Systemic Choices by Daneke Gregory A.;

Author:Daneke, Gregory A.;
Language: eng
Format: epub
Publisher: University of Michigan Press

Much of the foreign interpretation of Japanese management is either one sided—with more recent emphasis on success factors—or one dimensional . . . training and employment practices are treated in isolation from the hardware or technology issues. . . . [Also] firm level types of factors—human resource strategies or marketing issues—are isolated from broader industrial goals and public policies. (16–17)

In essence, a gestalt or systemic view of Japanese management gives a much clearer picture of the nature of their successful strategies. Obviously, cultural and political disparities between the United States and Japan make a difference. The fact that the Japanese universities produce approximately ten engineers for every lawyer, and in the United States the ratio is exactly the opposite, probably has an impact. For example the Japanese prowess in process engineering probably results from the synergy of workforce and reward systems. Generally speaking, a comparison of U.S. and Japanese high-tech industries yielded items quite similar to Erich Trist’s comparison of old and new sociotechnical paradigms (see Brown and Daneke 1990). That is, Japanese firms exhibit patterns congruent with the normative implications (see table 5) of “sociotechnical systems theory” (SST). In a recent article Charles Manz and Greg Stewart (1997) contend that a blend of perspectives from STS (à la Emery and Trist 1973) and TQM should be highly instrumental in addressing the apparently conflicting demands for “stability and flexibility.”

At work in the Japanese firm (or any firm for that matter) are many nonlinear processes, and it is their awareness and nurturing of these processes that explain much of their relative vitality. Most prominent among these are the “experience curve” and “network externalities.” U.S. economists and management specialists have been aware of these processes (Hirschman 1984; Katz and Shapiro 1985; Arthur 1983), yet their overall importance has been somewhat overlooked. The experience or learning curve describes the simple yet powerful phenomena of performance improvements that accumulate as a result of experience. For example, unit cost reductions take place that are not only the result of increasing labor productivity but occur across all cost categories (e.g., overhead, marketing, etc.). In essence, experience cascades and collides to create learning throughout the organization, and this learning is reflected in real cost reductions over time. Studies of the experience curve have demonstrated 10 to 30 percent cost reductions across a range of industries per experience doublings (Conley 1970, 8). Essentially, the experience curve is a primary example of “increasing returns,” a fact that flies in the face of traditional economic theories (i.e., “the law of diminishing returns”). Network externalities is the term economists use, which implies that these extramarket phenomena are somehow aberrations. In reality, they are quite ubiquitous (note Maruyama 1982; Arthur 1988; for a nontechnical discourse see Arthur 1990). Feedback within these networks often generates signals that completely contradict the logic of the market. As Brian Arthur (1988) observed, these networks can cause “lock in” and allow an inferior technology to gain a predominant position. As Magorah Maruyama (1982) points out, these processes of “deviation amplifying, mutual causality” are quite common in nature.

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