BPSPAP12482

THE BCG MATRIX REVISITED: A COMPUTATIONAL APPROACH
Although the Boston Consulting Group’s growth share matrix has been the subject of many critiques, there has been surprisingly little empirical research that directly examines the effectiveness of the model. The current study uses a computational model based on Nelson and Winter’s (1982) evolutionary model of economic change to test whether firms using BCG’s investment rules outperform firms using Nelson and Winter’s investment rules. We found that the original BCG rules were not capable of outperforming the Nelson and Winter rules even under the most favorable conditions. However, we were able to use this data to construct a set of modified BCG rules that outperformed the Nelson and Winter on almost every occasion. The implications of these results are discussed. Key Words: portfolio planning; simulation; agents; evolutionary economics

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BPSPAP12482 The Boston Consulting Group’s (BCG) growth share matrix is one of the best known and persistent tools in strategic management. At the height of its success between 1972 and 1982, the BCG matrix was used by around 45% of the Fortune 500 (Bettis & Hall, 1981; Haspeslagh, 1982). The JSTOR database reports that no fewer than six major journal articles were authored on the BCG matrix in 1982. However, in the first decade of the 21st century, the BCG matrix is certainly in the decline phase of its product life cycle; perhaps qualifying for ‘dog’ status in its own terminology. References to the BCG matrix have disappeared from graduate textbooks and academic journals, and are slowly being phased out of undergraduate and marketing texts except, perhaps, as historical footnotes. There are several sound reasons for this decline, including: the model’s use of only two dimensions (growth and share) to assess competitive position, the focus on balancing cash flows rather than other interdependencies, the emphasis on cost leadership rather than differentiation