William G. Hunter Award 1997: Lynne Hare

The 1997 William G. Hunter Award was presented to Lynne B. Hare at the Fall Technical Conference (FTC) in Baltimore, Maryland. The Statistics Division of the American Society for Quality (ASQ) established the Hunter Award in 1987 in memory of the Division's founding chair to promote, encourage and acknowledge outstanding accomplishments during a career in the broad field of applied statistics. The attributes that characterize Bill Hunter's career - consultant, educator for practitioners, communicator, and integrator of statistical thinking into other disciplines - also characterize Lynne's career.

Lynne Hare is Chief, Statistical Engineering Division, National Institute for Standards Technology. Prior to his current job Lynne worked as an independent consultant in applied statistics and quality management, a director and manager at Thomas J. Lipton Co., visiting professor at Rutgers University, consulting statistician at CPC International, Best Foods Division and a Group Leader in statistics at Hunt-Wesson Foods, Inc. He is a Fellow of ASQ and ASA. He is chair of the Quality and Productivity Section of ASA and was chair of the Statistics Division of ASQ in 1988-89. He has also served on several other ASQ committees and review boards. He is currently the chair of the Ellis R. Ott Scholarship Award Committee, which is administrated by the Statistics Division. Lynne made these remarks in accepting the award at the FTC:

Bill Hunter emphasized the human side of statistics. He developed and exposited statistical methods, and he made the discipline come alive. Bill got involved with the community by sharing his extensive knowledge in statistics and quality management. Many know of his accomplishments with the City of Madison. Bill's successes made people thirst for more.

Bill also linked statistical methods to other-than-usual applications of research and quality control/quality improvement. He did this by maintaining a grand process view, seeking sources of variation, and using data - the right amount of the right kind of data - to effect improvements. These three components form the basis of Statistical Thinking. In Statistical Thinking, as in so many other areas, Bill was years ahead.

Bill also acknowledged help. Likewise, I thank the ASQ Statistics Division, specifically the Statistical Thinking Team who, as I, are students of Statistical Thinking, and the Statistical Engineering Division at the National Institute for Standards and Technology for helping me to learn and grow. Thank you.