Research on Relationship of Knowledge Management And Organizational Performance

Abstract. Establishing criteria for knowledge management (KM) is important, because criteria help to establish a basis for assessing the value and evaluating its results. More importantly, the criteria will tell us what the KM outcomes are and their relevance to organizational performance. The literature review has revealed that widely accepted criteria and performance measures have not been developed for KM. Delphi Technique and survey-based research using a questionnaire targeting KM professionals as respondents were aimed at establishing criteria for assessing KM success for different types of organizations. The results show what organizations consider important outcomes of a KM initiative. Contributions from this research effort should support government, nonprofit, and for-profit organizations in making decisions about KM initiatives and measuring KM efforts in terms of its relevance to the performance of organizations. Future research efforts can focus on developing these KM outcomes into detailed measures.

Key words: Knowledget; Management; style; Organizational Performanc

1. INTRODUCTION (HEADING 1)

Knowledge is recognized as a key economic resource, and obviously, organizations must possess the right knowledge in the desired form and context under all circumstances in order to be successful. Specifically, knowledge sharing and resultant knowledge creation are critical in order for organizations to gain competitiveness and to remain competitive. Knowledge is considered important for sustaining competitive advantage.

With the development of the modern study, the increasing gap between the book value and the market value of some business entities indicates the increasing importance of knowledge-based intangible assets and knowledge management (KM). However, the dimension of KM has not received adequate attention. Also, the KM concept is still understood as information management and is associated with technological solutions, such as intranet and databases.

Several organizations are attempting to use KM to improve organizational performance, but commonly accepted KM principles are yet to be developed. KM’s lack of focus and absence of commonly accepted KM principles are some of the gaps in this discipline. Among the commonly accepted KM principles or references that are missing are the criteria for measuring success associated with KM. In this chapter, a research effort is presented to address this knowledge gap from the practitioners’ point of view and leading to identifying expected outcomes of a KM initiative in organizations.

2. DEFINITIONS

Knowledge is derived from thinking and is a combination of information, experience, and insight. Deriving knowledge from information requires human judgment and is based on context and experience. Knowledge categories—tacit and explicit—can be found in different forms. But in my opinion, it should be understood that the primary focus of KM is to utilize information technology and tools, business processes, best practices, and culture to develop and share knowledge within an organization and to connect those who possess knowledge to those who need the knowledge. Ultimately, leveraging relevant knowledge assets to improve organizational performance is what knowledge management is all about.

3. BACKGROUND

KM and Organizational Performance

While many organizations have implemented knowledge management (KM) initiatives, it remains unclear the extent to which they are successful in delivering the anticipated outcomes, and why. Research studies show that it is difficult to assess return on investment of KM. Improving organizational performance by using a KM initiative is an investment decision, and we, therefore, must have an understanding of its outcomes. While discussing approaches to building KM systems (KMS), Jennex and Olfman contended that the measurement of a KMS is crucial to understanding how these systems should be developed and implemented. They cite several reasons for measuring success of a KMS, including three from Turban and Aronson: to provide a basis for valuation, to stimulate management’s focus on what is important, and to justify investments.

However, inherent intangible characteristics of knowledge assets make them difficult to measure. Unlike materials or equipment, the core competencies and distinctive abilities of employees are not listed on balance sheets. As a result, factors that contribute substantially to a firm’s success elude traditional means of quantification, thereby presenting significant challenges to KM performance measurement.

These research findings lead to the conclusion that KM results are difficult to measure and that commonly accepted outcomes of a KM initiative are not yet established. This research effort is aimed to address this knowledge gap in order to develop an understanding of the relevance of KM to organizational performance. This chapter uses a literature review to identify a number of KM outcomes at the organizational level that then are translated into KM criteria. Based on this literature review, a list of KM criteria and important research questions was established for the Delphi study. To support the Delphi findings, a survey consisting of the same list of criteria and questions was distributed. Based on these research findings, expected KM initiative outcomes from the practitioner’s point of view were established. Finally, limitations of the study and future research opportunities are discussed.

4. LITERATURE REVIEW

Research related to KM success can be classified into two focus areas: KM success factors and KM outcomes. KM success factors can be viewed as facilitating factors for a KM initiative. Though the main focus of this chapter is on outcomes of KM initiatives, a brief discussion on success factors is relevant for this study in order to understand the distinction between the two.

There have been efforts to identify organizational factors for successful KM initiatives. While discussing KMS frameworks, Jennex and Olfman (2004) recommend that developing a successful KMS would involve designing a technical infrastructure, incorporating KM into processes, developing a secured KMS and knowledge structure for the enterprise, gaining senior management support, and building motivational factors into the system.

A conference in London, Measuring Knowledge Value 2002, addressed the knowledge measurement issue from both macro and micro perspectives. The macro perspective focused on quantifying intangible assets to capture the value of human capital, competencies, customer relationships, employee collaborations, and so forth, which are not purely financial measures and emphasize the importance of intangible assets. The micro perspective addressed the issue of quantifying the impact of individual knowledge projects. While analyzing the 2002 London conference proceedings, Perkmann (2002) supported the idea of case studies and anecdotal evidence by illustrating that ROI can capture only a part of the project’s impact (efficiency and productivity concerns) and that projects always have unintended consequences or effects (competency development and learning), negative or positive, that cannot be captured easily in quantitative or financial terms. However, anecdotal evidence and case studies are context-specific artifacts that may not reflect overall reality and may not be commonly accepted. In addition, they do not meet some of the desired characteristics of measures, such as reliability, applicability, and transferability.

