Chapter 1 - Business Impacts of Poor Data Quality

Abstract

This chapter discusses different types of risks that are attributable to poor data quality as well as an approach to correlating business impacts to data flaws. To be able to communicate the value of data quality improvement, it is necessary to be able to characterize the loss of value that is attributable to poor data quality. The chapter gives some basic understanding of data use, information value, and the ways that information value degrades when data does not meet quality expectations, different categories of business impacts attributable to poor information quality, ways to facilitate identification, and classification of cost impacts related to poor data quality. The objectives of designing an impact hierarchy are twofold. First, the original intention of determining how poor data quality impacts one's business processes is a much more manageable task when it can be broken up into small analytic pieces. The categorical hierarchy of impact areas naturally map to the future performance reporting structure for gauging improvement. As one identifies where poor data quality impacts the business, one also identifies where data quality improvement enhances the business. This provides a solid framework for quantifying measurable performance metrics that is eventually used to craft key data quality performance indicators.