Big Data

Alternative Approaches For Forecasting New, Low Volume, Or Highly Seasonal Items

Watch Now Date Added: Mar 2009
Format: Webcast

Product portfolios will always evolve to meet the demands of customers, but in difficult economic times the decision to add or eliminate products has even more risk. This webcast describes alternative approaches to three particularly troublesome forecasting situations: new products, low volume products, and highly season products. For new products (with little or no history), the use of structured analogies can help automate the process while exposing management biases that lead to poor product release decisions. For extremely low volume products, simply pruning the item from your offerings can eliminate the forecasting problem and have financial benefits. For highly seasonal items (sold only during certain parts of the year), the method of time compression lets you apply traditional forecasting techniques to transformed historical data.