Data Quality – an imperative for better business outcomes
W. Edwards Deming, an electrical engineer, became interested on how statistical analysis could be used to drive better quality output from operations. Adopted by the Japanese for their reconstruction after WWII, his 14 Point treatise became a go-to approach for improving output in industrial facilities.
Who could have thought that his principles could also apply to something without Who could have thought that his principles could also apply to something without mass but equally important as a foundation for long lasting business results – DATA.
Data quality is the focus of a recent article on Dataversity.net – The Impact of Poor Data Quality (and How to Fix It) by Keith D. Foote. Sources of Poor Data Quality, Consequences and Methods for improving Data Quality comprise the three clearly outlined sections of this quick and effective read.
What caught my attention is how we can draw a direct connection between Demings 14 Points and Foote’s article. Logical it would be to look in Deming’s points for emphasis on better machinery adjustments to generate improved precision in manufacturing industrial components. Or one would think that Foote’s article would call for more robust code to properly ingest data.
Both authors, however, place more emphasis on people and culture as a roadmap to better quality results. Driven by senior leadership, today’s organizations need to acknowledge that the growing enthusiasm with more and more data for better decisions demands a concerted, company-wide and strategically-structured approach to ensure the data on which business directions and ultimately outcomes depend is treated as an ultra-valuable asset for which a quality focus is paramount