Evaluating strategic alternatives: An analytical model

-The amount of information involved in strategic decision making and the computational limitations of human decision makers makes strategy selection a difficult task. Various approaches from sheer intuition to computerized decision systems have been proposed for strategy selection. In this paper we present an analytical model which systematically evaluates a series of strategic alternatives by decomposing environmental opportunities and threats into internal, transactional, and contextual segments. Judgments about opportunities and threats are used to obtain two composite weighted scores measuring the risk and return associated with each strategic alternative. The proposed system puts the decision maker and the computer into an interactive partnership by providing a formal and systematic approach to strategy selection while using the computer to manage complex logical processes and vast amounts of information. 1. I N T R O D U C T I O N The literature on strategic planning has presented many definitions of corporate strategy and corporate planning [1-3]. However, one of the oldest defintions of corporate strategy defines it as "the determination of the basic long-term goals and the objectives of an enterprise, and the adoption of courses of action and the allocation of resources necessary for carrying out these goals" [4, p. 13]. A company has only one corporate strategy which may incorporate several business strategies [5]. A business strategy refers to the choices made by a strategic business unit after examining risks and opportunities in the market, expected behavior of competitors, and the strengths and weaknesses of the unit [11. There are many paradigms for strategic management [6]. Most of these paradigms agree that the strategic management process, both for corporate and business "l'Madjid Tavana is Chairman of the Management Department at La Salle University where he has also served as the Director of the Center for Technology and Management. He received an M.B.A. in Management Science from La Salle University and a Post-Master of Information Systems from Drexel University. Dr Tavana completed his doctoral coursework in Systems Sciences at the Wharton School of the University of Pennsylvania and received his Ph.D. in Management Information Systems from the American University of London. His research interests are in Multi-Criteria Decision Making. Model Management, Decision Support Systems, and Expert Systems. Dr Tavana has published in such journals as Expert Systems with Applications, Journal of Management Systems. lnter/'ace, and Organizational Behavior and Statistics. ,Snehamay Banerjee is Assistant Professor of Management Information Systems and Management Science at Drexel University. He received an M.Tech. in Engineering from India, an M.S. in Operations Research from Case Western Reserve University, and a Ph.D. in Management Information Systems from the University of Maryland at College Park. His current research interests are in Knowledge Based Systems and their uses in Management Science, Model Management, and Electronic Data Interchange. Dr Banerjee's works have appeared or are to appear in b!formatim) and Management. Decision Support Systems, b~ternational Journal of Operations and Production Mana#ement, Pro&wtion Pltmnhl~l and Control, International Journal of Technology Management, Ioternational Journal of Production Ecoltomics, Journal o/" b¢/brmation Technology. and Journal o/" Computer h!/brmation Systems.