The paper deals with clarifying the role of contextual information in demand forecasting. Both judgemental and statistical forecasting methods are often needed to provide accurate forecasts. However, in practice it is often difficult to tell when judgemental intervention is needed and when it is not. This paper presents a case example about judgemental forecasting, in which the forecaster has different pieces of information available for the basis of a forecast. The paper provides some guidelines on how to evaluate the value of contextual information with probability calculations. The calculations show that in some situations, it is impossible to improve forecast accuracy, even though the contextual information is seemingly valuable. With probability calculations, it is possible to give more objective and specific rules on when contextual information is useful in forecasting and when it is not. This can help in selecting proper forecasting methods, and setting more realistic accuracy targets.