Organizational learning theory

Organizational learning theory states that, in order to be competitive in a changing environment, organizations must change their goals and actions to reach those goals. In order for learning to occur, however, the firm must make a conscious decision to change actions in response to a change in circumstances, must consciously link action to

Introduction to Organizational Learning Curves

“Learning curves” have been found in many organizations. As organizations produce more of a product, the unit cost of production typically decreases at a decreasing rate. A learning curve for the production of an advanced military jet built in the 1970s and 1980s is shown in Fig. 1.1. The number of direct labor hours

Historical Overview of Organizational Learning Curves

Psychologists were the first to discover learning curves (see Mazur & Hastie, 1978, for review). These researchers focused on the behavior of individuals. Psychologists found that the time individuals took to perform a task and the number of errors they made decreased at a decreasing rate as experience was gained with the task (Ebbinghaus,

Recent Research Trends on Organizational Learning Curves

1. Expanded Set of Outcomes Several important new trends have occurred in research on organizational learning curves in the 1990s. First, researchers expanded the set of outcome measures used as indicators of organizational learning. Research conducted before the 1980s had shown that outcomes in addition to the number of direct labor hours per unit

Measuring Knowledge and Assessing Learning

The classic form of an organizational learning curve is where y = the number of labor hours per unit a = the number of labor hours required to produce the first unit x = the cumulative number of units produced through time period i b = the learning rate i = a time subscript

Organizations Vary in Their Learning Rates

Organizations vary dramatically in the rate at which they learn. Some organizations show remarkable productivity gains with experience, whereas others evidence little or no learning. A study by Dutton and Thomas (1984) nicely illustrated the tremen- dous variation observed in organizational learning rates. Dutton and Thomas plotted a frequency chart or histogram (see Fig.

Sources of Variation in Learning Rates

What explains the variation in the rate at which organizations learn? Many researchers have speculated about factors explaining organizational learning curves and con- tributing to the variation observed in organizational learning rates. For example, Hayes and Wheelwright (1984) discussed the following factors as facilitators of organizational learning: individual learning, better selecting and training of

Theoretical Models of Organizational Learning

Several theoretical models of organizational learning curves and related phenomena have been proposed (e.g., Dorroh, Gulledge, & Womer, 1994; Levy, 1965; Muth, 1986; Roberts, 1983). Muth (1986) provided an excellent review of these models and developed a new one. Muth (1986) generated the power law relationship between unit cost and experience [see Eq. (1.1)]

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

Organizational Learning Defined

Although researchers once debated whether organizational learning should be defined as a change in cognitions or in behavior, that debate has declined (Easterby- Smith, Crossan, & Nicolini, 2000). Most researchers agree with defining organiza- tional learning as a change in the organization’s knowledge that occurs as a function of experience (e.g., Fiol & Lyles,

A Theoretical Framework of Organization Learning

Figure 2.1 depicts a framework for analyzing organizational learning (Argote & Miron-Spektor, 2011). The figure portrays an ongoing cycle through which task performance experience is converted into knowledge through organizational learn- ing processes. Task performance experience interacts with the context to create knowledge. The knowledge flows out of the organization into the environment and

The nature of Organizational Experience

Because various types of experience can affect organizational learning processes and outcomes differently, researchers have characterized experience at a fine-grained level along various dimensions (Argote, McEvily, & Reagans, 2003). The most fundamen- tal dimension of experience is whether it is acquired directly by the focal organiza- tional unit or indirectly from other units (Argote,

The Organizational Context of Organization Learning

As noted previously, Argote and Miron-Spektor (2011) developed a conception of the organizational context that includes latent and active components. The latent or background context affects learning through its effects on the active components of members, tasks, and tools. The background context determines the organization’s task and the tools available to perform its task.

Organizational Learning Processes

Organizational learning processes are represented by the curved arrows in Fig. 2.1. When knowledge is created from a unit’s own direct experience, the learning sub- process is knowledge creation. When knowledge is developed from the experience of another unit, the learning subprocess is knowledge transfer. Thus, the curved arrow at the bottom of the

Knowledge from Organization Learning

Knowledge is the outcome of learning. Knowledge can manifest itself in changes in cognitions or behavior. The knowledge can be explicit or tacit and difficult-to- articulate. The knowledge includes both knowledge in the sense of a stock and knowing in the sense of a process (Cook & Brown, 1999; Orlikowski, 2002). Knowledge can be

Organizational Knowledge Depreciation

Does knowledge acquired through learning by doing persist through time or does it decay or depreciate? The classic learning curve model described in Chap. 1, which uses cumulative output as the measure of experience, assumes that knowledge acquired through learning persists indefinitely through time. More recent research indicates, however, that this characterization might not

A Case Example of Organizational Forgetting

As noted previously, analyses of organizational learning that use cumulative output as the measure of organizational experience have been found at times to contain large errors. The L-1011 TriStar produced by Lockheed throughout the 1970s and early 1980s is an example of a production program for which predictions based on the classic learning curve

Empirical Evidence of Organizational Forgetting

1. The Shipyard Study Our first empirical study of knowledge depreciation was based on data from the construction of the Liberty Ship during World War II (Fisher, 1949). We learned about these data from Rapping’s (1965) study, in which he found evidence of learn- ing in the shipyards. Rapping’s study provided particularly compelling evidence

Depreciation Rates Vary in Organizational Forgetting

Because the extent to which knowledge depreciated varied across the contexts we have studied, these studies provide grist to develop hypotheses about factors affecting the rate of depreciation in organizations. By far the most rapid depre- ciation was found in the fast food study. One important way in which the fast food franchises differed

Implications of Organizational Forgetting for Practice

The results on knowledge depreciation have important implications for both opera- tional and strategic decisions in organizations. On the operational side, depreciation has important ramifications for forecasting, planning, and scheduling. If knowledge depre- ciates, forecasts based on the conventional learning curve will systematically overesti- mate future productivity. The gap between an organization’s actual and