Knowledge Management Critical Success Factors

Section: Strategy
Topic: Knowledge Management
Author(s): Murray E. Jennex, Iryna Zakharova, San Diego State University
Posted: June 29, 2005
Hits: 28447

Перші дві статті з даної серії були присвячені Управлінню знаннями (An Introduction to Knowledge and Knowledge Management) та Системам Управління знаннями (Knowledge Management Systems). Але що саме є запорукою успіху УЗ чи що стоїть за побудовою успішної СУЗ? Факторами успіху УЗ та СУЗ є фактори, що сприяють чи допомагають користувачам використовувати СУЗ для ефективного виконання функцій УЗ. У даній статті проаналізовано наукову літературу для ідентифікації цих ключових факторів успіху. Для виявлення їх сутності, аналіз було зроблено на основі основних визначень та концепцій з подальшим їх поєднанням для формулювання вже загальних ключових факторів успіху. Хотілося б також зазначити, що всі наведені фактори є ключовими.
The Key (Jackson Pollock)
"The Key" (1946)
by Jackson Pollock,
Art Institue of Chicago

Introduction

The first two articles in this series discussed Knowledge Management (KM) and Knowledge Management Systems (KMS). Summarizing these two articles we concluded that KM is the retention of experience, knowledge, information, and data about events in an organization that are then applied to future events to support decision-making. The KMS is the system an organization builds to implement KM by supporting the capture, storage, search, retrieval, and application of knowledge. This includes the management support, processes, and IT applications and components necessary to support these activities. A holistic, Churchmanian (1979) view of KM and the KMS reveals these two concepts to be closely linked. So closely linked that it is unlikely we can have one without the other or that one can succeed without the other being successful. This leads to the topic for this article, what factors influence KM and KMS success.

What does it take to be successful in KM or to build a successful KMS? Knowing the critical success factors is useful as it provides researchers and practitioners with the basic requirements for implementing a successful KM initiative and building a successful KMS. However, what is KM or KMS success? The literature does not provide a consensus on this although two concepts of success can be identified. The first considers KM or KMS a success if knowledge use through the initiative or system improves the organization's ability to compete. The second considers KM or KMS a success if the KM processes implemented through the KMS are implemented effectively. Both success concepts imply that the KMS has to be used. Therefore, KM and KMS success factors are those factors that encourage or help users to use the KMS to effectively perform KM functions.

This paper uses a literature review to identify these critical success factors. Studies looking at KM, KMS, OM and OMS/OMIS were reviewed and the critical success factors extracted. The first article presented the KM/OM/OL Model (Jennex and Olfman, 2002) which shows that KM and OM are essentially the same with the difference being the players. End users tend to do KM where KM is concerned with the identification and capture of key knowledge. Information Systems, IS, personnel tend to be concerned with OM where OM is the storage, search, retrieval, manipulation, and presentation of knowledge. KMS and OMS are the systems built to implement KM and OM and are essentially systems designed to manage organizational knowledge. Organizational Learning (OL) is the result of the use of this organizational knowledge and is therefore a manifestation of KM success.

The literature review identified many critical success factors that are summarized below. To make sense of these factors they were analyzed for key words and concepts and combined into generic critical success factors. Definitions for the generic critical success factors were generated by combining and simplifying the concepts included in the base success factors. The generic critical success factors were rank ordered based on the number of articles the base success factors appeared in. It is understood that using the number of studies mentioning a critical success factor is an imperfect ranking methodology. We justify the resulting ordering by suggesting that given a lack of detailed, quantitative studies on critical success factors that can be used to statistically indicate significance of the factor, then the more studies reporting the factor the more influential the factor is over a broader spectrum of KM/KMS projects justifying the factor's listing at or near the top. However, we remind the reader that all the listed generic critical success factors are critical and should not be ignored just because fewer researchers observed it as critical.

