Knowledge strategy planning: methodology and case

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Abstract

This study aims at suggesting an integrative methodology for planning knowledge management initiatives. First, four major underpinning assumptions which should be addressed in knowledge management are identified through literature reviews on strategic information systems planning and knowledge management. Based on these assumptions, we introduce a knowledge strategy planning methodology, called P2-KSP methodology. The P2-KSP methodology places its emphasis on improving organizational performance by identifying and leveraging knowledge directly related to business processes and performance. The methodology consists of five phases: business environment analysis, knowledge requirements analysis, knowledge management strategy establishment, knowledge management architecture design, and knowledge management implementation planning. After its detailed procedures and related features are explained, results of applying it to a large semiconductor manufacturer's knowledge management project are discussed.

Introduction

Facing a knowledge economy (Nonaka, 1994, Nonaka and Takeuchi, 1995) and knowledge-based competition (Drucker, 1993), an organization should be able to secure various types of knowledge assets and maximize their strategic value. To do this, many organizations began to reexamine and rearrange their business strategies, processes, information technologies, and organizational structures from a knowledge perspective (Davenport, Jarvenpaa, & Beers, 1996). Adoption and assimilation of the knowledge management paradigm requires the design and establishment of structures, processes, and technologies along with organizational knowledge resources (Lee & Kim, 2001).

Despite the active implementations of knowledge management projects, however, many organizations have failed to realize the expected benefits of knowledge management. First, they were not able to distinguish knowledge from information or data, ignoring the unique characteristics of knowledge and knowledge workers (Ruggles, 1998). Secondly, as Miles et al., 1998, Wiig et al., 1997 identified, they lacked the proper methodology for implementing knowledge management. In many cases, traditional methodologies for developing information systems or business consulting were applied in implementing knowledge management (Iivari et al., 2000, Management Review, 1999).

To overcome such problems, academics and practitioners introduced frameworks for embodying knowledge management effectively and comprehensively (Earl, 2001, Miles et al., 1998, Teece, 1998a, Teece, 1998b, Wiig, 1997). Based on such frameworks, this article introduces a methodology for planning and implementing knowledge management. The proposed methodology starts from identifying organizational knowledge requirements and leads to the architecture development for the related systems. To assess the applicability of the methodology, we applied it to the knowledge strategy planning process of a large, global company and discuss its results.

This article proceeds as follows. First, we review the literature on organizational knowledge and knowledge strategy planning. Then, underpinning assumptions for knowledge strategy planning are identified in contrast to the traditional information systems planning. This is followed by the detailed description of the performance-driven and process-based knowledge strategy planning (P2-KSP) methodology. Finally, results of applying the P2-KSP methodology to a real knowledge management project are discussed in terms of its usefulness and limitations.

Section snippets

A revised epistemological perspective

Organizational knowledge is created from individual experiences or learning in embedded routines, information-processing tasks, domain-specific problem-solving activities, or organization culture (Argyris and Schon, 1978, Bohn, 1994, Nass, 1994, Nelson and Winter, 1982, Nonaka, 1994, Spender, 1996). Polani (1966) classified organizational knowledge into tacit and explicit knowledge from an epistemological point of view. Although diverse types of knowledge have been defined from various

Definition and roles of knowledge strategy planning

While knowledge is recognized as a critical resource for sustained competitive advantages, implementation of knowledge management remains a main challenge to an organization (Davenport and Prusak, 1998, Demarest, 1997, Grant, 1996, Grant, 1997, Nonaka and Takeuchi, 1995, Teece, 1998a, Wiig, 1997) requiring vast amounts of organizational resources, diverse techniques, and related tools calling for a solid and deliberate plan from the beginning (Davenport, DeLong, & Beers, 1998).

In many cases,

Underpinning assumptions of the methodology

A knowledge strategy planning (KSP) methodology enables an organization to identify its core knowledge and to design the organizational infrastructures for managing it. The organizational infrastructure is a basis for supporting human, organizational, administrative, cultural, and technical aspects of knowledge management. To address issues identified in the previous section, our methodology is based on the following underpinning assumptions.

Application of the P2-KSP methodology: case discussion

To validate the usefulness of the P2-KSP methodology, we applied it to a large semiconductor manufacturer's knowledge strategy planning process. This application is essential to refine details of the methodology and to search for a clue as to the future direction of knowledge strategy planning.

Conclusion

As knowledge management becomes basic and imperative in the knowledge society, active research on knowledge management will appear on the academic and practical scene, developing the field of knowledge management past its embryonic status. However, it is still difficult to decide where to start and how to embody this new field. Up to now, many efforts for implementing knowledge management were almost the same as those for information management (Gold et al., 2001) since preexisting information

Young-Gul Kim is professor at the Graduate School of Management of the Korea Advanced Institute of Science and Technology in Seoul. He received his BS and MS degree in Industrial Engineering from the Seoul National University, Korea and PhD degree in MIS from the University of Minnesota. His active research areas are: Knowledge Management, IT Innovation, and Customer Relationship Management. His publications have appeared in varied journals such as Communications of the ACM, Journal of MIS,

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    Young-Gul Kim is professor at the Graduate School of Management of the Korea Advanced Institute of Science and Technology in Seoul. He received his BS and MS degree in Industrial Engineering from the Seoul National University, Korea and PhD degree in MIS from the University of Minnesota. His active research areas are: Knowledge Management, IT Innovation, and Customer Relationship Management. His publications have appeared in varied journals such as Communications of the ACM, Journal of MIS, Journal of Strategic Information Systems, Decision Support Systems, Information and Management, IEEE Transactions on Engineering Management, and others. Also, he presented several papers at ICIS, HICSS, and DSI conferences.

    Sung-Ho Yu is a PhD candidate at the Graduate School of Management of the Korea Advanced Institute of Science and Technology (KAIST) in Seoul. He received his BS and MS degree in Industrial Engineering from Pohang University of Science and Technology (POSTECH), Korea. His research areas are: Knowledge management and Management of information system. His publication has appeared in IE interfaces. He has also presented several papers at Asia Pacific DSI, ISEE and Korean KM Academic Symposiums.

    Jang-Hwan Lee is working for Samsung SDS Inc., which is the biggest system integration company in Korea. He received an MBA degree in MIS specification from the Graduate School of Business of the George Washington University in Washington, DC, US and a PhD degree in MIS form Korea Advanced Institute of Science and Technology (KAIST) in Seoul. His research areas are Knowledge Management, Knowledge Management Systems, and Management of Innovation. His publications have appeared in IE Interfaces and Expert Systems With Applications. He has also presented several papers at DSI, HICSS, and Korean KM Academic Symposiums.

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