Lucie Douma, a 2022 Nuffield Scholar, recently completed her final research report into data interoperability. The report was informed by extensive global travel and visits to a range of agricultural operations.
In our latest Ideas That Grow podcast, Douma chats to Farmers Weekly managing editor Bryan Gibson about the need for improvements to the way we collect, manage, and use information on farm as part of the decision-making process. She also delves into the challenges of data sharing and a solution potentially accessible to smaller farming operations.
Listen to the podcast here, or read the transcript below.
Kia Ora, you’ve joined the Ideas That Grow podcast, brought to you by Rural Leaders. In this series, we’ll be drawing on insights from innovative rural leaders to help plant ideas that grow so our regions can flourish. Ideas that Grow is presented in association with Farmers Weekly.
Bryan Gibson: Welcome to the Ideas that Grow podcast. I’m Bryan Gibson, Managing Editor of Farmers Weekly. This week we are talking to Lucie Douma. G’day, how’s it going?
Lucie Douma: Hi, Bryan. I’m good, thank you. How are you?
BG: Good. Now, we’re together today to talk about your Nuffield Scholarship and your report. You’ve covered something that is a real big issue in New Zealand agriculture, I think, and that’s how we best utilise farm data. What got you into this topic?
Data interoperability and why it’s useful.
LD: That’s a very good question. So there’s a lot of people actually working on data interoperability challenges at the moment. I mean, they don’t call it a wicked problem for nothing. I had also been involved in that in my time at the Ministry of Primary Industries, where I was looking after the data interoperability and governance work stream as part of the Agritech Industry Transformation Plan.
That was about four years ago and we’re still at the point that we’re having conversations about how to tackle this problem, because it’s a really difficult one.
So that’s what made me want to apply for a Nuffield Scholarship, that I could unpack the problem a bit more and see what was happening internationally and if we could learn anything from that and move from the talking to the action.
BG: Now, just to explain, data interoperability is lots of farm data is collected by lots of different people, but at the moment, lots of those data sets don’t talk to one another, so you’re not necessarily getting the best out of them. Is that kind of how it works?
LD: Yes, that’s correct. That’s how I’ve been looking at it. So you’re correct that there is a lot of different data points and data collected from different organisations. Farmers can access that data, but it’s all siloed. It is independent systems and then farmers and growers are required to actually do their own calculations and then find out what some of those relationships are between the different data points.
So what we want to achieve from data interoperability is to have data sets, and platforms, and systems that speak across each other so that you can see your farm or operation as one holistic approach. One holistic organisation.
The challenges to achieving shared data.
BG: What are the main stumbling blocks? Is it sovereignty? People like to think that the data is worth something and so they won’t share? Or are there other, more structural or technological issues?
LD: Yes, it’s actually not a technological issue. So technically, we’re at the point that we can do it. A lot of it comes down to the relationships. There’s also commercial challenges that we have to deal with because it’s commercially sensitive data, some of it. The sovereignty side is also a really big aspect.
It really comes to the relationships between companies, relationships between people and who has access to it, because data is seen as an asset and something that people own, and I think we need to get away from that. Like, data is something we can use. But it’s the information that you get out of it that’s the benefit of it, not the data itself.
BG: Yeah, I mean, it’s all very well thinking that data is worth something, but it’s only worth something to a farmer if it turns itself into lower costs or greater value or something like that.
LD: Yeah, exactly. You can make better decisions on farm, so it’s the information that you want.
Nuffield global travel, the engine for good research.
BG: Now, Nuffield Scholars do a bit of touring around the world and you did the same. What did you find out there in terms of other nations and their relationship to data sharing in the farming sector?
LD: I spent about four months overseas last year. I predominantly spent the time with farmers and growers and farming organisations, as well as support organisations overseas. I found out some really interesting aspects around how people were managing data. Then what we can learn for us here in New Zealand.
