgamated correctly. So just to get into a bit more detail on that. So Map of Ag the organization, the platform itself that you work to connect the food industry to farmers is called Pure Farming. Pure Farming. The value within that. So you're collecting or you're integrating data from lots of different data collection across lots of farmers, and then that's being used to help make decisions and reporting and make the right decisions at the agrifood business end. So we're looking at what processors and retailers? Absolutely, yeah. And what does that tend to be used for by the process and retailers? So to use a sort of current example, if you like, sort of a board might make a commitment to be net zero by a certain date and that's sort of a headline that we will increasingly see. So if you're looking to deliver that in terms of scope three emissions from farm, and to do so, you're going to have to sort of influence change more quickly than it probably has been happening over the last ten years on those farms, then if you're going to deliver that, you need to be able to understand what's happening on individual farms in your farming supply chain. But you need to be able to do that at scale, which is really hard to do economically and in a way that engages those farmers because they haven't had that relationship across the farm gate before. So in terms of change, both in what's happening on farm, but in terms of relationship change, then the change is massive. So having a technology platform that takes as much of the pain out of that as possible and delivers trust on both sides of the farm gate is important. And that's what we've tried to deliver through the product development that we've done within the Pure Farming platform. Yeah. One of the major issues you see across a lot of agritech development is this idea of interoperability. And so you've obviously taken on one of these herculean tasks that we know needs solving. My presumption then is that this is often as it's where the larger amount of benefit is driven by retailers and food processors. Does that tend to mean that if a retailer or food processor is working with, for example, 50 farms across the UK, that you would sort of then work with those farms who might have different farm information management systems, etc, etca. And work out how to coordinate all of that data in a way that's kind of easy for the farmers and that is less of a headache, but then provides actual insights for the food processor and retailer. Exactly that. So the processor or retailer would come to us and say, right, we have this problem that we need to solve. We need to know more about our farming supply chain for one of probably six different six different use cases and we would say, okay, and that might be thousands of farms. So that's really tricky. And each of those farms will have different farm management software systems, they will be using those systems in a different manner, they will be engaging in government systems and NGO systems in a different way. And this conversation we would be naive if we didn't raise the fact that a lot of farms don't have farm management software and are operating in quite a traditional way still because agriculture has a huge diversity of what is taking place and how different farmers farm extremely effectively in very different ways. So if we're going to do a whole supply chain, which is the utility that we fulfill, then we need to be extremely agile in our approaches to solving those problems. So we will work with the farm management software systems to bring that data in for the dominant systems within those supply chains, whether it's government systems or NGO systems, we will bring that data in and we structure that and normalize that data. So data point out of one software system. We will try and align that with a data point out system, the data that's being presented to the industry that's been permission by those farmers. So those farmers are retaining control of what that data can be used for and for what purpose. Then we will have normalized that data for those guys that they're connecting through to. And so food processers and retailers kind of being the customers who were kind of receiving these actual insights that have been collated through what sounds like a very complex and difficult data management system. What's the primary use case for this? Is it governance, ESG commitments? I'm sure there's a variety. As I alluded to, there's a number of different use cases. So what sets us out on this journey was back in 2007, we were approached by Sainsbury's. I was doing consultancy work for some of the largest, highest yielding dairy herds in the country. Through that role there, that brought those farmers at that time into contact with Sainsbury's. So Sainsbury's approached myself and my partner, James Husband, as to how they might work more closely with clients that look like our clients at that time, sort of thing, to engage them. And so essentially at that time, sort of what Sainsbury's were interested in and why they were talking to us was health and welfare data. So we set out in animal health and welfare, and then that very quickly evolved then to say, okay, well, we're gathering this data about production, about cow numbers. We can do that in different species. So we went into sheep, beef, lamb, pork, health and welfare. And then because we were gathering that data, it became very easy then to say, okay, well, antimicrobial resistance has become a huge consumer issue. We need to start to act on that, because that's the responsible thing to do for a brand as big as ours and people like Sainsbury's. And so we added in antibiotic monitoring to that data set, and then very quickly moved into production efficiency, because you can deliver on production efficiency, so you're producing more goods for less inputs. Once you've got all those data inputs, then you've got 85%, 90% of the data inputs