Effective on-farm research starts with a clear question and a shared understanding of the system. By involving farmers and stakeholders early, we can build explanatory frameworks that connect the local farming context with existing knowledge, helping to clarify what matters, what’s known, what to measure and what to test.

By sharing relevant farm data, making meaningful measurements, and combining these with soil, weather, and satellite-derived datasets, we can enable benchmarking and analytics that help farmers compare performance, build shared insight, and develop hypotheses about what works on-farm that can then be tested in experiments.

To understand if something works, we need fair comparisons — ideally replicated within and across farms. Field variability makes this challenging, but with good design and the  right tools, robust trials are possible. ARC tools support co-ordinated experiments using satellite imagery to place and monitor trials. Robust statistics can be applied to yield map data.

Real progress depends on listening. Capturing farmers’ experiences, feedback, and ideas is essential — not just for sharing results, but for shaping the direction of research and innovation. We help bring together tools like FarmPEP and support facilitation through groups like BOFIN to enable meaningful exchange and distil shared knowledge nuggets.