Academic journal article Research-Technology Management

Knowledge Management in Research and Development

Academic journal article Research-Technology Management

Knowledge Management in Research and Development

Article excerpt

A study of knowledge management practices in 19 leading companies yields a model for knowledge flow in the R&D process, aspects of KM unique to R&D, and a catalog of "better practices" that R&D leaders are putting to work.

In a turbulent and rapidly changing world, every organization faces the challenge of how to best manage its knowledge assets to generate value for the marketplace and obtain competitive advantage. Such advantage derives from special capabilities that are rare, valuable, nonsubstitutable, and costly to imitate (1). Historically, the focus was on capabilities involving tangible assets; now, knowledge is widely recognized as the source for competitive advantage, with the tangible assets representing the physical manifestation of but a fraction of this knowledge (2,3). As companies scramble to develop strategies for more proactively and strategically managing their knowledge, the field of KM receives increasing attention from trade organizations and academic journals.

This special report is the result of work by Industrial Research Institute member company representatives to better understand KM and specifically its application to Research and Development (see "How the Study Was Conducted," p. 30). Although many of the underlying assumptions of KM are not new, the formal study and application of KM in R&D organizations is a relatively young discipline. The goal of the study was threefold:

* Identify a model for knowledge flow in the R&D process that could be a visual point of contact for discussions around the key issues R&D managers face and the ways to manage knowledge flow.

* Highlight aspects of KM that are unique or especially important to the process of R&D.

* Catalog "better practices" that R&D managers use to facilitate knowledge flow and the knowledge creation process.

The findings from the research are reported in three Parts:

* Part I describes the flow of knowledge in R&D, develops a model that emphasizes some of the unique KM opportunities and requirements intrinsic to R&D, and shares high-level findings and conclusions.

* Part II details three specific enablers of culture, infrastructure and information technology (IT), summarizes specific KM application experiences related to these enablers, and identifies particular facilitators and inhibitors that affect KM performance.

* Part III suggests a holistic approach to implement KM in R&D. Six imperatives are presented with a recommendation that each be addressed for greater initial effectiveness and business impact.

I--Knowledge Flow and Facilitating Practices Cc. c. Chappelow, F. M. Ross Armbrecht, Jr., and S. R. Postle)

In this Part, we differentiate between Knowledge Management and knowledge flow in R&D. We discuss the nature of the flow of knowledge in terms of a model that emphasizes some of the unique KM opportunities and requirements intrinsic to R&D. We then share key findings from the research and conclude with our own learning from this work. To provide an appropriate content, it is necessary to first discuss our conception of the terms "Knowledge" and "Knowledge Management".

Knowledge and Its Management

Purists consider "knowledge" to be that which is within and between the minds of individuals and is tacitly possessed. Knowledge has the capability to add value to the organization (or individual). After knowledge has been explicitly captured (i.e., documented), the purist considers it to be a form of data or information (4). Data are better viewed as a "set of discrete, objective facts about events." Information is "data that makes a difference"; that is, it has a message that informs the recipient of potential value (5). This documented material--data and information--and knowledge are all vital to the R&D process.

In the course of our investigation, we came to understand that "managing" knowledge is not literally possible and, from an R&D perspective, we are really interested in facilitating knowledge flow. …

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