Enhancing the Bottom-Line Impact of Statistical Methods

Abstract

The purpose of this article is to diagnose the root causes for statistical methods not reaching their potential bottom-line impact and to suggest potential solutions. Evidence of the tremendous potential impact of statistical methods, and for the lack of widespread achievement of this potential, is briefly reviewed. Some of the key root causes for this situation are identified as follows; overemphasis on the tools, with a lack of understanding of how statistical concepts and methods apply at the strategic and managerial levels of an organization; attempts to jump to the latest, most sophisticated methods without dealing with the required basic building blocks; and the general lack of understanding within the managerial and statistics communities of the scientific method, at least as practiced by other scientists.

Specific suggestions are given for addressing each of these issues. Implementing these suggestions will require understanding of basic frameworks from the field of organizational effectiveness and of the manner in which the scientific method is actually applied in other sciences. Recent research by George Box is used to illustrate how mathematics is necessary, but not sufficient, to effectively apply the scientific method utilizing statistical methods.

• problem solving
• scientific methods
• statistics education

Additional information

Notes on contributors

Roger W. Hoerl

Roger W. Hoerl is the manager of quality methods and information at Scott Paper Company. He earned a doctorate in statistics at the University of Del aware. Hoerl may be contacted at Scott Paper Company, Scott Plaza I, Philadelphia, PA 19113.