If used correctly, it can provide better margins, increase market shares, and many other positive results. At a more tactical level, it can help reduce the costs associated with meeting the customer demand and make the supply chain more efficient. For instance, it can reduce the ratio of unplanned inventory to the total inventory. As a result, companies are interested in making the forecast as accurate as possible.

However, forecast being important does not make the job of forecasting easy. While many techniques exist to calculate forecasts, it is important to understand whether the data at hand is forecastable and to what degree. In this webinar, we will explore various ways to evaluate the forecastability of a data set.