Perspectives on knowledge management By Patricia Morizio

London School of Economics and Political Science Information Systems and Innovation Group

Department of Management 2013/2014

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Abstract Epistemology is the philosophical branch of study which focuses on the essence and breadth of knowledge and its

acquisition. As there exists no single definition of knowledge, there have been countless theories developed to explain it. Knowledge management as a field has emerged as a way to understand how the vast array of, often unorganized, data that most organizations have at their disposals is harnessed and honed in the production of useful information, or knowledge, for the firm. Information systems research has focused on the way ICTs can be leveraged to improve

knowledge management practices and success. As a result, theories ranging from the technical­rational, socially­embedded, and economic have evolved to address the phenomenon of how best to manage knowledge and also

explain why sometimes technology not only fails to improve, but can even hinder, organizational efficiency.

1. Introduction Knowledge management (KM) is most generally defined as the storage, retention, and dissemination of significant information that has been acquired by an organization. Systems to manage this so called “knowledge” – a.k.a. knowledge management systems (KMS) – have been the subject of active concern amongst researchers and firm managers alike for their potential to disrupt organizational innovation and, ultimately, translate into competitive advantage and business strategy success. This essay will begin by presenting various definitions for what exactly KM is. I will segue to its relation to IS theories, namely Transaction Cost Theory, the Knowledge­based View of the Firm, the Resource­based View of the Firm, and various socially­embedded theories. I will also touch on common limitations of companies’ sometimes myopic focus on KM as presented in the IS literature. It is beyond doubt that the way organizations utilize knowledge within their contexts is essential to their productivity and, ultimately, success. By critically analyzing the research that has been dedicated to the topic of KM, we can assess the value and proper execution of certain KM practices in order to most effectively leverage the array of technologies and KMS we are fortunate to have available today.

2. Definitions of KM & the KM Spectrum There are a variety of KM definitions in the existing literature causing it to be, at times, poorly defined, or resulting in sometimes unrelated theories being classified under the broad heading of knowledge management. These definitions often dilute a multi­dimensional topic to an individual, simplified view (Binney, 2001). To fill this void, Binney created the “KM spectrum” to help companies comprehend the scope of KM choices at their disposals. The framework provides a comprehensive structure for management to strategically assess and adequately communicate its KM direction.

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Throughout the literature on applications of KM, there have been different terminologies for a group of six, general business case clusters a.k.a. “elements” which Binney outlines within the following KM spectrum:

1. Transactional The user requests information and the system produces it. The system does not prescribe a course of action for the user based on the knowledge given, but merely allows access to it. Examples Binney gives are help desk, customer service, and order entry applications.

2. Analytical The analytical element presents the user with interpretations extracted from massive amounts of unstructured data, thereby creating new knowledge. It is used for “competitive intelligence” by providing information on competitive and market activity. An example Binney gives is companies using this element in the (apparently most common) scenario of providing a direct answer to a complex problem e.g., “What are my competitors doing to take advantage of the Net?”

3. Asset management Binney directly compares asset management KM to a library, “with the knowledge assets being catalogued in various ways and made available for unstructured access and use.” Assets are often a by­product of business as usual and are kept for later use (the specifics of which are often unknown or unclear at the time of creation). Asset management KM differs from analytical systems in that the data usually have increased complexity and are less numerous with asset management. Binney also argues that assets within this element may require some intervention to “codify” them, such as in capturing product development history or project experiences.

4. Process based The process­based element addresses the arrangement, systemization, and improvement of process such as through internal lessons learned or standardization of best practices and benchmarking, usually with the help of a third party specialist (Feltus, 1995; Hill, 1999; O’Dell & Grayson, 1999; and Powers, 1995 cited in Binney, 2001, p.36).

5. Developmental Developmental applications – a.k.a. “investing in human capital” (Edvinsson & Malone, 1997 cited in Binney, 2001, p.36) – are concerned with expanding and improving the skills and knowledge of an organization’s employees or “knowledge workers.” This covers the transfer of knowledge through training (explicit knowledge) or “developmental interventions” such as experience via work assignments, collaborative learning environments, or communities of practice (tacit knowledge). Increasing the capabilities of a company’s knowledge is akin to increasing the firm’s knowledge

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capability. Additionally, such a practice can also attract the most desirable knowledge workers to the organization.

