Data Warehouse ad hoc classification Oracle Tips by Burleson Consulting

The Data Warehouse Development Life Cycle

AN EXAMPLE OF AD HOC CLASSIFICATION

Let’s illustrate this concept with an example from Guttbaum’s Grocery. One of management’s requirements is to be able to compute the demand curve for each item category. As you may remember from Economics class, the demand curve for an item is a downward sloping curve that measures the propensity of a customer to pay for a product as the price changes. Obviously, the smaller the price the greater the sales, but it is the slope of the curve that is of interest to Guttbaum’s management. For example, Guttbaum’s management needs to be able to compute the demand curve for all brands of coffee to make an intelligent decision about which product to offer at a sale price. In Figure 3.16, you can see the computed demand curve for all customers for all brand names within a specific product category, in this case, coffee.

Figure 3.16 The demand curves for different brands of coffee.

Here, you can see that there are different demand curves depending on the brand name. Essentially, this is a measure of product loyalty, and this type of information is very useful when management decides which product to advertise at a discounted price. In this example, a $1 per pound price reduction will have drastically different effects on various brands of coffee. For instance, a price reduction will not affect the demand for Java Joe’s Coffee, indicating that consumers of Java Joe’s have a high product loyalty, as evidenced by the inelastic demand curve. Peak Coffee, on the other hand, shows a very large increase in demand when the price is reduced by $1 per pound. If the goal of a sale is to get customers into the supermarket, then it appears that the brand name with the most elastic demand curve would be the best choice for an advertised price reduction. Guttbaum’s wants to offer specials on those products that demonstrate a high elasticity--the products that will substantially increase sales volume with a small drop in price. Figure 3.17 illustrates price elasticity and how it affects sales.

Figure 3.17 Price elasticity for different products and the effect on in-store promotions on sales.

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This is an excerpt from "High Performance Data Warehousing", copyright 1997.

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