Probabilistic scenario planning in agriculture: balancing risks through data-driven forecasting

Many decisions in the agricultural sector are made under uncertainty. Farmers choose crops and varieties without knowing how much it will rain, or how farmgate prices will develop. Food processors and retailers buy perishable farm produce without knowing if demand will go up or down.

Such uncertainty about the future creates economic risk: the decisions made by farmers and other food system stakeholders today can prove suboptimal in the future. Many stakeholders mitigate such risks by choosing a heuristic ‘best-bet’ strategy: for example, farmers may plant a mix of traditional drought-tolerant varieties and highyielding hybrids. Applying the same best-bet strategy every year is a reasonable way to deal with risk because many uncertainties affecting agriculture cannot be predicted
accurately. For many phenomena, however, it is possible to estimate their probability of occurring. This enables more flexible, anticipatory decision-making that considers how the future is likely to differ from the present or past situation.

Steinke, Jonathan; Ortiz-Crespo, Berta.