Most computer systems forecast future demand of products based on past usage history.  These systems assume that what you sold or used in the past is a good indication of what you will sell or use in the future.  But this isn’t always true.  For example:


  • Products may increase or decrease in popularity over time
  • Customers may ask you to stock products that you have never sold in the past
  • You may introduce new products into the marketplace
  • Promotions, the weather or special events may temporarily affect sales of specific items


We need to supplement past usage history with “collaborative” information.  Collaborative information is comprised of predictions from salespeople, customers, management or other sources of how demand for products in the future will be different from what was sold or used in the past.  Over the next several months we will examine how to effectively incorporate collaborative information into your forecasting process.


The first step in this process is to accurately collect collaborative forecast information.  As you collect this data be sure to note:


  • The source of the information. For example, the customer’s or salesperson’s name.
  • The quantity of the item the source predicts will be sold or purchased in a specific upcoming month or week
  • The reason why demand will be different from what was sold or used in the past. For example, the customer has a new contract or you are planning a price promotion.


Note, we are asking only what will be sold or used in the future, not the quantity that should be stocked.  Later on, it will be easy to compare these predictions (what will be sold or used in the future) against the actual sales or consumption and to monitor the accuracy of the source’s predictions.  If actual sales fall short of the source’s forecast, we can immediately be prompted to investigate the reason behind the discrepancy.  If we are only told to stock a certain number of pieces of a product for a certain customer (e.g., ABC wants us to keep 100 pieces in to at all times, we would have to determine how long we should stock the product without significant sales or usage.  How often have you noticed a large dust-covered quantity of a product stocked for a specific customer in your warehouse and wondered why it has been there for so many months?


Basing forecasts of future demand solely on past usage history is like trying to drive down a highway after someone has sprayed paint all over your windshield.  You will have a difficult time maneuvering your car if all you can do is look through your mirrors.  Collaborative information can provide useful information for effectively managing your inventory.  But, it must good data.


Next month we will discuss how to ensure that the collaborative information you collect is as accurate as possible.