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Building A Business Case For Data Quality: Overview

Building A Business Case For Data Quality, 2 of a 7-part series

When building a business case for a data quality initiative, you can either build a case from the top down or from the bottom up. From the top down, you’ll be working with corporate executives who have already identified a problem that is most likely caused by a data issue. Some examples are:

  • Fines for violating the do-not-call list
  • A large number of mailings failing to reach intended recipients
  • Failure to receive volume discounts from vendors because there are multiple item numbers for the same item
  • An increase in the average talk time in the call center because agents are spending too much time correcting the data in the system

Building a business case from the top down is the most efficient way of doing so, but unfortunately, it is rare that metrics such as the ones above are clearly defined. Instead, you often need to build the business case from the bottom up. This approach will be the focus of this series of Blogs.  The bottom-up approach starts with looking at the data first. Here you need to profile the data with an automated profiling tool, such as Informatica Data Explorer, or you can ask Informatica to assist you with a Data Quality Assessment or Business Value Assessment (which is actually a hybrid of the two approaches) service to get you started. Profiling your data can reveal its content, quality, and structure with minimal effort.

After the initial assessment, you may want to categorize the anomalies and establish some basic metrics to measure the quality of your data. It helps to put these into categories, which should be based upon specific characteristics of your data.

The next step in measuring data quality is identifying the business impact of data quality anomalies. After profiling the data and identifying the data anomalies, you then work with the business to understand the effect the anomalies could have on the business. For example, a profile of your customer data shows that 8 percent of the records have inoperable or missing phone numbers. How does that impact your ability to up-sell or cross-sell your other line of business products to your existing customers? If you are missing 3 percent of your medical procedure codes in your insurance claims, what is that cost in terms of rejects, research, correction, and resubmission of those claims? What about the value of the money during the time you are not being reimbursed for these claims?

Finally, you create the business case. In it, you show how the anomalies are affecting the business and how repairing the anomalies can increase revenue or decrease costs.

In general, a major difference in the two approaches has to due with budget money. In the top-down approach, management has already allocated some money to investigate and fix the problem. In the bottom-up approach, you are trying to quantify the problem to obtain initial or additional budget money for beginning the project. With the bottom-up approach, you also are trying to estimate the impact that the data quality issues have upon the business.

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