Farm Data Is No Longer a Blind Spot
Why the least visible part of the supply chain is becoming the most critical driver of corporate sustainability performance
In most agri-food supply chains, more than 70% of emissions sit at farm level. Yet for many companies, the farm is still the least visible part of the system.
Most Scope 3 data is still based on averages, emissions factors, and lifecycle databases. It is the best available approach in many cases, but it means the biggest part of the footprint is also the least specific.
Two farms with very different practices can end up looking the same in reporting. That makes it harder to see where progress is happening, or where to focus effort.
As expectations increase from retailers, investors, and SBTi, there is a shift from simply having numbers to being able to stand over them. That is where clearer, farm-level data starts to matter.
Why Farm Data Is Becoming a Corporate Performance Asset
There is a stat I keep coming back to in conversations with food companies, and it tends to land the same way every time. In most agri-food supply chains, more than 70% of emissions sit at farm level. Not in factories. Not in transport. Not in packaging. On farms.
And yet, if you look at how most companies actually track and manage data across their supply chain, the farm is still the least visible part of it. That gap is where a lot of the current frustration is coming from.
If you are working in sustainability or procurement right now, you can probably feel it. There is pressure coming from retailers, from SBTi, from internal targets. Everyone wants clearer numbers, faster progress, and something they can stand over externally. But when you trace those numbers back to source, especially for Scope 3, things start to get a bit vague.
Most Scope 3 Category 1 data is still based on a mix of averages, emissions factors, and lifecycle databases. It is the best available approach in a lot of cases. But it does create a strange situation where the biggest part of your footprint is also the least specific. You end up with numbers that are technically correct, but not particularly reflective of what is actually happening across your supply base.
The Problem With Averages
Take two dairy farms supplying into the same processor. One has invested in feed changes, better fertiliser use, maybe some work around soil and grassland management. The other is running in a more traditional way. Those two farms are not the same from an emissions point of view. But if you are using regional averages, they basically show up as the same thing in your reporting.
So the farmer who has made changes does not really see any benefit, and the one who has not is not under any pressure to do so. From a company perspective, you also lose the ability to see where improvement is actually happening.
It is a bit like trying to manage business performance using industry financial averages instead of your own accounting numbers. You get a general sense of direction, but not enough to act on properly. A lot of the conversation tends to focus on better tools, better models, more automation. That all helps, but it does not really solve the underlying issue if the input data stays the same.
The Incentive and Engagement Challenge
There is also an incentive piece that does not get talked about enough. For a lot of farmers, sustainability data collection still feels like extra work with no obvious return. There might be a survey, or an audit, or a platform to log into, but it is not always clear what they get out of it, leading to inconsistent engagement, which then feeds back into the quality of the data.
It is easy to frame that as a participation problem, but it is probably more accurate to say it is a design problem. Most engagement approaches still look like workshops, webinars, toolkits. They are well intentioned, but they sit slightly outside the day-to-day reality of running a farm. Then you add in things like long questionnaires or systems that assume good connectivity, and it just becomes another layer of friction.
What seems to work better is when the process is simple and actually useful to the farmer. If someone is taking the time to share data, there needs to be something coming back. Even small things like insight into input use, yield trends, or cost patterns can make a difference. Once that exchange feels more balanced, participation tends to improve quite quickly. And when participation improves, the data starts to look very different.
Some approaches are starting to move in this direction. VSAg is one example, using a video-guided way for farmers to capture what is actually happening on the ground, rather than relying on surveys or generic models. Because it fits more naturally into day-to-day workflows, it would improve engagement, and the data that comes out is more consistent and traceable back to individual farms. That makes it more useful, not just for reporting, but for understanding what is really driving emissions across a supply base.
From Reporting to Real Decision-Making
At that point, the question becomes less about collecting data and more about what kind of data is actually useful. Perfect data is probably not realistic in agriculture. There are too many variables. Weather alone makes sure of that. But you can get to a point where the data is good enough to make decisions.
In practice, that usually comes down to whether it is traceable, consistent, and usable. Can you link it back to a specific farm and time period. Is it being collected in a similar way across your supply base. And does it tell you something you can act on. If those pieces are in place, the role of data starts to change. It stops being something you produce for a report and becomes something you can actually use to guide decisions.
This is where it starts to connect back to SBTi in a more practical way. There is a shift happening from just having numbers to being able to stand over them. Modelled data is still useful, but there is more scrutiny now, especially from retailers and investors. If most of your footprint is based on estimates, that can become a weak point.
When you start to get a clearer view at farm level, the conversation changes a bit. Instead of just asking what your footprint is, you can start asking where the biggest opportunities are, which suppliers are already performing well, and where support or investment might have the most impact. That leads to more targeted approaches. Not everything needs to be applied across the whole supply base in the same way.
The Shift That’s Already Happening
One thing that becomes obvious quite quickly is how different farms actually are. Some can make changes relatively quickly if the right support is there. Others are more constrained, whether that is down to land type, scale, or access to capital. Without data, those differences are hard to see. With data, you can start to respond to them in a more practical way.
There is also a wider business angle to this that is starting to come through. The quality of Scope 3 data is beginning to show up in investor conversations and due diligence. It plays into how credible sustainability claims are, and in some cases how easy it is to access certain types of finance. It is not just a reporting line anymore.
There is also something to be said for the relationship with suppliers. Farmers who feel like they are part of the process, and that their efforts are being recognised, are more likely to stay engaged. Given how much volatility there is in supply chains at the moment, that kind of stability is not insignificant.
If you take a step back, it feels like the direction of travel is pretty clear. We are moving away from a system where estimates were acceptable and reporting was the main goal, towards one where the quality of the data itself matters a lot more, and where it is expected to support actual decision making.
Retailers, regulators, and investors are all pushing in that direction in slightly different ways. The question is how far companies go in response. Some will continue to build on what they already have, improving models and filling gaps where they can. Others will start to focus more on what is happening at farm level and how to make that part of the system more visible and more useful. That is a bigger shift, and it takes more effort, but it also changes what is possible.
The Takeaway
The farm gate has traditionally been seen as the edge of the business. In reality, it is where a lot of the risk and opportunity sits. It just has not been very visible. That is starting to change. And the companies that figure out how to make that part of the supply chain clearer and more usable are probably going to be in a much stronger position over the next few years.
Because in the end, most of the real change does not happen in reports or dashboards.
It happens on farms.
