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The data warehouse and customer profitability

This is the first article of a five-part series on competitive advantage and the data warehouse.

This article originally appeared on the BeyeNETWORK.

Proponents of the data warehouse have long held that the data warehouse was the key to competitiveness. This assertion seems to be intuitively obvious—at least to those who have been around the industry for a number of years. But why does the data warehouse provide true competitive advantage?

This series of articles will explore how the data warehouse can provide true competitive advantage.

The starting point for the journey is the observation that for most organizations that manufacture and sell products, 20 percent of their customers provide all of the profit.

Many organizations seem to know this intuitively, but with a data warehouse it can be proven.

For example, Figure 1 below shows one way of looking at this assertion.

 

BillInmon,TheDataWarehouseandCustomerProfitability

How do you analyze customers to determine which are the most profitable? One way to determine customer profitability is to look at total customer volume of business. Identify the top 20 percent of customers who spend the most money and look carefully at their purchases. However, this simple way may yield skewed results because the biggest dollar volume customers may not be the most profitable.

A second way is to look at contract size. It may turn out that the cost of servicing a contract is such that only large contracts are profitable. Therefore, high-volume customers that buy frequently in small lots may be less profitable due to the cost of servicing the contracts. Instead, what is needed is a list of customers based on contract size, not total volume.

A third approach is to do a micro-level analysis. In a micro-level analysis, a profitability formula is constructed. The profitability formula is one that takes into account expenses and revenues. In a classical fashion, expenses are subtracted from revenue. The formula is then applied to each customer transaction. Then the net gain or loss for each transaction for each customer is calculated. This allows a net worth for each customer to be determined. Ranking the customers by net worth provides another way of determining who the most profitable customers are.

In any of these cases, the data warehouse provides the foundation of information needed for profitability analysis.

The first step in understanding how data warehousing leads to competitive advantage, is to look at customer profitability. Indeed, there is value in just this relatively simple step, because, once you know who the most profitable customers are, you know whom to cater to and to whom to address your advertising and marketing programs. For many organizations, merely knowing this information is sufficient payoff from the data warehouse.

But the search for competitiveness doesn’t stop there. Merely knowing who your profitable customers are is only the first step in achieving competitive advantage.

The next step to competitiveness is to understand not only who your profitable customers are, but also understanding the categories of revenue/profitability for all of your customers.

For example, there are profitable customers, sustainable customers and entry customers. The segmentation of customers into these categories provides some interesting information for management. How large are these categories? How long have people been in each of these categories? What dollar volume is represented by these categories?

It is the data warehouse that provides the basis of data for analysis. The data warehouse contains integrated data, historical data and granular data, which are precisely what the analyst needs to do the segmentation that has been suggested.

These questions lead to insight into the customer base. The organization is now one step further into achieving competitive advantage using a data warehouse.

Next week, in Part II of the series, I will discuss unprofitable customers.

Bill is universally recognized as the father of the data warehouse. He has more than 36 years of database technology management experience and data warehouse design expertise. He has published more than 40 books and 1,000 articles on data warehousing and data management, and his books have been translated into nine languages. He is known globally for his data warehouse development seminars and has been a keynote speaker for many major computing associations. Bill can be reached at 303-681-6772.

Editor's Note: More articles, resources and events are available in Bill's BeyeNETWORK Expert Channel. Be sure to visit today!

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