Outline for a Business Justification for Data Quality Improvement

August 30, 2011 by
Filed under: Data Analysis, Data Governance, Data Profiling, Data Quality 

I am currently working on my presentation slides for the upcoming DataFlux IDEAS conference, and the topic I am discussing is building a business justification for data quality improvement. I intend to walk through the assessment process to understand specific business impacts of data flaws, then look at evaluating alternatives for improvement, and then developing a cost/benefit analysis.

One artifact I plan to share is a template for the final report, and I thought that this would provide a good teaser for the high level section topics:

  • Introduction, (duh) which gives an overview of the report and its conclusions and recommendations;
  • Process, which details the methodology used for soliciting feedback from the users, synthesizing their experiences, and measurement;
  • Business Impacts of Poor Data Quality, which provides specific details as per the Knowledge Integrity 4-vector (Financial, Risk, Productivity, Trust) impact categorization scheme;
  • Root Causes of Poor Data Quality, where we specify what kinds of errors exists and how they are linked to the business impacts;
  • Aggregation of Impact, in which the aggregate impacts are related to specific root causes so as to direct the consideration of solution alternatives;
  • Alternative Solutions, which provides some different approaches for addressing the root causes and relative costs;
  • Cost/Business Analysis, which looks at the potential “lift” for selected solution alternatives and offsets that against their costs and resource requirements, within a prioritization scheme;
  • Recommendations, detailing the best opportunities for short-, medium-, and long-term improvements; and the
  • Summary, which reinforces the suggestions as well as revisit the risks on inaction.

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