Figures on global data availability and growth are staggering. Data are expected to grow by an astounding factor of 300 between 2005 and 2020, and are predicted to reach 40 trillion bytes by 2020. This creates significant opportunities for data-based decision-making in industries such as agriculture.

Indeed, ongoing developments in precision agriculture and web-based apps can help the farmer to greatly enhance their efficiency, productivity and sustainability, and to prepare themselves for potentially catastrophic climatic events in real time.

On the other hand, farmers have traditionally relied on a more conventional approach for monitoring and improving their performance, namely, benchmarking. In a nutshell, benchmarking is about comparing one’s performance to that of their peers in terms of one or more performance indicators, typically expressed as ratios – i.e. output over input.

For instance, a dairy farmer may want to know how far their milk production per cow is from the top 10% of farms, or whether farms with a different management strategy than theirs (e.g. pasture-based farm vs. all-year housed system) could deliver higher milk yields. Farm benchmarking reports are standard practice in agricultural extension and consultancy.

However, these reports can be overly simplistic, because partial performance ratios cannot capture the multifaceted nature of agricultural sustainability, encompassing environmental (e.g. carbon footprints), social (e.g. labour use) and other indicators (e.g. animal health and welfare), in addition to economic and technical ones.