Larry English

Larry English 1947-2020

A few months ago the data management profession lost a legendary thought leader and much-respected practitioner, Larry English. 

Larry was a uniquely successful and transformational pioneer. Often referred to as the “Father of Information Quality,” Larry was one of the most well-known and oft-quoted authorities in data management and data quality. He developed the Total Information Quality (TIQM) system by adapting proven quality concepts from Deming, Kaizen, Juran, Shewhart, Ishikawa, Crosby, Baldrige, and Six Sigma. In fact, Larry’s homage to and application of these existing methodologies to the world of data management inspired me in developing the concept of infonomics which leverages traditional asset management and valuation methods.

The TIQM System has been implemented in market-leading organizations worldwide since the early 1990s. He had worked with more than 400 leaders in more than 40 countries on six continents. The American Society for Quality, MIT Information Quality Program, and DAMA International each have recognized and bestowed honors on Larry for his contributions. And his books, Improving Data Warehouse and Business Information Quality, and Information Quality Applied have been an industry staple for decades.  

Larry began his career with Sears, Roebuck and Co. as a programmer and systems analyst. He went on to found the consulting firm Information Impact International, and served as an adjunct associate professor in computer science. 

His key message about information quality was that it shouldn’t focus on downstream data cleansing or even about data itself, but rather on improving business processes to increase information quality. Larry defined information quality management as:

“The application of proven quality management principles, processes and practices to information as a product of enterprise processes to meet or exceed information consumers’ expectations.” 

The fundamental quality principles he espoused consisted of:

  • A customer focus

  • Process improvement

  • Proven methods

  • Management accountability

 

He also believed that successful information quality should consist of two sets of plans: one long-range plan to establish the IQ environment, plus an immediate improvement initiative. He showed how this kind of approach could cut in half the cost of continuing with defective processes while addressing downstream data cleansing. 

I believe Larry’s greatest contribution was the adaptation of Deming’s quality principles to information quality: 

  1. Create constancy of purpose for improvement of information product and service: Long term plan; the obligation to the knowledge worker never ceases.

  2. Adopt the new philosophy of quality shared information as a tool for business improvement: “Reliable (quality) shared information reduces costs.”

  3. Cease reliance on data and application inspections alone to achieve information quality: Design quality into the information design and production processes.

  4. End the practice of developing applications on the basis of “on-time,” “within budget” measures alone and capturing data at the lowest cost. 

  5. Develop single data creation programs and trust in information producers* Improve constantly and forever the processes of application and information development and service and of information production, through a habit of continuous “information defect prevention”.

  6. Institute training on information quality for all employees, especially management and producers.

  7. Institute leadership for information quality: appoint a full-time information quality leader; management must assume accountability for information quality.

  8. Drive out fear of data uncertainty or data correction: Implement incentive programs for finding / and correcting problem causes; do not blame or punish.

  9. Break down barriers between business areas: information management and application development; IT and business; business area and business area units.

  10. Eliminate slogans and exhortations; replace them with actions for information quality improvement such as a “Plan-Do-Check-Act” process for information quality improvement.

  11. Eliminate quotas of “productivity” that increase errors and costs of scrap and rework. 

  12. Remove barriers to pride of workmanship; empower information producers to fix the broken processes.

  13. Institute a vigorous program of education and self-improvement for all people. Understand the paradigm shift and learn tomorrow’s skills.

  14. Take action to accomplish the transformation for IQ. Senior management must feel the pain of the status quo, organize itself and communicate to a critical mass. Every process is a candidate for improvement.

 

During an interview Larry once commented, “An organization should never correct data before identifying the root cause of the information defects and defining process improvements that eliminate the causes of the defective process. Data correction is a major cost of poor quality information processes.” 

Although Larry’s life may have been cut short, his ground-breaking ideas live-on within organizations around the world--especially those treating information quality as a continuous process.

 

DOUG LANEY BIO

Doug Laney is the Data & Analytics Strategy Innovation Fellow at West Monroe where he consults to business, data, and analytics leaders on developing new value streams from their data assets. He originated the field of infonomics and authored the bestselling book, “Infonomics: How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage.” Laney is a three-time Gartner annual Thought Leadership Award recipient, co-chairs the annual MITCDOIQ Symposium, and is also a visiting professor at the University of Illinois Gies College of Business and the Carnegie Mellon University Heinz College. Follow and connect with Doug on Twitter and LinkedIn.