Critical Success Factors

A successful KMS should perform the functions of knowledge creation, storage/retrieval, transfer, and application well. However, other factors can influence KMS success. Mandviwalla, et al. (1998) summarized the state of the research and described several strategy issues affecting the design of a KMS. These include the focus of the KMS (who are the users), the quantity of knowledge to be captured and in what formats; who filters what is captured, and what reliance and/or limitations are placed on the use of individual memories. Additional technical issues affecting KMS design include knowledge storage/repository considerations, how information and knowledge is organized so that it can be searched and linked to appropriate events and use, and processes for integrating the various repositories and for re-integrating information and knowledge extracted from specific events. Some management issues include how long the knowledge is useful, access locations as users rarely access the KMS from a single location (leads to network needs and security concerns), and the work activities and processes that utilize the KMS.

Ackerman (1994) studied six organizations that had implemented his Answer Garden system. Answer Garden is a system designed to grow organizational memory in the context of help-desk situations. Only one organization had a successful implementation because expectations of the capabilities of the system exceeded the actual capabilities. Ackerman and Mandel (1996) found that a smaller task-based system was more effective on the sub-organization level because of its narrower expectations. They refer to this narrower system as “memory in the small”.

Jennex and Olfman (2000) studied three KM projects to identify design recommendations for building a successful KMS. These recommendations include:

  • Develop a good technical infrastructure by using a common network structure, adding KM skills to the technology support skill set, using high end PCs; integrated databases; and standardizing hardware and software across the organization.
  • Incorporate the KMS into everyday processes and IS by automating knowledge capture.
  • Have a enterprise wide knowledge structure
  • Have Senior Management support
  • Allocate maintenance resources for OMS.
  • Train users on use and content of the OMS.
  • Create and implement a KM Strategy/Process for identifying/maintaining the knowledge base.
  • Expand system models/life cycles to include the KMS and assess system/process changes for impact on the KMS.
  • Design security into the KMS.
  • Build motivation and commitment by incorporating KMS usage into personnel evaluation processes; implementing KMS use/satisfaction metrics; and identifying organizational culture concerns that could inhibit KMS usage.

Additionally, Jennex and Olfman (2002) performed a longitudinal study of KM on one of these organizations and found that new members of an organization do not use the computerized KMS due to a lack of context for understanding the knowledge and the KMS. They found that these users needed pointers to knowledge more than codified knowledge.

Jennex, Olfman, and Addo (2003) investigated the need for having an organizational KM strategy to ensure that knowledge benefits gained from projects are captured for use in the organization by surveying Year 2000 (Y2K) project leaders. They found that benefits from Y2K projects were not being captured because the parent organizations did not have a KM strategy/process. Their conclusion was that KM in projects can exist and can assist projects in utilizing knowledge during the project.

Davenport, et al. (1998) studied 31 projects in 24 companies. Eighteen projects were determined to be successful, five were considered failures, and eight were too new to be rated. Eight factors were identified that were common in successful KM projects. These factors are:

  • Senior management support
  • Clearly communicated KMS purpose/goals
  • Linkages to economic performance
  • Multiple channels for knowledge transfer
  • Motivational incentives for KM users
  • A knowledge friendly culture
  • A solid technical and organizational infrastructure
  • A standard, flexible knowledge structure.

Malhotra and Galletta (2003) identified the critical importance of user commitment and motivation through a survey study of users of a KMS being implemented in a health care organization. They found that using incentives did not guarantee a successful KMS. They created an instrument for measuring user commitment and motivation that is similar to Thompson, Higgins, and Howell's (1991) Perceived Benefit model but based on self-determination theory that uses the Perceived Locus of Causality.

Ginsberg and Kambil (1999) explored issues in the design and implementation of an effective KMS by building a KMS based on issues identified in the literature and then experimentally implementing the KMS in a field setting. They found knowledge representation, storage, search, retrieval, visualization, and quality control to be key technical issues and incentives to share and use knowledge to be the key organizational issues.

Alavi and Leidner (1999) surveyed executive participants in an executive development program with respect to what was needed for a successful KMS. They found organizational and cultural issues associated with user motivation to share and use knowledge to be the most significant. They also found it important to measure the benefits of the KMS and to have an integrated and integrative technology architecture that supports database, communication, and search and retrieval functions.