6. Innovation/creation based This element is primarily concerned with establishing a collaborative environment for knowledge workers from different backgrounds to produce new knowledge – e.g., new products or company competencies – together. The importance of facilitating the interaction between teams of people with differing skills and experiences is increasingly becoming a key aspect of innovation. It is the role of management to “foster the dynamism of knowledge creation” and “manage knowledge emergence” (Nonaka & Konno, 1999 cited in Binney, 2001, p.37).

3. Knowledge Management Theories 3.1 Transaction Cost Theory’s relationship with KM The costs of doing business (i.e., making exchanges) in the market are defined as “transaction costs”. They can be separated into three general categories of information­related costs: search and information; bargaining and decision; and policing and enforcement (Dahlman, 1979). Coase (1937) defines a transaction cost as the cost of acquiring a good or service through the market as opposed to producing it within the firm. The related Transaction Cost Theory (TCT) accounts for the actual cost for firms of outsourcing production of products or services. These costs include the above search, negotiation, and enforcement costs (e.g., time of weighing different provider options, negotiating the contract, and enforcing the contractual agreement, respectively). When making a decision, the inclusion of all costs are considered, not just the base market prices. Essentially, this theory delineates the “make vs. buy” decision for organizations. It had been commonly presupposed that IT has the potential to improve economic efficiency due to its ability to improve the flow of information and reduce transaction costs. However, as Cordella (2006) exhibits, ICT adoption often increases transaction costs. This is due to the “externalities” or extra costs associated with accommodating environments of greater numbers of technical possibilities which leads to increased search time and effort to select the most appropriate solution (i.e., search costs), as well as an intensified complexity of coordination (i.e., negotiation and enforcement costs) in today’s landscape of ever­changing IT governance and regulation. Cordella argues that we can avoid “electronic disorder and sub­optimal economic results”, as well as manage this deluge of data and successfully translate it into knowledge, by reducing the amount of information, filtering it appropriately, and minimizing coordination needs. This will, ideally, lead to increased economic efficiency (Cordella, 2006).

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Within the KM literature, there has been discussion of a so­called “Knowledge­based Theory” – or Knowledge­based View of the Firm (KBVF) – which classifies knowledge as an organizational asset that paves the foundation for sustained competitive advantage (Alavi & Leidner, 1999). Nonaka and others have contrasted this KBVF to TCT (Nonaka, 1991 cited in Brown & Duguid, 1998, p.90). The arguments consider organizational knowledge more advantageous than knowledge that can be created or found in the open market place. As Brown & Duguid (1998) write, it is this organizational knowledge, not the minimization of a firm’s transaction costs, which holds the firm together. This explanation helps to understand why firms still exist in today’s rapidly changing environments which are supposedly radically breaking down traditional organizational boundaries. Brown & Duguid argue that, because of this, firms will continue to exist and it is why organizing knowledge will remain a critical part of what organizations do. Hedlund (1994) echoes Nonaka and Brown's sentiments against the transaction­cost view of KM. He argues that this type of approach is limited because it takes:

“transactions as given (rather than something to be created), adopting an atomistic view of the basic unit of analysis...not paying much attention to historical heritage and consequent inertia and path dependency, and by not considering what happens inside the firm in great detail.”

Hedlund (1994, p. 78) goes on to criticize the traditional transaction­cost literature, as it tends to ignore the importance and value of tacit – as opposed to explicit – knowledge transfer. He uses the real­world comparison of Western and Japanese firms to accentuate the differences between the West’s apparent production stagnation and the rise of Japan’s production efficiency in the 1980s. Hedlund attributes the Western firm’s “inflexibility of tightly specified and articulated systems of knowledge” as its Achilles’ heel of the era. This is made apparent through rigid plans unable to be modified or innovated upon and the fallacious conception of the firm as merely a tool to “exploit” the resources and knowledge at hand. Hedlund highlights how Japanese firms tended to import a product or other tangible object, system, etc. and fiercely integrate it into the local context of the firm, thereby building knowledge related to it from the ground up. For example, these firms tended not to hire senior managers, experts, or consultants from foreign firms to teach them ways of operating or using technologies. Instead, they preferred to build the tacit knowledge enabled by a new technology internally. This could be attributed to culture and even level of difficulty in assimilating the “foreign” knowledge. Either way, as a result (although perhaps at the expense of speed), the Japanese example builds in tacit and highly­localized knowledge from product inception, often leading to novel uses of