that you need to do a carbon footprint. And then if you're in that space, people very quickly want to start talking about biodiversity and water quality. So they're the sort of six areas that we now work across. And so the primary sort of unifier of those different six areas is you would call it ESG. So that's the primary use case that people come to us to address. That's absolutely fascinating. A lot of those areas require kind of physical data collection just to think of just a few that we work with. So in terms of earlier stage agritech startups, we work with Smartbell who have an ear tag for livestock, for Animal Health and welfare Chordata have a similar proposition. Then you've got people like DroneAg who are looking more arable crops and collecting up through drone usage, NoFence or someone even like AgriSound who are looking at measuring pollinator count and therefore biodiversity. As an organization that has been working to collect data through Farm information Management systems and direct from the farmers and try and bring that all together. Do you see the kind of potential surge of more data from all of these different types of technologies, whether it be wearables or satellite or drone being something positive in the end? Or do you see it as a challenge? Love to hear your thoughts. I see it as being super positive because if I come back to I'm a vet by training, so you forgive me for sort of bringing it back to sort of livestock examples. But equally, some of those examples you've given, we could take it in a sustainability sort of arable direction, but I'm more comfortable talking about livestock. So if you look at we've tried to sort of push outcome measurement rather than specifying encouraging our supply chain customers to look at the outcomes of what is coming from farms. So leaving farmers free to farm rather than saying you must farm like this. So if they're getting good outcomes, it doesn't matter how they're achieving those outcomes. An example of that would be dairy cow lameness mobility. And so really the only way of looking at outcomes at the moment, or certainly if you dial it back about five years, is to send somebody down that farm drive and for them to score those cows subjectively to say how many are lame. What we've got now with the advent of technology is the use of machine learning across cameras. And there's multiple solutions for this and they can analyze those images and give an objective score of cattle lameness at scale. So we've solved, we're solving, what is probably one of the biggest welfare challenges of the dairy cow using technology in a way that then is a level playing field across all those different farms. So the farmers, we can present that data back to them using those solutions, using our headline, sort of bringing all that data together, benchmarking the guys and they can be presented sort of like for like data points. So it's perceived as much fairer sort of thing and therefore much more likely to influence positive change than what was previously a really important score, but highly subjective between different scorers. So that's a real positive. And any of those examples that you gave using sort of imagery analysis would do the same within the sectors of the examples that you've you gave. Yeah, I think more than anything, to me, listening to this is the ability for you to apply this stuff at scale. I think we can introduce all sorts of exciting technologies onto an individual farm, but I think often we forget that the vast majority of how this entire sector pieces together is obviously through a bit more scale with food processing, manufacturing and retailer. And therefore you do need to come up with a solution of how do we take the data not just from an individual farm enterprise, but from, as you said, thousands of farms, and put that on a fair level pegging of benchmarking. So that's really fascinating to me. Something you mentioned a little bit back, which I'd love to circle back to, is around consumer pressure, which of course is the end of that food chain. What do you mean by that? And it'd be good to hear about and I think it also ties into what you mentioned around outcome measurement rather than input measurement allowing farmers to farm. Because I think at one end you've got consumer pressure and then at the other end you've got farmers trying their absolute best to produce food in a sustainable and profitable way. And it'd be really good to understand how it all ties together for you along that. Yeah. I don't know what the end point of the evolution that we're taking place is, but if you I started telling the story of Map of Ag, I suppose, from 2007, which we had around that time, sort of soon after that, the horsemeat scandal, we had the Arab Spring that may or may not have been associated with a huge spike in global food prices. And also, I suppose the antibiotic resistance I've already alluded to is almost that the food chain had become too complex and too long. And I think probably only good things can happen if you shorten using technology, the distance between the consumer and the farmer. So if you can communicate with someone, then you develop a relationship with someone. If you develop a relationship with someone, you're much more likely to trust them. And if we get sort of the consumer trusting the farmer, and the farmer trusting that they are able to add they're able to work hard but receive a fair return for that hard work, which is all they want, is only good things can happen if we do that. And I think technology is gives us the unique opportunity to evolve evolve to that point, which is it's all sound very grandiose and sort of potentially naive, but essentially what we're trying to do with Pure Farming is sort of bridge right across the supply chain with that view from farm using farm data. Absolutely. I think it would be interesting to touch on. So I think often this idea of data