Holsapple and Joshi (2000) investigated factors that influenced the management of knowledge in organizations through the use of a Delphi panel consisting of 31 recognized KM researchers and practitioners. They found leadership and top management commitment/support to be crucial. Resource influences such as having sufficient financial support, skill level of employees, and identified knowledge sources are also important.

Koskinen (2001) investigated tacit knowledge as a promoter of success in technology firms by studying ten small technology firms. Key to the success of a KMS was the ability to identify, capture, and transfer critical tacit knowledge. A significant finding was that new members take a long time to learn critical tacit knowledge and a good KMS facilitates the transference of this tacit knowledge to new members.

Barna (2003) studied six KM projects with various levels of success (three were successful, two failed, and one was an initial failure turned into a success) and identified two groups of factors important to a successful KMS. The main managerial success factor is creating and promoting a culture of knowledge sharing within the organization by articulating a corporate KM vision, rewarding employees for knowledge sharing, creating communities of practice, and creating of a “best practices” repository. Other managerial success factors include obtaining senior management support, creating a learning organization, providing KMS training, and precisely defining KMS project objectives

Design/construction success factors include approaching the problem as an organizational problem and not a technical one, creating a standard knowledge submission process, methodologies and processes for the codification, documentation, and storage of knowledge, processes for capturing and converting individual tacit knowledge into organizational knowledge. Also create relevant and easily accessible knowledge-sharing databases and knowledge maps.

Cross and Baird (2000) proposes that KM would not improve business performance simply by using technology to capture and share the lessons of experience. It was postulated that for KM to improve business performance it had to increase organizational learning through the creation of organizational memory. To investigate this 22 projects were examined. The conclusion was that improving organizational learning improved the likelihood of KM success. Factors that improved organizational learning include:

  • Supporting personal relationships between experts and knowledge users
  • Providing incentives to motivate users to learn from experience and to use the KMS
  • Providing distributed databases to store knowledge and pointers to knowledge
  • Providing work processes for users to convert personal experience into organizational learning
  • Providing direction to what knowledge the organization needs to capture and learn from.

Sage and Rouse (1999) reflected on the history of innovation and technology and identified the following issues:

  • Modeling processes to identify knowledge needs and sources
  • KMS strategy for the identification of knowledge to capture and use and who will use it
  • Provide incentives and motivation to use the KMS
  • Infrastructure for capturing, searching, retrieving, and displaying knowledge
  • An understood enterprise knowledge structure
  • Clear goals for the KMS
  • Measuring and evaluating the effectiveness of the KMS

Yu, et al. (2004) explored the linkage of organizational culture to knowledge management success. They found that KM drivers such as a learning culture, knowledge sharing intention, KMS quality, rewards, and KM team activity significantly affected KM performance. These conclusions were reached through a survey of 66 Korean firms.

Discussion

These studies provide several success factors. To summarize them they have been reviewed and paraphrased into a set of ranked success factors were the ranking is based on the number of sources citing them. Table 1 lists the final set of success factors in their rank order. Additionally, success factors SF1 through SF4 are considered the key success factors as they were mentioned by at least half of the success factor studies.

Table 1. KMS Success Factor Summary

ID

Success Factor

Source

SF1

Integrated Technical Infrastructure including networks, databases/repositories, computers, software, KMS experts

Alavi and Leidner (1999), Barna (2002), Cross and Baird (2000), Davenport, et al. (1998), Ginsberg and Kambil (1999), Jennex and Olfman (2000), Mandviwalla, et al. (1998), Sage and Rouse (1999), Yu, et al. (2004)

SF2

A Knowledge Strategy that identifies users, user experience level needs, sources, processes, storage strategy, knowledge and links to knowledge for the KMS.

