Presenting uncertainty and variability to the decision maker: A computer program that uses Monte Carlo simulations to improve the management of the dry period

Each piece of advice has a certain degree of uncertainty attached to it which can be hard to convey to dairy farmers. The aim of the present work was to facilitate good communication between advisor and client through using a decision system. Software was designed that estimates the expected financial return of specified interventions as probabilities as opposed to point estimates when aiming to reduce mastitis following the dry period. The program was built in MS Excel. The user is asked to enter information on herd milk recordings, mastitis cost data, as well as to choose dry period interventions expected to reduce mastitis prevalence after calving. Each intervention has a distribution associated with its expected effect. Using a Monte Carlo method, a model is run internally for a number of iterations chosen by the user, typically several hundred. The model incorporates recent research findings as well as estimates from the literature on cow and herd level predictors of mastitis. The prevalence of mastitis in the first month of lactation and the associated costs are simulated both with and without interventions. The user is then presented with probabilities for different levels of mastitis and associated costs in both scenarios and the probability that the intervention will be cost-effective. The handling of uncertainty is fundamental in communication between advisors and farmers and this type of probabilistic tool has the potential to be more realistic because decision makers are better informed by considering inevitable uncertainties that are inherent to any intervention.