collection on farms being used by food processing retailers can be spun in a negative way and it can be spun around putting more price pressure or more things to do on farmers. It sounds like you've got more positive outlook on that and this idea of labeling used as a positive way to indicate to consumers and then to reward farmers on that, am I right thinking you do have a more positive spin? Because I've been at this a long time now, sort of thing. So I've seen most of those examples that you've alluded to and where it's worked best, where we've supported the delivery of the most change across the farmers, where you've maintained that trust and the communication between, ultimately the retailer as a proxy for the consumer and representative farmers representing their group. And it's been a collaborative venture that they've sort of gone out to. They've agreed the change that they're going to deliver and they've all signed up to that and move forwards in an agreed manner. And generally there's been some sort of kinks and deviations along the way and the rest of it, if you've got that forum and that sort of agreed vision and then generally it's just massively powerful for delivering huge changes that I didn't think would have been possible back in 2007. But to reach a point now, if you told me, oh, this will be happening 15 years later, oh God, no way. But yeah, there's those the supply chains have altered wholesale, wholesale. And that's exactly what's going to have to happen now with a net zero sort of example, an agenda sort of thing, it probably even greater change in the next 15 years of that which has happened over the last 15 years sort of thing. Sometimes talking net zero, I often have a sense that maybe there's a bit too much of a focus on GHG emissions or carbon especially. And we work quite closely with the Global Farm metric. We had them speak at our conference and I'm a big fan of the work they've done there to try and at least create a shared language around this incredibly complex system where every farm is different and we need to be measuring different things. And what do we measure? Would you broadly, do you agree that we shouldn't just be focusing on carbon and GHG emissions when we talk about Net Zero? Yeah, totally. And I guess that's why we work across those six different areas. And if you focus on an outcome, if you had to choose one metric from each of those cases and you pursued that metric to an endpoint, then you would end up with some very perverse outcomes in the other areas. Because to come back to a ruminant example, to take it back to my safe place, you can lower, substantially lower methane emissions by placing antibiotics into the room and essentially sort of thing, antiproid cells and stuff provide in terms of our responsible use sort of agenda, a perverse outcome. Perverse outcome there. Similarly, you can do some things stocking extremely heavily in things which gives you again a perverse animal welfare outcome, but potentially quite a nice sort of regen sort of thing because if you've come totally focused on soil health then actually some of the other things you can start to do some weird things with your animal health and welfare sort of thing. So you need to sort of take a step back and get the appropriate outcomes in each of those areas and try and keep all the balls in the air at once, which is hard, but with data appropriately and appropriately chosen. KPIs you can absolutely do that. And we need to be very careful of sort of this route that we're taking for all the reasons that you've alluded to. Fascinating answer. As you said, you personally have been at this for quite some time and Map of Ag has been around for longer, I'd say, than some of the kind of much earlier stage startups, particularly tech and hardware that we work with. Do you have any good learning lessons or potentially any great case studies of projects you've worked on that you'd want to have it to talk about? I think the key lesson in sort of delivering success at Map of Ag for our customers, which are the guys beyond the farm gate is to before they set out on the project is a have a very clear idea of what the end point is and how are you going to add value from this project. What is the marketing message that you're going to deliver to the consumer? Essentially? So will you be able to shout about this? And you may not want to and that's fine, but then don't sort of finish the project and think, oh, I can't shout about this for these reasons because I did away. So start with the end in sight and then really carefully think about what's in it for the farmers. Why would they do that? Why would they take the time? Because even we provide a solution that takes a lot of the friction out of data sharing for the farmer. And that's our whole ethos is to deliver trust and minimize the friction for the farmer sharing data. But equally, it takes some time and it's the farmer's data about what they're doing. They're opening their shop window, not to the world, but to that partner that's buying their produce, usually, or supplying them. And you've got those guys beyond the farm gate that have engaged us really need to think, how am I going to incentivize this? And that's the bit that needs some very careful thought. Sorry, rich obviously Map of AG is a well established AG tech business in the UK now and obviously I'm sure you'd be keen to hear from other UK based food processors and retailers, but it'd be great to hear a little bit about what your plans for growth and expansion are in the organization. Yeah, sure. So in the next twelve months, our mission really is to consolidate our position in Australia, where we have a foothold and I perceive the Australian market isn't as advanced in terms of the consumer pressure that we see in the UK in terms of animal welfare and the sustainability agenda, but is catching up fast. So the processors there, the retailers there want