(Rosenberg, 1982;Dutton and Thomas, 1985). These problems, in turn, require adaptation of the technologies already in use.A close understanding of the process of adaptation is critical for several reasons. First, users' adaptations to technologies-in-use often help to shape funher development and research activities (von Hippel. 1988;Dutton and Thomas, 1985). Second, the operating efficiency ultimately achieved with a new technology depends heavily on users' modifications (Enos, 1958;Hollander, 1965;Dutton and Thomas. 1984). Third, modifications affect not just the technologyin-use, but also its physical and organizational context (Leonard-Banon, 1988 (1983) states that when organizations try to rush the introduction process, they fail to identify and correct problems that later hamper productive use of the technology. Thus, "too-rapid implementation of the innovation ... can lead to disastrous results" (Rogers, 1983:364). Similarly, Hughes (1971:152) maintains that "trying to force the pace" of adaptation is counterproductive, while Hage and Aiken (1970:106) suggest that "the longer the elite allow [the] period of tnal and error to continue, the greater the chances of the new program achieving its intended objectives." Finally, Imai (1986) (Kiesler and Sproull, 1982;Starbuck, 1989). Groups in organizations also develop tendencies toward routine behaviors. Over time, they become increasingly unlikely to recognize and respond to new kinds of problems (Kelley and Thibaut, 1954;Katz, 1982;Hackman, 1990). Even research teams have been shown to be reluctant to alter a given technical approach once it has been selected, and the longer the approach has been used, the greater their rigidity (Allen, 1966).At the individual level, research suggests that people's arousal, attention, and motivation to engage in effortful problem solving is not constant over time. Specifically, active problem solving and information processing appear to drop sharply as soon as tasks become familiar or manageable (Langer and Imber, 1979;Kruglanski and Freund, 1983). With increasing exposure, observers tend to "chunk" activities into larger units that convey less information than fine-grained observauons, although a sudden surprise can sometimes reverse the process (Newtson, 1973; Louis and Sutton, 1991). Familiarity also breeds rounnized response patterns; once activities are well entrenched, even superficial resemblance to a known stimulus is sufficient to tngger a familiar response (Luchins, 1942).One of the few scholars to have considered the implications of these behavioral tendencies for technological adaptation is Weick (1990). Following Winner (1986), Weick (1990:21) suggests that "the point at which technology is introduced [may be) the point at which it is most susceptible to influence." Weick argues that "beginnings are of special imponance ... because they constrain what is learned about the technology and how fast it is learned " (1990:21-22 We deliberately sought vanety in the settings studied, the technologies...
This paper explores the nature of adaptive learning around new technology in organizations. To understand this issue, we examine the process of problem solving involving new production equipment during early factory use. We find that adaptation is a situated process, in that different organizational settings (1) contain different kinds of clues about the underlying issues, (2) offer different resources for generating and analyzing information, and (3) evoke different assumptions on the part of problem solvers. Consequently, actors frequently must move in an alternating fashion between different organizational settings before they can identify the causal underpinnings of a problem and develop a suitable solution. These findings suggest that traditional, decontextualized theories of adaptive learning and of collaboration could be improved by taking into account that learning occurs through people interacting in context—or, more specifically, in multiple contexts. Learning is often enhanced not just by bringing people together, but by moving them around to confront different sorts of clues, gather different kinds of data, use different kinds of tools, and experience different pressures relevant to a given problem. We discuss both managerial and theoretical implications of these findings.
The costs of producing goods and services has been shown to decline over time as a result of "learning by doing." In this paper we explore how learning by doing is done at the micro level via empirical study of a sample of problems affecting two novel process machines. These problems were created and/or identified by "doing" in the factories where the machines were used. Analysis shows two forms of learning by doing. The first enables the identification of problems through field use, and the second involves the creation of problems and related needs for improvement by problem solving in the field.Examination of the role of doing in these two types of learning by doing allows one to understand why it would be very difficult to eliminate doing and still learn the same (important) things. It also suggests that, typically, one can't "get it right the first time" when introducing a new product or process to the field, and that it would be valuable to adapt the innovation process accordingly.
died in November of 2000, at the age of 36, after battling a long illness. This paper is a testimony to Nancy's dedication, creativity, extraordinary colleagueship, and enthusiasm for her emerging career. Nancy was a gifted scholar whose love of learning shone in all her work. She brought energy, vision, and abundant talent to all that she did. She was an inspiring colleague who brought not just good ideas, but also the care and commitment to make those ideas happen. Nancy always contributed more than her share to projects, and she taught us all a good deal about the meaning of colleagueship and the importance of follow-through. As a friend, Nancy was unwavering, caring, thoughtful, and generous. She had a knack for reaching out to others and for providing just the kind words or warm gesture they needed. We feel extremely fortunate to have known Nancy as a colleague, a friend, a student, and a teacher.
This paper examines the effectiveness of organizational problem solving in response to technological change in the production process. First, the paper measures the degree of uncertainty associated with a given technological change by examining (1) the novelty of specific new features and functions, and (2) the required departure from established operating assumptions and organizational relationships. Second, the paper identifies three modes of problem solving that organizations use in dealing with technological change: modification prior to implementation (preparatory search), joint work with external technical experts during production start-up (joint search), and integration of engineering and manufacturing functions engaged in start-up (functional overlap). The effectiveness of these approaches is then tested on a sample of 48 new process introductions undertaken in eight plants by a leading global producer of precision metal components. Results indicate that the measured characteristics of technological change are significant predictors of the difficulties encountered in introducing new process technology. Findings also suggest that intensive problem solving efforts can significantly improve change outcomes, both shortening the period of disruption experienced and increasing the operating gains achieved. In addition, there was some evidence that the three organizational problem solving activities discussed here are not equally effective for responding to all types of process change. Specifically, the higher the level of technical novelty involved, the less useful was overlap between engineering and manufacturing functions. This challenges the general prescription that cross-functional team involvement in major technical projects always should be maximized, regardless of the nature of the change involved.
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