I also found what doesn’t work. I’ll tell you a story. I was over in Norway and I was looking at some of the aquaculture there for salmon. That’s quite a new industry. It’s very advanced and you need a lot of capital to start. So, I went over there thinking, oh well, they’ll have data interoperability sorted, so I’m sure we can learn a lot from them.
While I was talking to the people there, they actually had the same problem as almost everyone else, only at a company level. So every department had invested in their own system to look at fish housing and then there was like, fish production and things like that, but again, you had none of those systems talking to each other.
So that was really interesting that it actually didn’t matter what size the companies were, it was also that they still had the challenge of data interoperability, because, again, it comes back to the relationships and the way that that business is structured.
How the Australians are doing it.
So where I learned the most, and where my plan and way forward of looking at this differently came from, was in Australia. So I learned a lot from the Australians because they have spent a lot of time with data in the mining sector. The mining sector gets it and has done a good job of finding out that everything has to be very precise.
There’s a lot of investment when you’re looking for new mine and new minerals. They have worked out what data they want and how to collect that. Then the best way to present that so it’s consolidated. What they have done is they’ve got a data manager. The data manager actually works with the mine to find out what it is that they need. They have big data teams. Now, that’s not something you can apply directly to farming, but it is something we can learn from.
Data managers may be an answer.
BG: You mentioned in your report, perhaps having a data manager as part of a wider farming business. How would that work do you think?
LD: Yes. That’s the way that I’ve looked at it. How could we do it differently, in that we aren’t asking farmers to be finance experts. They have an accountant for that. So why are we going around asking them to be the experts in their data with the technical expertise to work out what to do with these systems? They should have a data manager.
I went to Brisbane and spoke to Smithfield Cattle with cattle feedlots. They have their head office in Brisbane, then they have two feed blocks that are about 4 hours apart in two different directions. Those two feed lots are about 20,000 cattle per feedlot, 40,000 total.
The feedlots are managed and formed very differently. One of them is very organic, so they have quite a different structure to the one that’s very symmetrical. And so you can’t apply the same sorts of applications and way that you manage those feed lots.
They hired a data manager, and that data manager was responsible for working with the feedlot managers to find out what was actually going on in the feedlot. What their strategy was and then what information they need to make the best decisions on the feedlot to maximise production.
So, with the data manager, it was working really well. He knew exactly how the feedlots operated. He was spending a lot of time with the managers, and from a head office perspective, they were getting all of the information they needed from the two feedlots.
On the ground asking the people that know.
I also went out to the feedlot and asked the feedlot managers, hey, is this working for you? Because from the Brisbane perspective, head office is great. But does it work for you? The feedlot manager said that it was brilliant because they could get real time information and make decisions on the spot.
If something wasn’t working, they could call up Rowan, who’s the data manager, and actually say, this isn’t working, and they’ll get a response immediately rather than going through call centres and raising tickets and all those sorts of things. From that perspective, it worked really well.
A solution for smaller operations.
Now, that’s a large business. Not every farm here in New Zealand could do that – hire their own data manager. So that’s why I was looking at the accounting model in that we haven’t asked farmers to be finance experts. They have an accountant. That accountant looks after five or six different farms.
So why couldn’t we have that with the data space? That enables someone who can help with collecting information to then provide something useful back to farmers and growers for better decisions making.
They can also work with farmers to find out, well, this is your farm strategy, which the farmer or grower may have worked with their rural advisor on, then match that to a data strategy. Then do a data audit to find out what information and data is being collected now and what they may also need.
That information and that advice is independent because at the moment there are a lot of apps and tools that farmers and growers can use, but people are just selling it to them. There’s no reviewed independent advice on that.
I think the data manager role is a skill set that can be applied and I think would be really good for farmers and growers in the current time we are in – the information age. That’s how I see that working.
Getting the data farmers and growers need for the future.
BG: I mean, that sounds great. Apart from the fact you’re removing a large chunk of work that many farmers or many people in general are not wired to do, you get the benefits of having that data well utilised, don’t you?
