When it comes to back-room and sales floor inventory, too much is simply too much.
Inventory glut can be a big problem for convenience retailers. Too much inventory means too many damaged products, high levels of shrink, and high amounts of labor devoted to maintaining all that stuff. There’s a cost of holding that inventory, and the retailer could use that money for something else.

There is a need for a better system for counting, and more importantly, ordering products.

A Computer Assisted Ordering system uses point-of-sale data as its main driver for forecasting. It relies on complex algorithms to predict demand based on product movement history. The system needs about three months of daily data to get a good trend. The software adjusts for seasonality; it starts seeing weekly and monthly trends as months go in and out of summer and winter on certain products. It adjusts quite well, and quickly. The more it is used and the more data is entered into the system, the more it optimizes the order.

  • A minimum amount (safety stock) is entered into the system, which is a combination of product on the shelf and in back-stock at any time. The system then displays the forecasted order for the store manager, showing the history on this item. It can forecast how much the store will sell until your next delivery.
  • The store manager evaluates the forecast and is allowed to decide what adjustments are needed for the order before the forecasted order is sent or given to the supplier.
  • Since the CAO system makes its predictions based on the POS data and counts of inventory on hand, it’s essential that an accurate physical inventory is taken before going live with a particular category. Otherwise it’s a true “garbage in, garbage out” scenario. Because of this, when an error occurs, it’s usually a human one, such as a bad count or a mis-pick on the supplier’s end, which means it can easily be corrected by fixing procedures in handling inventory.
  • Once the system is rolling and all counts are correct, not many changes are needed to the system, other than those for seasonal adjustments.

As long as the store manager is disciplined in doing inventory counts, the system can be trusted to do the right thing. But turning over control to the system is not easy for everyone, especially for those
who began their careers before the advent of computers.

Spotting noncompliance is generally an easy task. Typical users of the CAO system change only a small percentage of each order generated by the system. Higher percentages of adjustments–outside of
promotions–are usually indicative of a manager making up for mistakes or a lack of discipline in inventory counts.

Conversely, if a manager is taking twice as long as the average user to review the orders in the store, it’s a pretty good indication that he or she is trying to micromanage it instead of just looking at the
exceptions.

This might sound like a lot of labor–and it is. If the total time it takes to order with computer assisted ordering, doing all of the cycle counts, and all of the maintenance is summed, it’s about the same
amount of labor as before CAO was implemented. Still, labor is saved in other areas, such as handling excess inventory. If that labor is factored in, then yes, there are labor savings. There are also the
inventory reduction and working capital investment reductions to be added to the savings. All three of those bring an immediate payback to utilizing Computer Assisted Ordering programs.