support for stuff. That may be the journey that the retailers and processors here started on five years ago, but their timeline is sort of, okay, we need to do this in a year, and then the following year we need to do this. It's a shorter timeline. So the world is sort of coming together in terms of its overall sustainability agenda that we support, in terms of the farm aspects of that. So we need consolidation in Australia. There's some fair bit more work to do in New Zealand in terms of the connection and then doing sort of more of the same, but better in the UK. And then a number of our clients are processes that are global in outlook, so they've got farm supplying them throughout the UK, but also through Europe, through Germany, through Poland, through scandinavia and the baltic States. So we need to meet their needs by doing what we've done in the UK across Europe, and then also some of those processes have North American suppliers, so we'll be looking to roll that out into North America with those customers as partners into those. So to that end, I'm going to the States three times this year to start scoping that work and to building that partner network over there to support the delivery of that which will probably, if the timeline goes according to how we would like to a sort of scaled rollout in North America, probably in two years from an 18 month sort of time frame to start out on that. Exciting and ambitious expansion plans. But it was interesting to what's the competitive set look like out there for you, because obviously it's quite a niche offering that you've developed and I imagine even competitors in that space won't be offering the exact same offering because it's quite complex. Absolutely. So that would be exactly how I would answer the question is that there's not another business that you would take off the peg that looks exactly like Map of Ag in terms of the competitive landscape. We try and avoid sort of having sharp elbows to do what we do and deliver on our vision. We kind of have to be mates with everybody, and our company culture reflects that. So we have to maintain humility across the business and work very carefully to preserve our relationships with everybody because our job is to connect, our strap line is "connecting agriculture" and to do that we can't be upsetting people left, right and center. So we try not to sort of compete where we can, we just connect where we tender for work and we've lost work that's up to date or where we've won work and somebody else has lost out. It would be with the scaled supply chain or farm consultancies, the information businesses that working with the farmers. And actually our long term aim is to power up those guys because we don't want to be delivering consultancy services ourselves. We simply want to be the technology platform that joins all the dots together and provides data that those guys are the experts. They have the farm relationships, they have supply chain relationships, and we power those guys up. So it's a situation that I don't massively envisage repeating many times over the next five years. I think we're having very fruitful conversations with most of those players now that we have been competing with that we want to take a step back and supply them. So that would be our vision. It feels like a very smart strategy. So speaking of connecting people, obviously people listening to this, who would be the ideal organizations to get in touch and have a conversation about how you might work together? Yeah, if you look at the membership of Agri-EPI from the retailers and process side of things, we're working with many of those organizations already. There's more that we're not, that we would love to work with. So that goes without saying that we want to be the Farm data platform and to do that we need to work with everybody if we can and the door is open. So in terms of people we're always keen to hear from is the guys entering that software space and the software providers, the data providers, the innovators on farm, solving problems for farmers. Because if they can do that at scale, then it's just great for everybody through the supply chain that A). They can solve problems for farmers, they can help that farmer decision making, and we can potentially take one of the problems they might want to sort of eventually be on their roadmap. We can solve that problem for them by connecting them through further up the supply chain so they can really add to their offer by solving a problem for the farmer because there's some data they don't have to tell to a consultant or type into a web interface because it's already there. And it's better than that data would be if they typed it in. So we're always keen to talk to more of those guys and then similarly the consultancies as well because we might be able to then sort of power up their offer. Okay. And as always, people can always contact us at Agri-EPI and, and we can make connections. But if anyone wants to get in touch with you directly, what's the best way to go about that? Yeah, they just go to the website. And so there's currently two websites, so Mapof.Ag, and you can contact us through that page. And then also, if you're interested more in what we do, check out the PureFarming.com website, which is all about the platform, and there's extensive developer documentation on that platform for people that would be interested in connecting. Happiness. Thank you so much for taking the time to chat to me. It's been really interesting. Well, thank you very much for having me. I really appreciate it. Not in the slightest. I think obviously a lot of these episodes focus on quite niche technologies for single use cases, and a lot of it tends to be on farm technologies, which is incredibly exciting. What's been really nice talking to you is about trying to understand how that collection of data, particularly on farm. How that connects further up the food chain