How can you ensure the reliability of assumptions made in forecasting?

Gathering historical data is essential in ensuring the reliability of assumptions made in forecasting because it provides a factual basis for predictions. By analyzing past trends and patterns, one can identify key factors that have influenced outcomes in the past, allowing for a more informed projection of future events. Historical data helps validate assumptions by offering concrete evidence of what has happened under similar circumstances, making forecasts more robust and trustworthy.

Utilizing historical data also facilitates the identification of anomalies and seasonality, which can significantly impact forecasts. By incorporating these insights, forecasters can create models that are better aligned with real-world dynamics, ultimately increasing the accuracy of the forecasts.

While consulting with team members can play a valuable role in gathering insights and perspectives, it is not as objective as relying on concrete data. Similarly, depending solely on management decisions or using subjective opinions might lead to biased outcomes that don't reflect actual performance trends. Therefore, historical data stands out as a fundamental component in building reliable forecasts grounded in objective evidence.