After graduating from Lehigh University in 1960, Scott Armstrong worked as an industrial engineer at Eastman Kodak. He became interested in forecasting, partly because he found it fascinating, but also because he was astonished at the primitive forecasting procedures then used in business. More than forty years later, he is still astonished.
He left Eastman Kodak to earn an MBA from Carnegie-Mellon University in 1965, then a PhD from the Sloan School, MIT in 1968. Since then, he has been teaching at the Wharton School of the University of Pennsylvania, where he is a professor of marketing. He was a visiting professor at the Stockholm School of Economics in 1974-75 and at IMEDE in Lausanne, Switzerland in 1980-81. In addition, he has held five visiting positions in New Zealand, and has taught in South Africa, Thailand, Argentina, Japan, and other countries.
Armstrong was a founding editor of the Journal of Forecasting in 1981 and the International Journal of Forecasting in 1985. He was also a founder of the International Institute of Forecasters and served as its president from 1982-83 and again from 86-88. In 1996, the International Institute of Forecasters named him as one of its first six "honorary fellows" for distinguished contributions to forecasting.
A 1989 study by Kirkpatrick and Locke (Group and Organizational Management, 17 (1992) 5-23), based on publications, citations, and peer ratings by faculty, ranked him among the top 15 marketing professors in the US. In an analysis by the Lippincott Library of the Wharton School, he was found to be the second most prolific Wharton faculty member during the 1988-1993 period.
He has merged forecasting with marketing and is currently engaged in a project to forecast the sales effectiveness of advertising. His other interests include studies of social responsibility in business, the use of formal planning in organizations, the design of learning systems (as contrasted to teaching systems), and the conduct and reporting of scientific studies.
His research findings have often challenged conventional wisdom. For example, in a study on planning, he concluded that firms that ignore market share when setting objectives are more profitable than those seeking to increase market share. In forecasting, he concluded that fairly simple models typically outperform complex ones. For this handbook, he has called on other researchers who challenge current wisdom for help in developing an inventory of what is useless as well as what is useful in forecasting.
His studies on reporting scientific research revealed that readers are impressed by researchers who produce papers that are hard to read, a phenomenon known as â€œbafflegab.â€ (His paper on this topic is the second most frequently cited study published in the journal, Interfaces.) Despite this finding, he decided that Principles of Forecasting should focus more on being readable than on being impressive.