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the artefacts and systems that their creators could never have imagined (Hedlund, 1994, p.80). A by­product of this is increased product and knowledge application innovation. Western firms, on the other hand, have shown a tendency in the research to opt for importation of high­complexity, tacit knowledge which is then transformed “in a machine­like fashion through articulated means (clear organization and division of labor, replaceable parts and people, etc).” Hedlund goes on to compare the work of transaction­cost theorists including Coase; Williamson; Jensen & Meckling; and Alchian & Demsetz who seem to myopically value speed of integration above all else. Hedlund aligns his viewpoint more with Aoki (1990 cited in Hedlund, 1994, p.80), however, who points out the weakness in such outlooks, particularly in terms of comprehending the Japanese example, as they underestimate the importance of “information processing and decision making” in analysis. 3.2 KBVF & RBVF Knowledge has been treated “as either a thing (to be captured, stored, transmitted, etc.) or a disposition (whether individual or collective) resulting in ‘objectivist reification’ on the one hand or ‘subjectivist reduction’ on the other” (Orlikowski, 2002). Orlikowski highlights Kogut & Zander’s view of KBVF which emphasises the role of “shared identity” among members of an organization (Kogut & Zander, 1996 cited in Orlikowski, 2002, p.256). They posit that the sense of community instilled in employees by the firm structures an identity which influences interactions and learning among members. Moreover, Orlikowski (2002) points out the argument of Dutton et al. (1994 cited in Orlikowski, 2002, p.270) that employees’ deep connection with the organizations for which they work improves their performance standards, levels of cooperation, and frequency of contribution towards company­wide aims. Orlikowski describes two separate streams of organizational knowledge perspectives. The first suggests that organizational knowledge can inherently be split into two types: tacit and explicit (Polanyi, 1967 cited in Orlikowski, 2002, p.250). The main idea is that by identifying organizations’ different types of knowledge, it will result in more effective knowledge generation, sharing, and management. This “taxonomic” view has been criticized by some researchers, namely Tsoukas, for ignoring that tacit knowledge is the [inseparable] basis for all knowledge and that it is wrong to separate it into a pair of distinct types (Tsoukas, 1996 cited in Orlikowski, 2002, p.250). Instead, Tsoukas aligns himself with the viewpoint of other IS researchers related to a combined outlook which considers knowledge to be “processual, dispersed, and ‘inherently indeterminate’” (Tsoukas, 1996; Boland & Tenkasi, 1995; Davenport & Prusak, 1998; and Cook & Brown, 1999 cited in Orlikowski, 2002, p.250).

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Brown & Duguid (1998) reinforce the separation of knowledge types but into “know­what” and “know­how” (Ryle, 1949 cited in Orlikowski, 2002, p.250) – the latter being the capability to apply the former in practice. Brown & Duguid introduce the concept of “stickiness” to describe the ability of a certain “know­how” to be translated across similar organizations or “communities of practice”. This acknowledgment of “stickiness” has resulted in various theories on knowledge­facilitating best practices (Orlikowski, 2002). She presents these ideas along with the caveat that there is still much to be learned from these differing perspectives on organizational knowledge. A corresponding IS topic is the Resource­based View of the Firm (RBVF) which “focuses on the firm’s resources and capabilities to understand business strategy and provide direction to strategy formulation” (Andreu & Ciborra, 1996). The RBVF describes firms as pursuing valuable resources, acquiring them, and turning them into capabilities in order to attain sustainable competitive advantage which should lead to maximum return on capital. Resources are assets – “things” such as knowledge – that the firm owns. What a company does with a resource is known as a “capability”, and standard resources can develop into capabilities through organizational learning. Capabilities are created from fostering and exchanging information through an organization’s human resources. To distinguish themselves, firms must establish strategic differentiation through the process of developing their distinctive – i.e., core – capabilities. Core capabilities are defined as assets of a company which are desirable, rare, and inimitable, and with no strategic substitutes (Andreu & Ciborra, 1996). According to the authors, they are developed from standard capabilities “through a transformation process by which undifferentiated resources, available in open markets (where all firms can acquire them), are used and combined, within the organizational context of each firm, with organizational routines to produce capabilities, which in turn can become core and the source of competitive advantages if the above conditions are met.” Thus, firms aim to gain strategic, competitive advantage by cultivating valuable and rare resources into honed, learned, core capabilities. 3.3 Other Social Perspectives on ICTs The Social Construction of Technology (SCOT) is an IS theory originating from the 1980s which argues that technology is not a determining factor in human action (i.e., in the vein of technological determinism), but, instead, that human use shapes the technology to which it is applied. This view also holds that the precise ways technologies are used within organizations cannot be fully understood without determining how they are embedded within their local, social contexts.