Barna (2002), Ginsberg and Kambil (1999), Holsapple and Joshi (2000), Jennex, Olfman, and Addo (2003), Koskinen (2001), Mandviwalla, et al. (1998), Sage and Rouse (1999), Yu, et al. (2004)

SF3

A common enterprise wide knowledge structure that is clearly articulated and easily understood

Barna (2002), Cross and Baird (2000), Davenport, et al. (1998), Ginsberg and Kambil (1999), Jennex and Olfman (2000), Mandviwalla, et al. (1998), Sage and Rouse (1999)

SF4

Motivation and Commitment of users including incentives and training

Alavi and Leidner (1999), Barna (2002), Cross and Baird (2000), Davenport, et al. (1998), Ginsberg and Kambil (1999), Jennex and Olfman (2000), Malhotra and Galletta (2003), Yu, et al. (2004)

SF5

An organizational culture that supports learning and the sharing and use of knowledge

Alavi and Leidner (1999), Barna (2002), Davenport, et al. (1998), Jennex and Olfman (2000), Sage and Rouse (1999), Yu, et al. (2004)

SF6

Senior Management support including allocation of resources, leadership, and providing training

Barna (2002), Davenport, et al. (1998), Holsapple and Joshi (2000), Jennex and Olfman (2000), Yu, et al. (2004)

SF7

Measures are established to assess the impacts of the KMS and the use of knowledge as well as verifying that the right knowledge is being captured

Alavi and Leidner (1999), Davenport, et al. (1998), Jennex and Olfman (2000), Sage and Rouse (1999)

SF8

There is a clear goal and purpose for the KMS

Ackerman (1994), Barna (2002), Davenport, et al. (1998), Cross and Baird (2000)

SF9

Learning Organization

Barna (2002), Cross and Baird (2000), Sage and Rouse (1999), Yu, et al. (2004)

SF10

The search, retrieval, and visualization functions of the KMS support easy knowledge use

Alavi and Leidner (1999), Ginsberg and Kambil (1999), Mandviwalla, et al. (1998)

SF11

Work processes are designed that incorporate knowledge capture and use

Barna (2002), Cross and Baird (2000), Jennex and Olfman (2000)

SF12

Security/protection of knowledge

Jennex and Olfman (2000), Sage and Rouse (1999)

Future Research Trends

Many of the above critical success factors were identified through qualitative research with their importance established through bibliographical analysis. Future research needs to consolidate these factors into a single critical success factor model. To be useful the generated critical success factor model needs to be quantitatively validated against a variety of organizations. This will improve the validity and general application of the model.

Conclusions

Many studies have been performed that have identified KM/KMS critical success factors. The summary of Table 1 is a useful summary of success factors and their importance and is useful for researchers and practitioners. However, more research into KM and KMS success is needed. The success factors presented in this paper were generated from a literature survey. The studies used for this literature survey utilized a variety of methods including surveys, case studies, Delphi studies, and experimentation. A total of 78 projects or organizations were investigated using case studies and approximately 100 organizations were surveyed. Overall, in addition to the case studies mentioned, four surveys were administered and one Delphi study and experiment were performed. However, this isn't sufficient research completed to definitively state all KM/KMS critical success factors have been identified and their importance determined. Only a few of the source analyses were able to conduct any kind of statistical analysis or hypothesis testing leaving a qualitative analysis basis for most of these success factors. This leaves an opportunity for researchers.

