Learning Curve Applications

We turn now to a brief overview of applications for improving firm performance that are based on the learning curve. Organizations use learning curves as planning and forecasting tools. Analyses based on organizational learning curves have been used in many applications geared at improving firm performance (Dutton et al., 1984). Learning curves have been used to plan and manage the internal operations of firms as well as to make strategic decisions regarding their behavior vis-à-vis other firms. For example, on the internal side, learning curves are used for planning production schedules, setting labor standards, planning for training, deciding about subcontracting, making delivery commitments, budgeting, monitoring performance, and determining manufacturing strategy (Ghemawat, 1985; Hayes & Wheelwright, 1984; Jucker, 1977; Levy, 1965). On the external or strategic side, firms use fore- casts based on learning curves to predict competitor’s costs (Henderson, 1984) and to decide about whether to enter a market and how to price their products.

At a more macro level, the rate, persistence and transfer of learning are also impor- tant issues for antritrust policy (Spence, 1981), trade policy (Baldwin & Krugman, 1988; Gruenspecht, 1988; Young, 1991), and market structure and performance (Benkard, 2004; Besanko, Doraszelski, Kryukov, & Satterthwaite, 2010; Dasgupta & Stiglitz, 1988; Ghemawat & Spence, 1985). Developing the implications of organiza- tional learning and its persistence and transfer for these phenomena are important undertakings and worthy of future research but beyond the scope of this monograph. Dutton et al. (1984) vividly described the problems associated with some appli- cations of the learning-curve concept that were too simplistic. The learning curve came into vogue as a management tool in the 1960s and 1970s (e.g., see Conley, 1970). It was promoted by consulting groups and by the US government’s require- ment that defense contractors include estimates of progress rates in their proposals. Unfortunately, some of these applications treated learning as though it were auto- matic. Relatedly, there was also a tendency to adopt the “80% learning curve” as the norm. Proponents of this view believed that all production programs should achieve an 80% learning rate—that is, with each doubling of cumulative output unit costs would decline to 80% of their previous value. Indeed, we have encoun- tered a few organizations where managers were fired because their operations did not achieve an 80% learning curve. This belief in an 80% learning curve is too simplistic and neglects the many factors that affect rates of learning. The overly simplistic use of the learning curve led to some disgruntlement with it in the 1980s (Kiechel, 1981).

The 1990s have enjoyed a resurgence of interest in organizational learning. More recent analyses of learning curves are more appreciative of the many factors affect- ing learning than earlier treatments were. Academic interest in organizational learn- ing has increased dramatically in recent years. The many popular books and articles on organizational learning and knowledge management reflect concern on the prac- titioners’ side. Subsequent chapters of this monograph return to learning curve applications and develop the operational and strategic implications of new results on organizational learning for firm performance.

Source: Argote Linda (2013), Organizational Learning: Creating, Retaining and Transferring Knowledge, Springer; 2nd ed. 2013 edition.

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