Forecasting & Replenishment

Inventory Management Systems – Where the Past Definitely Drives the Future

Sounds counter-intuitive, but history is about the future. We often study the past to learn about our present and how we can achieve the future we want. This is especially true in the case of inventory management. What has happened in the past directly affects what we need for the future.

With inventory management systems, all too often very little attention is paid to the importance of having accurate data. When your historical usage information isn’t accurate, your future forecast won’t be good either.

How can you be sure your historical usage data is as accurate as possible? First of all, let’s start with defining what we mean by usage data. Usage data is a special history maintained for forecasting purposes that is derived from actual sales –but it is adjusted based on “when and where” the customer actually wanted the product versus “when and from which warehouse” it was actually delivered. Historical usage accurately reflects the date the customer wanted the product, instead of when you shipped it, as well as where the product should have been shipped from, rather than the location from which the product was actually shipped. It is a fine, but critical, distinction.

Many companies are not aware of, or disregard, this subtle distinction, and instead put many hours into assigning formulas to usage data that does not accurately reflect the actual customer needs. The end result is still the same — they never get the forecast accuracy that they desire. An inventory management system with a best-fit formula selection process can only perform well when it works from accurate and consistent historical usage data.

So how do you handle situations such as seasonal or sporadic items or a one-time sale or new items with no history when it comes to your historical usage data?

Let’s look at the last situation – New Items with No History.

There are several separate actions that are appropriate in this case, but they should not be combined on the same item.

• If the item is somehow related to another item you might choose to clone some of the history from the related item.
• You could freeze the daily forecast with an expire-date in order to get the item started, and then let it collect its own history.
• You can adjust the forecast for a period or two in the future.
• Without the above actions the item will initially be sporadic since there is not enough history to create a forecast. You might consider setting up a Sporadic Rule for new items, causing the system to initially calculate a Target Stock for the item. Once there is enough history to calculate a forecast, a good demand planning system will then select the best formula to calculate a valid forecast going forward.

By putting in place an inventory management system that helps ensure historical usage data is accurate and consistent, companies can optimize their purchasing in order to effectively manage their largest and most costly asset inventory!

To find more about Lanham’s Demand Planning solution, visit our product page, or contact a Lanham Reselling Partner or Lanham Associates.  And — be sure to register for the 2018 Forecasting & Replenishment Forum, May 8-10 in Scottsdale, AZ.