What is SALSA?
Demand forecasting can be difficult to nail down for many inventory management systems. This is because most systems use shipment or invoice data to create demand forecasts. While there may be good reasons for this, it doesn’t give buyers an accurate picture of true demand.
Wholesalers want and need to see true demand. Most wholesalers have excellent Order Entry data already. Therefore, Service and Lost Sales Analysis (SALSA) was developed to enable HIMPACT to use order entry data in demand forecasting, which makes it more relevant.
How Does SALSA Work in HIMPACT?
SALSA Core Features:
- automates forecasting.
- prevents overstatement during extended outages.
- provides visibility into realistic customer demand across multiple locations and periods.
SALSA enables buyers to use order entry demand data for forecasting. However, using this data creates a higher chance that demand will be overstated in the ship and cancel environment during extended periods of out-of-stock. SALSA is designed to eliminate this weakness, resulting in highly accurate forecasts.
The “secret” behind this capability is that SALSA classifies lost sales as either REPEATED orders or NEW orders. Seen another way, the forecast for an item should remain the same before and after an out-of-stock period. SALSA helps the forecast stay consistent rather than increase as a result of repeated unfulfilled orders.
Here are a few common scenarios where SALSA helps wholesalers.
Ship and Back Order
More common in hardgoods, in this context, a customer will order a product from the wholesaler once. The customer doesn’t need to reorder a product that hasn’t been delivered. The customer also knows that their order is backordered, (via a B2B portal) and when the product arrives with the wholesaler, it is shipped out. A key challenge with this approach is knowing when to consider the Back Order to be a Lost Sale. Even in a near monopoly situation, eventually, snow and ice season ends and so does the need for ice melt. SALSA helps buyers easily make this decision.
Ship and Cancel
While HIMPACT uses order entry data for ship and cancel situations, there are some alternative methods. Some systems can feed the forecasting engine invoice data, i.e., only what was successfully shipped and invoiced. However, this approach understates demand significantly if you don’t have a mechanism to deal with a period of extended out of stocks.
In our legacy E3 solutions, we simulated lost sales based on days out of stock. At a high level, if you were out of 3 days and the daily forecast was 5, we would simulate Lost Sales of 15. This prevented the forecast from diving. It also prevented the system from detecting any increase in demand during such periods. This is how we manage forecasts for our retail customers in HIMPACT today, though the underlying functions are significantly improved from the E3 days.
SALSA and Long Term Outs
Even before COVID’s supply disruptions, we have been working on how to make SALSA work during significantly longer periods of out-of-stock, such as six or more weeks. A new element of SALSA is that HIMPACT can now self-detect and flag items as Long Term Outs and it will recommend a Pipeline fill.
For those unfamiliar with what a Pipeline fill refers to, imagine a new item is introduced or a season is starting. Every customer will want a full shelf of this product. While the supply chain is working, normal demand might be 100 cases a week. If you have been out for multiple weeks, all stores now need additional inventory beyond their normal replenishment order quantities. A system recommended pipeline fill value has been a long-standing request, even going back to our E3 days, so we are more than delighted that we were able to devote four months of development and user testing to finally meet this need. The reason we focused on this supply chain issue NOW is that Long Term Outs have become a much more significant problem since the pandemic, increasing from 50-100 Items, to 800-1,200 for our typical wholesale grocery.
Finally, HIMPACT uses the long-term out flag to indicate that a more aggressive SALSA demand data cleansing approach is to be employed. This feature has been in production since January of 2023.
If you have any questions concerning SALSA, or how to more effectively manage long-term outs, please contact us for more information and our team of experts will be happy to answer your questions.