June 12, 2006
JDQ Systems has recently completed two data quality improvement projects for large Canadian companies with revenues in the billions of dollars. In one case, the objective was to assess and improve the quality of millions of records containing customer name and address data for a service-oriented company. In the second case, a production and refining company needed to correctly define, measure and analyze hundreds of production control parameters, automatically measured and collected more than 14,000 times each day.
JDQ's expertise in both information technology and quality improvement methods made it the ideal candidate for these data quality projects. JDQ's data quality initiatives helped these companies:
- reduce measurement uncertainty,
- simplify and automate data preparation, analysis, standardization, "fuzzy" matching and survivorship,
- improve predictions, forecasts and decision making,
- enhance business relationship management and communication, and
- expedite business process improvement.
For each initiative, JDQ's project teams used their in-depth knowledge of applied statistics on issues arising from the data analysis. While each client and project was very different, the data quality improvement opportunities were revealed by using similar techniques including:
- Six Sigma Defects per Million Opportunities (DPMO) for measuring data quality.
- Measurement System Analysis (MSA) for understanding measurement uncertainty.
- Probability statistics for the identification of data duplication and data matching.
- Statistical Process Control (SPC) for achieving process stability.
- Histograms and capability analysis for assessing process and data quality relative to corporate objectives.
JDQ project teams used statistical applications such as Minitab, Statgraphics and IBM WebSphere QualityStage to support their data quality analysis and improvement initiatives. After several years of experience with these software tools on various IT platforms, JDQ's consultants have become recognized experts in advising and training clients in these applications.
JDQ President and ASQ Six Sigma Black Belt Jon Morris comments: "Data quality is a growing concern for our clients. Improving data quality requires a broad set of skills including a solid understanding of applied statistics, information technology and project management. JDQ is uniquely outfitted to provide the expertise required to define, measure, analyze, improve and control data quality."