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SCOT eventually paved the path for the later Social Shaping of Technology (SST) theory which states that there are choices – both conscious and subconscious – ingrained both within the individual design of technological artefacts and systems, as well in the ultimate direction of the subsequent innovation’s consequences (Williams & Edge, 1996). In other words, each technological artefact holds within it different potential routes of use which lead to, perhaps, very different outcomes. The choices the actors make in rolling out such artefacts will have implications for future users of the systems and, potentially, other groups, including society as a whole. Both SST and SCOT differ from Actor­Network Theory (ANT) in that the latter involves technology as not only a factor, but a motivator or prescriber (i.e., directing duties or actions) of human actors. These theories can be useful in explaining why capitalizing on knowledge through technology is oftentimes difficult. Walsham (2001) addresses this issue by taking a similarly human­centered view to articulate the broad tacit knowledge which underlies all human cognition and action. His paper ties in with the Sensemaking perspective in postulating that ICTs can benefit KM only if human meaning is taken into account in the adoption and diffusion of said technologies. In the Institutionalist perspective, institutional or social elements and structures make up and hold together organizations as entities within themselves. Social elements may include such constructs as company mantra, norms, processes, professional roles, structures of authority, regulation, etc. Through time, these structures come to be so entrenched in the operations of a firm that they become, therefore, “institutionalized”, making other ways of functioning practically unfathomable. According to Institutionalist theory, ICT is considered an institution in its own right. Institutions are defined as “authoritative, established, rule­like procedures in society which have a self­sustaining character...[and] taken­for­granted standardized sequences of activity in their environment” (Avgerou, 2000). For example, the knowledge that ICTs can provide is one of the institutional elements of ICT. An Institutionalist perspective would look at how institutions impact the implementations of technologies intra­ and inter­organizationally. Sensemaking Theory, as mentioned earlier, emphasizes a more individual or micro­focus. It studies how actors affect IS implementation based on their own usages and, moreover, abilities to make sense of new technologies (Dervin & Nilan, 1996). A new artefact may disrupt an actor’s current way of working, resulting in a shock that sparks a process of “sensemaking” which would determine the actor's subsequent actions (Weick, 1988). As Orlikowski and Gash (1994) write:

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“to interact with technology, people have to make sense of it; and in this sensemaking process, they develop particular assumptions, expectations, and knowledge of the technology, which then serves to shape subsequent actions toward it.”

Connecting these ideas with the knowledge­focused perspective on the diffusion and adoption of complex technologies (Newell et al., 2000), when given a “black boxed” technological artefact (i.e., a new company system), actors must unpack the new ideas – or knowledge – inherent in the technology, figure out how it applies to them and their routines, and then “action” that application appropriately. In the Institutional view, this unpacking and application of knowledge embedded within an artefact would be based around institutional rules and norms; in the Sensemaking view, it would be based on the actor’s local view of the world (namely, within his place of work) and his role in it – which could, perhaps, also be shaped by the overarching institutional structures of the organization in question.

4. Conclusion KM has been the subject of much academic and practitioner interest over the past several decades as a potential enabler of competitive advantage for firms which harness and use it correctly. There have been various definitions of the term “knowledge management” as well as scores of economic, technical, and social theories that have developed to make sense of its development and possibilities. It is important, however, to acknowledge the limitations of KM, and not just the positive effects it has on organizations, as a majority of the literature tends to assume. Knowledge can be a “double­edged sword” (Leidner & Schultz, 2002) – the lack of which can lead to costly blunders and inefficiencies, and the overabundance of which can lead to undesirable liability and counterproductive inflexibility. Sensemaking and other social perspectives on ICTs can help to explain the application of technologies towards KM, stressing the importance of the human­centric point of view if the ICTs are to be an enabler of, rather than a barrier to, knowledge creation and management. Successful use of ICTs in KM is a determinant of not only production efficiency, but also economic efficiency, which are both, ultimately, necessary in the pursuit of the end goal of sustained competitive advantage for firms.

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References

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