In my book, Enterprise Knowledge Management: The Data Quality Approach, one of the main issues I discuss is building a business case for data quality improvement based on determining a return on the investment made in the infrastructure and affiliated ongoing costs related to improved data quality. In a simplistic way, this approach is appealing in a commercial environment driven by profits because we are more likely to be able to find opportunities for increased revenues by improving data quality.
An interesting question arises when confronted with developing a return on investment argument for organizations not primarily concerned with profits, including nonprofit organizations and state and federal government organizations. In this case, our goal is to identify different kinds of business impacts to which we can link poor data quality; and this is a more thought-provoking challenge because it forces us to think about quantifying the value of business aspects that are not typically reviewed.
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