Case Study: SEGES deepens agricultural insight with IBM Watson Analytics

Nurturing Danish agriculture with unprecedented insight into farming processes

SEGES, Denmark’s leading agricultural advisory body, needed a better way to understand the complex relationships across crop, livestock, climate, environment, and financial data so it could give farmers more profitable, 360-degree advice. Working with IBM and IBM Watson Analytics, SEGES sought to uncover patterns in farming processes that its existing tools could not reveal.

IBM implemented Watson Analytics to help SEGES quickly explore large datasets, ask natural-language questions, and create visualizations that made insights easier to share. The solution uncovered previously unnoticed correlations, such as the link between higher temperatures and poorer milk quality, helping SEGES improve guidance to dairy farmers, spark new research ideas, and gain faster, deeper insight into agricultural trends.

SEGES

Peter Enevoldsen

Head of IT