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Organizational Learning: Creating, Retaining, and Transferring Knowledge. - Review - book review

Administrative Science Quarterly, Sept, 2000 by Theresa K. Lant

Linda Argote. Boston: Kluwer Academic, 1999. 212 pp. $89.95.

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Research on organizational learning has been plagued by widely varying theoretical and operational definitions and a lack of empirical study. Argote's book goes a long way toward addressing these complaints. This book is a coherent and comprehensive treatment of the state of knowledge about organizational learning. Argote has purposely limited this book to a clearly articulated definition of organizational learning and a related set of questions. She focuses on contexts in which the outcomes of learning can be identified and evaluated and in which feedback on the efficacy of acquired knowledge is clear, timely, and understandable. Thus, the emphasis is on the learning of knowledge and practices that produce some measurable outcome, such as production quantity and quality. The book does not delve into issues such as the role of interpretation in organizational learning or the dynamics of learning processes across levels of analysis. There is some discussion of the micro underpinnings of organizational learning , in particular, the evidence around group dynamics and group structure in relation to knowledge creation and evaluation. Argote's stated goal for the book is to describe and integrate the results of research on "factors explaining organizational learning curves and the persistence and transfer of productivity gains acquired through experience" (p. xvi).

If you are looking for a book on the social construction of knowledge, then this is not the book for you. If you would like to read a cogent assessment of research on organizational learning that has been based on solid theorizing and empirical study, then look no further. This book is a well-crafted, readable overview of issues such as learning curves, organizational memory, and knowledge transfer. I outline the key issues that Argote explores and summarize the key findings that she reports. Many of these findings are based on an extensive body of empirical research conducted by Argote and her students and colleagues.

The section on learning curves goes beyond the standard application of learning curves to an understanding of how learning-curve patterns are influenced by factors such as organizational forgetting and knowledge transfer. The benefit of Argote's approach is twofold. First, she links the formal models and sophisticated empirical testing associated with the learning-curve literature with the broader literature on organizational learning. Second, she describes specific and quantitative ways of testing the degree of learning, forgetting, and transfer of knowledge within and across organizations. This is a significant contribution to a body of literature that has suffered from a lack of precise definition, measurement, and estimation (Miner and Mezias, 1996).

The findings reported suggest that organizational learning might explain the significant performance variations that are evident at the firm level of analysis. Three broad categories of organizational factors appear to influence the rate at which organizations learn and their subsequent productivity: proficiency of individuals performing both production and managerial activities, technology, and an organization's routines, structures, and means of coordination. To understand the role of learning and subsequent outcomes, Argote chooses to decompose the learning concept into three components of the learning process: knowledge acquisition, knowledge retention, and knowledge transfer. Research on these components is summarized throughout the book.

A critical contribution of Argote's elaboration of the learning curve concept is the finding that acquired knowledge does not stay at a constant level; it depreciates. Like water in a bathtub, knowledge tends to seep out of organizations. Several mechanisms cause this seepage. Knowledge can be lost when the physical substrate on which knowledge is encoded decays. Argote gives the example of old recordings of film or data stored on magnetic tape. Knowledge can also be lost through poor record keeping. Both of these causes of knowledge depreciation are significant, but solutions can be readily imagined, if not implemented.

A more complex cause of knowledge depreciation is personnel turnover. To the extent that knowledge is held by people rather than in technologies, structures, or routines, knowledge leaves when people leave. A significant body of research supports this conclusion. But turnover is a double-edged sword. Knowledge is not necessarily related to a constant level of productivity increases. Knowledge can become obsolete; changing technologies is a common cause. Under these circumstances, turnover can be beneficial for two reasons. First, individuals with obsolete knowledge may be resistant to new knowledge. Newcomers may be more willing to learn new skills. Second, newcomers may be more likely to have knowledge relevant to new technologies when hired. For instance, young newly hired employees are more likely than older workers to understand how to use the Internet. To determine the relationship between turnover and knowledge depreciation, an organization must have a good understanding of the degree to which knowledge is embedded in technologies, structures, and procedures versus people. The more knowledge resides in people, the higher the rate of depreciation due to turnover.

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Organizational Learning: Creating, Retaining, and Transferring Knowledge. - Review - book review

Administrative Science Quarterly, Sept, 2000 by Theresa K. Lant

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