Improving product and process quality requires that organizations make data-driven decisions about when, how much, and how often to adjust aspects of operations.
This means the data has to be available and accurate! Unfortunately, information often is siloed, living in Word docs and Excel files, and although that data might be on a publicly accessible network, finding it and knowing whether it will meet your needs can be impossible.
Busting silos and encouraging collaboration facilitates systems integration and leads to better decisions -- ones that save time, money and effort while capturing valuable opportunities for growth and improvement. A solid plan for data governance -- strategic, high-level planning and control for data management tasks.
A data governance framework essentially is a quality management system for data. Setting one up is an essential part of planning for Quality 4.0 for large enterprises or other organizations that are drowning in data.
The Data Management Association (DAMA) defines data management as the “development,
execution, and supervision of plans, policies, programs, and practices that control, protect, deliver, and enhance the value of data and information assets.” DAMA defines governance as “the exercise of authority, control, and shared decision making (planning, monitoring, and enforcement) over the management of data assets.”
The best place to begin is to figure out the most critical data that your organization needs to survive -- items like who your employees are, who your customers are (and how to get in touch with them) and data about the products you offer and the suppliers who help make them possible. This master data tends to change slowly over time, but should be carefully controlled by processes and guidelines, as well as metrics to provide insight into its evolution.
Khatri, V., & Brown, C. V. (2010). Designing data governance. Communications of the ACM, 53(1), 148-152.
Radziwill, N. M. (2018, October 5). Your Data is Your Most Valuable Asset: Getting Started with Quality 4.0. Intelex Blog. Available from https://blog.intelex.com/2018/10/05/data-valuable-asset-getting-started-quality-4-0
About the Author: Nicole Radziwill Quality Practice Lead
Nicole Radziwill is the Quality Practice Lead at Intelex Technologies. Before Intelex, she was an Associate Professor of Data Science and Production Systems, Assistant Director (VP) End-to-End Operations at the National Radio Astronomy Observatory (NRAO), and manager and consultant for several other organizations since the late 1990's bringing quality management to technologically-oriented operations. She is a Fellow of the American Society for Quality (ASQ) with a Ph.D. in Quality Systems from Indiana State University. Nicole serves as Editor of Software Quality Professional (SQP) journal and is a former Chair of the ASQ Software Division. She is an ASQ Certified Manager of Quality and Organizational Excellence (CMQ/OE) and Certified Six Sigma Black Belt (CSSBB).
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