REFERNCES

  1. Ackerman, M. (1994). Definitional and Contextual Issues in Organizational and Group Memories. Proceedings of the Twenty-Seventh Annual Hawaii International Conference on System Sciences, IEEE Computer Society Press, 191-200.
  2. Ackerman, M. and Mandel, E. (1996). Memory In the Small: An Application to Provide Task-Based Organizational Memory for a Scientific Community. Proceedings of the Twenty-Ninth Annual Hawaii International Conference on System Sciences, IEEE Computer Society Press, 323-332.
  3. Alavi, M. and Leidner, D.E. (1999). Knowledge Management Systems: Emerging Views and Practices from the Field. 32nd Hawaii International Conference on System Sciences, IEEE Computer Society.
  4. Alavi, M. and Leidner, D.E. (2001). Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly, 25(1), 107-136.
  5. Barna, Z. (2003). Knowledge Management: A Critical E-Business Strategic Factor. Unpublished Masters Thesis, San Diego State University.
  6. Churchman, C. W. (1979) The Systems Approach (revised and updated) New York: Dell Publishing. Cross, R. and Baird, L. (2000). Technology Is Not Enough: Improving Performance by Building Organizational Memory. Sloan Management Review, 41(3), 41-54.
  7. Davenport, T.H., DeLong, D.W., and Beers, M.C. (1998). Successful Knowledge Management Projects. Sloan Management Review, 39(2), 43-57.
  8. Ginsberg, M. and Kambil, A. (1999). Annotate: A Web-based Knowledge Management Support System for Document Collections. 32nd Hawaii International Conference on System Sciences, IEEE Computer Society Press.
  9. Holsapple, C. W., and Joshi, K.D. (2000). An Investigation of Factors that Influence the Management of Knowledge in Organizations. Journal of Strategic Information Systems, 9, 235-261.
  10. Jennex, M.E. and Olfman, L. (2000). Development Recommendations for Knowledge Management/ Organizational Memory Systems. Information Systems Development Conference 2000.
  11. Jennex, M.E. and Olfman, L. (2002). Organizational Memory/Knowledge Effects on Productivity, A Longitudinal Study. 35th Hawaii International Conference on System Sciences, HICSS35, IEEE Computer Society.
  12. Jennex, M.E., Olfman, L. and Addo, T.B.A. (2003). The Need for an Organizational Knowledge Management Strategy. 36th Hawaii International Conference on System Sciences, HICSS36, IEEE Computer Society.
  13. Koskinen, K.U. (2001). Tacit Knowledge as a Promoter of Success in Technology Firms. 34th Hawaii International Conference on System Sciences, IEEE Computer Society.
  14. Malhotra, Y. and Galletta, D. (2003). Role of Commitment and Motivation as Antecedents of Knowledge Management Systems Implementation. 36th Hawaii International Conference on System Sciences, IEEE Computer Society.
  15. Mandviwalla, M., Eulgem, S., Mould, C., and Rao, S.V. (1998). Organizational Memory Systems Design. Unpublished Working Paper for the Task Force on Organizational Memory, Burstein, F., Huber, G., Mandviwalla, M., Morrison, J., and Olfman, L. (eds.) Presented at the 31st Annual Hawaii International Conference on System Sciences.
  16. Sage, A.P. and Rouse, W.B. (1999). Information Systems Frontiers in Knowledge Management. Information Systems Frontiers, 1(3), 205-219.
  17. Thompson, R.L., Higgins, C.A., and Howell, J.M. (1991). Personal Computing: Toward a Conceptual Model of Utilization. MIS Quarterly, 15(1), 125-143.
  18. Yu, S-H, Kim, Y-G, and Kim, M-Y, (2004). Linking Organizational Knowledge Management Drivers to Knowledge Management Performance: An Exploratory Study. 37th Hawaii International Conference on System Sciences, HICSS36, IEEE Computer Society.



COMMENTS

vinko, vinko@ukrsd.com.ua
Может я чего-то не понимаю, но какой смысл помещать подобное без перевода (переведённый - со ссылкой на оригинал был-бы гораздо полезен для посетителей)
16 23:54:47.04.2007
Reply

Sergey, sergey.kadulin@hp.com
А почему-бы и нет? Переведешь - глядишь, и английскому научишься, а заодно и книжки интересные (непереведенные) можно в оригинале прочитать... Да осилит дорогу идущий!
19 00:13:12.04.2007
Reply

Taras, k_tomass@mail.ru
... Because there are some managers who`ve got their degree in UK Universities ... stupid question Vinko
15 00:34:21.11.2007
Reply

Jonecir, jonecir@gmail.com
I'm doing some research on KMS and OM. Many articles/books I've read cites The Answer Garden system. Does such system still exists? If so, where can I see it?
14 17:23:16.04.2011
Reply


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