In my last blog post, I discussed the topic of building the business case for data quality. As such, one of the points I mentioned was the need to highlight resulting issues. Since my last post, I have had a number of discussions with clients and prospects on this topic. At the core of these discussions is the same fundamental question – what is the best way to package up the issues we uncover? In answering this, I often discuss the six dimensions of data quality (Completeness, Conformity, Consistency, Accuracy, Integrity, and Duplicates) and how to use a data quality scorecard to present the information in a meaningful way that it can be shared with key stakeholders within the organization. Although my response to this question remains the same, a conversation I overheard at the airport a couple of weeks ago made me look at the need for a DQ scorecard a little differently.

While grabbing a bite to eat prior to a flight, I overheard two gentlemen who were both retired from the newspaper business discussing how people don’t really take the time to read a newspaper like they used to. They were lamenting that people today preferred quick sound bites of information – whether it be from television or from reading one of the various news sites on the Internet.
This discussion struck a chord with me, as I had just wrapped up a discussion with a client where their means to build a business case for data quality was going to be driven by their ability to compile the results of their analysis into a quick snapshot or dashboard for key stakeholders to make a decision. Thus, just like the comment about people wanting “just the facts” when they read the news, the same holds true for data quality. Although some people still want to read the entire paper from front to back, the vast majority might choose to start with the headlines and only read an entire story if it appears to be of interest. In the case of data quality, a dashboard provides you with the overall state of data quality in your organization, while providing the capability to drill down as needed. Thus, just like in a newspaper article where the headline might influence whether someone decides to read the entire article or not, the types of issues captured in a dashboard will likely influence whether you are in tune with the types of key data quality in your organization, or if this is the type of “headline” that doesn’t entice the reader (or key stakeholders) to want to learn more. How successful you are in garnering attention to data quality issues through the dashboard results will directly impact your ability to articulate the need to pursue a data quality initiative.

Until next time…