According to a benchmarking study by APQC, the most common reason for managing and sharing knowledge is the transfer of best or exemplary practices within the organization, followed by increasing employee capabilities and providing customer or market information.

Successful KM programs achieve competitive advantage, customer focus, employee relations and development, innovation, and lower costs. Though KM promotes development and application of knowledge to attain enterprise’s ultimate goal of profitability, the implicit purpose of KM is to empower knowledgeable individuals with intellectual tasks in order to promote learning.

Based on the previous discussions and several other references, 26 factors were identified to be included in the list of outcomes. All of them have direct references, not necessarily as outcomes but under different terms such as benefits, impact, focus, performance factors, metrics, results, strategies, and value. Table 2 presents a summary of literature review consisting of KM outcomes and important sources.

5. RESEARCH QUESTIONS

The main research objective is to establish the criteria for measuring KM success. Consequently, it led to understanding the relevance of KM to organizational performance. Since a criterion can be considered as a standard on which a judgment may be based, establishing criteria and using them to evaluate KM initiatives will lead to knowing expected outcomes of KM initiatives. Thus, the main research question is:

What should be the criteria for measuring KM success?

Though KM principles are similar, irrespective of the type of organization, criteria and consequent KM outcomes could be different for different types of organizations for two reasons. First, an organization’s reason to invest in a KM initiative could be business-specific and, thus, could be different. Second, this initiative is driven by what the organization’s goals and objectives are, and each type of an organization may have different objectives and goals.

Many research studies support the contention that KM initiatives should be aligned with organizational goals and objectives. A poll of executives from 80 large companies in the U.S., such as BP Amoco, Chemical Bank, Hewlett-Packard, and Kodak, indicated that 80% believed that managing knowledge of their organization should be an essential or important part of business strategy. Strategic goals and business requirements drive process requirements, which, in turn, determine knowledge requirements. Massey and Montaya-Weiss (2002) contend that KM initiatives will be effective when they are aligned with the performance goals and requirements of a business, its processes, and its people. Citing that KM is about creating synergy in organizations, Davenport and Probst (2001) contend that such action translates into aligning individual goals with organizational goals. In other words, aligning KM practices with organization goals is a desired way to implement a KM initiative. Thus, an extension of the main research question is: Are the criteria for measuring KM success different for different types of organizations? The second research question focuses on establishing the criteria or outcomes for different types of organizations.

6. RESEARCH METHODOLOGY

Literature review findings and research questions discussed in previous sections suggest that those who are well-versed in KM theory and practice can better address these issues. For this reason, this research effort uses the Delphi Technique with occasional use of in-depth interviewing and personal discussions. The Delphi Technique uses a group of experts to deliberate a research issue or a problem anonymously. The Delphi Technique does not involve face-to-face group discussion, and it does not have the disadvantages of conventional groups, because it provides anonymity and controlled feedback. However, the Delphi Technique has certain disadvantages. It is time consuming, and swiftness of the decision making process is controlled by participating individuals to some extent. As results are limited by the number of experts and the number of organizations they represent, the Delphi Technique research effort is supplemented by a survey questionnaire, which also helped to set up priority among the established criteria. The survey was aimed only at KM professionals for the same reasons the Delphi was chosen for this research effort.

7. LIMITATIONS OF THE STUDY

As mentioned earlier, the number of experts and the number of organizations they represent limits Delphi Technique results. The survey questionnaire is similar to a one-time case study in which all the respondents were asked to respond to the questionnaire only once.

Of the internal and external validity factors, only statistical regression and biases are relevant to the survey and the Delphi Technique. Others are relevant for controlled experimental studies. External validity factors are no threat to the research study. Statistical regression, which is concerned with selection of groups on the basis of their extreme scores, is part of the research design, as responses from KM professionals and experts are sought for this research and its findings are limited to KM initiatives only. Bias, which results in differential selection of respondents for the comparison groups, is not directly related to the current research, as there are no comparison groups. However, selection bias is a possibility for the Delphi Technique.

8. SUGGESTIONS FOR FUTURE

Research：Statistical analysis and research findings helped to identify the criteria for measuring KM efforts, which, in turn, can be described as desired outcomes. The research study also helped to identify new areas of interest for further research. Some of these gray areas and new areas of interest are as follows:

The most useful criteria identified through this research can be developed further into detailed measures of KM success, as discussed briefly in the previous section. The research questions—What are the detailed measures for enhanced collaboration within an organization? What are they for: improved communication and improved employee skills?—are required to be answered in this effort. The research effort would entail establishing detailed measures for each useful criterion, validating their relation to the criteria and validating their effectiveness through research.

Based on geographical location as well as industry type, the differences in KM criteria can be analyzed using multiple factors. The research questions—What are the differences in KM criteria based on geographical location? Are they industry specific?—will have to be addressed in a follow-up research effort. However, by using data similar to those obtained from this research, the differences in KM criteria can be examined for Europe and the U.S.

Relationships among all 26 criteria can be explored to establish associations and classifications among these criteria by factorial analysis. KM criteria and outcomes may be classified based on business results, market results, customer service, and internal performance.

9. Acknowledgement

The work is supported by “12th Five-Year ”Science and Technology Research Project of Jilin Province Department of Education(2012528).

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