LD: Yes, and someone independent that can really help you work out what you’re trying to achieve on the farm. Someone who can provide you with that advice, and the strategy, and the data tools you may need to actually enable that.
BG: And this would also feed into reporting in terms of, say, emission schemes and freshwater plans into your council, that sort of thing?
LD: Absolutely. Because what I envision is that with the data manager, they would be holding that data digitally in a data lake. I mean, this gets more into the technical space, but with that large data lake, you can then get permission and share to different people that may want that, whether it’s government, local government, central government, or your customers.
A food system hungry for data – as a requirement.
Also part of the reason I did this, is that with our customers and consumers, they’re hungry for data and information. They want more of this. They want to know how our farms operate. So we need to be in a position that we can share those stories and we can explain that to them. For that you need data.
BG: I think that is a message that is beginning to spread more widely amongst the primary industries here. Just how important it is to be transparent about the supply chain of New Zealand food products. That’s really something that’s only going to get more important, isn’t it?
LD: Absolutely. Last month, Nestle, which is one of Fonterra’s largest customers, released their roadmap for how they want to get to net zero. They want to achieve net zero by 2050 and they want to halve their emissions by 2030. Now, that’s only seven years away. That’s not far. And of their emissions profile, about 30% of their total emissions comes from the sourcing of dairy and livestock.
They’re really pushing for this, which means we need to then have the data to back up those claims that we’re making on farm and the emissions that we have so that Nestle can report it to their customers.
There’s going to be more demands for this across all of our customers because we have premium products. For us to maintain that premium market access, we have got to be one of these first movers in reporting our emissions and actually giving it to these companies that are wanting that.
BG: So having access to all this data can not only prove where we are now, but it can make sure we have the best strategy going forward to get to where we want to go in the future.
Data and trade.
LD: That would be right. It’s also around our free trade agreements because with us having that market access, because we’re an export country, right – most of our products and food is sent offshore.
In March, I was at the Rural Leaders Agribusiness Summit and we had Vangelis Vitalis speaking to us. He is with the Ministry of Foreign Affairs and Trade and he’s the chief negotiator on the EU Free Trade Agreement. Now, he was saying that when he was negotiating that agreement, they asked questions back of that agreement, and of the 20 questions, around 15 of them were around climate change and environmental aspects, and GHG emissions.
So if that’s the requirement, to even get into these markets, we need to be able to meet them and we need to have the data to back that up. I think just going back to where the data sits and where it belongs, I think farmers are best positioned to actually collect that and pull that together. So that’s why I was looking at this from a farmer-grower perspective – having them in the centre.
BG: So what are the next steps for you? Have you got plans to move on from what you’ve written in your report?
Turning interoperability talk into action.
LD: Yes. The next step, like I said in the beginning, I want to move to action. The report is still in writing, so we need to action some of this. I’m in the process of working through what some of the pilot projects could be, because we need to now prove if this can work or not, because it is looking at it differently. And, look, don’t get me wrong, once we go out there and we try some of this, there will definitely be challenges and things that we can work on.
I don’t think we should be afraid to fail. At least not fail, but the fast fails that you can learn from. So the next step will be piloting some of this out on farm with a group of farmers. Yeah, you’ll hear about that in the future. There’s a few things in the making at the moment.
BG: That sounds amazing. Have you always been a data geek or is it something you’ve embraced recently?
LD: This is more of a recent thing. I actually have no data background. I’m more in that system strategic base, so I don’t have any technical background. But it was a bit of a learning curve with this project where I had to work out exactly how this can happen, at least to a basic level, and then just work through the strategy and the structure of making this work at a relationship and system space. So no, I’m not a data expert! It’s been very interesting though.
BG: Well, we wish you all the best with it and no doubt we’ll check in in a while and see how you’re going.
LD: Thanks, Bryan. I look forward to reporting back on this in the future.
