Friday, March 18, 2011

Advantages of Cloud Computing– Part XV – Forecasting

The three major components of deciding what to put in your stores and how to price it are usually based on historical data, math and judgment made up of product influences, item relationships, store influences, business influences, store layout, and corporate influences; resulting in order determination, category management, labor scheduling, planograms, merchandise planning and allocation.

Now think for just a minute. What currently goes into the determination of floor levels, placement and the selling price of those king-size Snicker bars sitting on the shelves in your stores? The floor levels are most likely determined by the space provided and how many bars your supplier delivers with each order. The placement is wherever there’s a spot available in the candy category, and the selling price is most likely determined by the manufacturer’s suggested retail (MSRP), regardless of the influences mentioned in the paragraph above. In the current environment, your suppliers are forecasting for the time the stores will want the product and the stores are… well, relying on the supplier to put what they need in their stores. This is a crippled system that needs re-engineering.

Forecasting differs from order determination in that forecasting attempts to determine product needs in future periods based upon future assumptions, dealing in parameters such as next week, next month,  or next July 4th, while order determination deals with only the next delivery.

Forecasting by item is seldom considered (if ever) in the convenience store industry, but if you had the resources to implement such a program, it would help to increase the profits in your stores. If you had a tool, or a third party, that could do that for you at a price that would result in higher profits, would you be interested? Sure, who wouldn’t want to lower inventory costs and increase profits? The main question then, is ‘how will you get the information to a third party in the format and in the right time period to give the forecaster time to make the predictions?’

I’ve come up with the answer. It may not be the only answer, but I can guarantee you it is better than what you’re doing now.  The facilitator of this program is The Cloud, because to be effective a forecasting service needs a continuous inflow from positive and negative feedback loops.  If you’ve read “Turning Convenience Stores Into Cash Generating Monsters,” we talk about how feedback loops are used to guide intercontinental ballistic missiles. Today’s forecasts for next month’s sales may be different than tomorrow’s. It all depends upon prevailing conditions.

I am told major department stores follow weather forecasts to decide when to put more umbrellas on the sales floor and when to take some of them back. I’ll bet you didn’t know umbrella sales went up when Michael Jackson died? Sales of science fiction books increased when the economy tanked. Glock pistol sales spiked after Gabrielle Gifford’s attempted assassination.

These blips in product movement are important because they may result in what we all love to love – increased profits. The irony of the situation is when something goes up, something else usually goes down. Apartment rentals rise when home sales take a dive. When your supplier announces a promotion to move more XYZ in your store, what you may not know is ‘what else might be affected?’ It may be something turning a good profit for you at this very minute.

Forecasting is both a science and an art. The numbers may tell you this or that, but the reality might be something entirely different.

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