Knowledge strategy in organizations: refining the model of Hansen, Nohria and Tierney

Abstract

We assessed the model of knowledge strategy and IT support proposed by Hansen, Nohria and Tierney. Their main argument is that, in order to enable effective use of knowledge, organizations should select an 80/20 knowledge strategy mix of codification and personalization with one of these strategies dominant. We examined the knowledge strategy emphasis (codification or personalization) in each of four case organizations. These organizations represented different combinations of the codification and personalization knowledge strategy mix. Our cases indicate some support for Hansen et al.'s main argument, but also highlight the need for refinements to their model. Based on our assessment, we conclude that the advice of Hansen et al. is useful for deciding upon an initial strategic direction and setting suitable priorities. We propose the following refinements to the model. First, organizations may find it necessary to evolve their knowledge strategy mix over time, augmenting the alternate strategy as a result of the intertwined nature of knowledge processes. Second, we propose two strategic pathways that organizations could adopt on their journey towards effective use of organizational knowledge. Lastly, we identify additional considerations for deciding upon a particular knowledge strategy direction.

Introduction

Many contemporary organizations view knowledge as one of their most important strategic assets. Accordingly, the choice of an effective knowledge strategy, and its implementation, are widely regarded as issues for the contemporary managerial agenda (Zack, 1999a, Earl, 2001). Tied to this are decisions about effective information technology (IT) infrastructure to support the chosen organizational knowledge management approach (Davenport and Prusak, 1998; Alavi and Leidner, 1999, Alavi and Leidner, 2001; Alavi, 2000).

The choices of knowledge strategy and appropriate supporting IT infrastructure are especially critical for knowledge-intensive organizations such as consulting and research firms. For these organizations, knowledge strategy and IT infrastructure decisions have a direct impact on their competitive position. Hansen et al., (1999) (hereafter HNT) have proposed a model to inform the choice of knowledge strategy and IT support for knowledge-intensive organizations. The HNT model is widely cited in the literature (Soliman and Spooner, 2000, Earl, 2001, Kautz, 2002, Maier and Remus, 2002) and was developed based on Hansen et al.'s work with organizations in the consulting sector. HNT have, however, claimed that “the strategy does not apply only to the world of consulting; we found that providers of health care and manufacturers of computers also need to choose a knowledge management approach that fits their needs and goals (e.g. as observed in HP, Dell and Access Health)” (Hansen et al., 1999, p. 110).

The HNT model suggests a choice between two alternative approaches to knowledge strategy; codification or personalization. Codification is a knowledge strategy that seeks to capture and store knowledge in explicit form (e.g. in documents and information systems), for subsequent transfer and (re)use by others within the organization. Within this approach, the role of IT is to support the storage and retrieval of this form of knowledge by people throughout the organization as and when required (Hansen et al., 1999). Personalization, on the other hand, is a knowledge strategy that seeks to link people to each other to foster ‘person-to-person’ sharing of knowledge rather than storing it (Hansen et al., 1999). In a personalization strategy, IT is used to extend interpersonal networks and the ability to connect and communicate with one another (Hansen et al., 1999). HNT's central argument is that, to enable effective use of organizational knowledge, depending on the nature of their business, organizations should predominantly pursue either a codification or personalization strategy, but still draw on the alternative strategy in support. Investments in supporting IT infrastructure should reflect this strategic choice.

While the HNT model is often cited, their advice appears to address mainly practical aspects of knowledge strategy decisions at the onset of a knowledge management initiative. In this paper, we question whether their model is adequate given the dynamics of knowledge strategy in organizations. We addressed this question using a case study approach with four organizations from various industries. The four case organizations represent different combinations of HNT's knowledge strategies and supporting IT infrastructure. The first case is a global management consulting organization that has an extensive investment in IT infrastructure to support a predominantly codified knowledge strategy. The second case is a small Australasian consulting organization in the educational sector where the investment in IT infrastructure is minimal and the knowledge strategy is predominantly personalized. The third case is an Australian manufacturing organization that has a moderate investment in IT infrastructure; their knowledge strategy is implicit and has no strong emphasis on either codification or personalization. The final case is a public-sector organization in Australia that provides research and statistical data for economic policy planning and development; this organization has an extensive investment in IT infrastructure to support both codification and personalization.

The structure of this paper is as follows. We review the pertinent literature on business strategy, knowledge strategy, and IT infrastructure support to manage knowledge. We then explain the concepts of HNT's model for knowledge strategy, implications for supporting IT infrastructure, and effective use of organizational knowledge. Following that, we outline our research methodology and present the four case studies. We compare HNT's arguments with the findings from the cases, which indicate some support for the model in the first three of our four cases. Based on the findings from our cases, we propose several refinements to the original HNT model.