Let’s look at the steps in more detail for building a business case for data quality using the bottom-up approach. Where do you start? You need to find a sponsor—someone who instinctively knows there is a problem and wants help in quantifying it. Marketing knows it has duplicate customer records and wants to get a better handle on them. You should look at these systems or business processes that work with the customer data. You must assess how the data in these systems is used within marketing. For example, what is the data used for, what critical decisions are made based on this data, and how many people use it to make decisions? The more users or the more critical the decision, the more likely this data is a candidate for evaluation. Also look at more than the initial decision support system and data. Look at any systems that get data from the decision support system. Data flow diagrams are always helpful in assessing this but usually difficult to find.
For example, the system is used for marketing campaigns. You need to also look at where the data comes from—that is, a “purchased” mailing list or some other source. You need to look at who else gets the data. After the mailing, do you send the data to the telemarketing system for a call campaign to follow-up on the mailing? If the assessment looks only at the mail campaign, missing or bad phone numbers would not matter. However, if you know the next step in the process is the telemarketing group, then suddenly, the accuracy of the phone numbers becomes critical.
Additionally, if you have a data hub that feeds multiple systems, it is a great candidate for assessment. You need to understand how each of the downstream systems uses the data it receives from the hub. Once you figure out this effect, then you need to understand the impact of making poor decisions based upon the data. The evaluation is easier after you have profiled the data.
For more on the steps your organization should take to build a business case for data quality, take a look at this interactive eBook entitled Selling the Business Value of Data Quality.