A Knowledge-Based Model For The Analysis Of Manufacturing Problems

This paper proposes a model to analyze manufacturing problems according to a knowledge management perspective. The analysis is based on the main cognitive processes involved in a problem solving process. The considered processes are knowledge generation, memory, transfer and codification. Each of them can be assessed by one or more variables, such as uncertainty, space-dependence, time-dependence, knowledge codification level. Given a specific manufacturing problem, the model allows to analyze possible actions of organizational improvement by analyzing the problem cognitive characteristics, and to identify suitable information technologies aimed to support problem solving. Introduction Knowledge management has gained in the last years a more and more crucial role in competition. In fact, knowledge is largely recognized as a fundamental asset to provide stable competitive advantages (Pralahad and Hamel, 1990; Nonaka and Takeuchi, 1995). For example, in the industries characterized by frequent technological changes, it is critical the ability of developing new knowledge and competencies (Bohn, 1994). The enlargement of the product functions can be also interpreted as the enlargement of the technological knowledge and of the expertise incorporated in the product. This often requires the integration of competencies from different departments through an effective product development process (Fine and Whitney, 1996). Similarly, for companies competing on the quality of their customer services, the competitive advantage largely depends on the knowledge about the customers’ needs and on the ability to exploit it (Reicheld, 1996). Also the competitiveness of some firm networks (such as the virtual organizations) is often related to synergies among different knowledge assets rather than to cost reduction (Chesbrough and Teece, 1996). Moreover, the effectiveness of downsizing policies is often related to the ability of avoiding the erosion of the firm core competencies. Similarly, policies of personnel turnover and job rotation can expose the firm to the risk of weakening the core competencies embedded in the organizational routines rather than in individuals, thus reducing the effectiveness of organizational interfaces and communication channels (Fujimoto, 1994). In this scenario, it becomes clear the importance of every managerial action directed to support companies in the knowledge management processes. Among the different streams of a dynamic and still diverse literature, that overlaps to some extent other well-established fields of studies, such as the learning organization, decision support ∗ Corresponding author: Michele Gorgoglione, DIMEG Politecnico di Bari, Viale Japigia, 182 – 70126 Bari (Italy). Tel. +39 080 5962765; fax +39 080 5962788; e-mail: m.gorgoglione@poliba.it Proceedings of the Twelfth Annual Conference of the Production and Operations Management Society, POM-2001, march 30-April 2,2001, Orlando Fl. systems, business process reengineering, three main directions can be highlighted, at least for the aims of this research. The first concerns the analysis of the knowledge nature, i.e. the shapes in which it can be recognized and utilized in the organization. There exist several analyses that adopt different perspectives and lead to different classifications. For instance, Nonaka (1991) stressed the difference between tacit knowledge, usually embedded in individuals or in procedures and informal organizational relationships, and explicit knowledge, that one can find in written documents or electronic files. Bohn (1994) developed a knowledge taxonomy related to the ability of problem solving and to the nature of the information used. He distinguished eight levels of knowledge, from the awareness of a problem, to the ability of locally controlling a phenomenon, up to the capability of producing formal and general models. Faulkner (1994) analyzed the innovation processes, by reviewing the work of scholars committed to clarify the difference between scientific knowledge and engineering knowledge. She came to define five categories of knowledge, each characterized by two extreme types: tacit and explicit, observable and non observable, simple and complex, elementary and systemic, context-specific and contextfree. The second research stream concerns the study of the knowledge management processes. For instance, Nonaka (1994), according to his model of knowledge nature, defined four basic processes: socialization, externalization, combination, internalization. Coombs and Hull (1998), moving the unit of analysis from knowledge to knowledge management practices, identified the processes of knowledge generation, transfer and use, as the most important and analyzed in the literature. The same authors distinguished also some additional processes, such as identification, extraction from memory, codification, validation, contextualization. Davenport et al., (1998), by analyzing some successful cases of organizational reengineering aimed to improve knowledge management, stressed four main managerial goals: developing organizational memories, sharing knowledge, improving information access, making culture and environment more suitable for knowledge management. Finally, Ruggles (1997) classified three main categories of knowledge management processes: knowledge generation, codification and transfer. The third research stream concerns the role of Information and Communication Technologies (ICTs), and more in general of Information Systems, in the new perspective of knowledge management (Hansen et al., 1999). Some of the most interesting debates, such as the change of managerial policies due to the adoption of information technologies or their organizational impact, which was already popular in the ‘80s, are today discussed under a new light. Despite the large variety of the existing technologies, it is possible to draw up some general observations. First, the development of technologies for managing knowledge is strictly related to the research on knowledge management processes and practices, previously mentioned. For instance, some technologies are oriented to build effective organizational memories (Abecker et. al, 1998), others support communication and information sharing within organizations (O’Leary, 1998), others aim to improve the access to the information stored (Davenport et al., 1998), while more difficult attempts have been done to support the knowledge creation process (Ruggles, 1997). Second, the support to management activities, which in the past was strictly related to effectiveness and efficiency of data gathering and processing, is today much more centered to cognitive processes, i.e. to the ability of supporting the typically human processes of giving meaning to information and using information to solve problems. It can be stressed that the research in the knowledge management field considers the role of ICTs quite different than in the past. For instance, the early aim of Artificial Intelligence (AI) was that of replacing the human