Rivers of knowledge

9th Specials, Health and Law Libraries Conference

Assessing your organisation's knowledge management health

P Jackson, and J E Klobas
School of Media and Information, Curtin University of Technology

Abstract

In order to manage knowledge, a clear definition and understanding of the processes associated with creating, storing, and sharing knowledge is required. The authors derive their definition and understanding from the sociology of knowledge. Based upon a social-constructivist theory of knowledge with a strong and established theoretical base, we present a model that describes and interconnects knowledge processes.

This model gives us a clear set of concepts with which to develop a methodology for assessing knowledge management health, and for managing the knowledge environment during projects which require transfer of knowledge. The theoretical basis of the model suggests that if all processes in the knowledge transfer model are working well, then knowledge transfer is working well. If there is a breakdown in one or several of the knowledge transfer processes in the model, then knowledge transfer may be degraded. The point therefore is to optimise each of the knowledge transfer processes.

Software development and implementation are knowledge management processes par excellence, and are essentially concerned with creating and moving abstract concepts through a chain of staff roles until their ultimate codification into programming rules and data definitions. A practical tool has been introduced to information systems professionals and used in two projects. The tool is described in this paper, along with a summary of information systems professionals' responses to it, and suggestions about how the model and tool may be used by knowledge managers.

Introduction

Library and information professionals are increasingly adopting the role of 'knowledge managers' in organisations. They therefore require management tools for the development of organisational knowledge environments, not just the collection, codification and publication of records of explicit and codified knowledge. This is an holistic task, which should address the whole spectrum of factors associated with knowledge transfer and creation as a social phenomenon. Those library and information professionals in more traditional roles are also responsible for the procurement, development and implementation of IT systems to support diffusion of and access to information about and within documents. The modelling of information access profiles, and the anticipation and appreciation of information needs and requirements as they pertain to business processes makes librarians designers of information systems, solutions and tools. This paper aims to address both roles: to help knowledge managers in understanding and managing the knowledge environment and information managers in understanding and managing the complex process of elicitation of user requirements for information systems.

The paper begins by re-framing the problems faced in organisational software development and implementation as knowledge management problems. From this concrete base, and theories of the social construction of knowledge which can be used to explain problems in information systems projects, a generic definition and understanding of processes associated with creating, storing and sharing knowledge is developed. This definition and understanding is presented in a model that describes and interconnects knowledge processes, and then a tool based on the model. The paper concludes with a summary of information systems' professionals response to this tool as it might be used to improve knowledge transfer in and management of information systems projects, and reiteration of the potential for use of such a tool by knowledge managers

It will be shown that our model, derived from social constructivist theory, represents a schematic for assessing the level of potential for breakdown in knowledge transfer. Factors that affect knowledge transfer have been analysed from perspectives in many disciplines: cognitive science, management science, philosophy, sociology, psychology and even architecture. The model, being a comprehensive process depiction of the steps required to effect knowledge transfer, can integrate these and provide a useful analysis and solution framework.

Information systems projects and knowledge

Software development and implementation projects continue to be undertakings fraught with risk and are historically dogged by failure. There is still an alarming rate of dissatisfaction, in spite of great gains in technology, programming tools, methodologies and management techniques (Gibbs, 1984; Lycett and Paul, 1999; Lyytinen and Robey, 1999; Wastell, 1999). In 1996, a time when management satisfaction with information systems development was relatively positive, the Standish Group CHAOS report found that only sixteen per cent of all systems were delivered on time and on budget, with the required level of functionality; in large firms, this figure was as low as nine per cent. The translation of stakeholder requirements into designs and programs is a major point of breakdown in many information systems projects, not only because many technical and usability problems can be traced back to errors made in this phase, but also because the cost of repairing these errors is very high (Jalote, 1997; Marakas and Elam, 1998, p. 38; Somerville and Sawyer, 1998).

Information systems projects, both in development of new software and in the implementation of packaged software, are quintessential knowledge management and knowledge transfer undertakings. The view of 'knowledge' prevalent in information systems methodologies reflect the positivistic orientation and definitions that have dominated western philosophical thinking since the time of Plato. This is the fascination with what is to know something, for knowing, in this tradition of thought, suggests truth, belief and certainty about some aspect of reality. It has implications for the special nature of man as a rational animal, and our relationship to the world. The definition of the 'essence' of knowledge, which was coined by Descartes, is that of 'justified true belief': a definition that orientates itself towards the propositional nature of knowledge and the special nature of man as a reasoning being.

In this century, philosophers and thinkers have changed the emphasis of their examination of knowledge. So-called 'ordinary language' philosophers, such as Gilbert Ryle (1949) and Ludwig Wittgenstein (1958), examined the usage of expressions containing the word knowledge or 'know'. Ryle argued that one could distinguish between two types of knowing, 'knowing that' (...a certain fact was the case) and 'knowing how' (to do something, such as ride a bicycle). This distinction was drawn at about the same time by Polanyi (1973), who made the now proverbial distinction between 'tacit' and 'explicit' knowledge.

In their analysis of knowledge creation, Nonaka and Takeuchi (1995) claim that the Cartesian view of knowledge (that which follows Descartes) has steered the perception of knowledge to be 'information processing' and, ipso facto, the 'goal of any cognitive system is to create the most accurate representation of this world' (von Krogh and Roos, 1996, Chapter 8). This ignores the active role of the 'knower' in creating knowledge.

In short therefore, our concept of knowledge is moving from a Cartesian subject, standing in a static, cognitive relationship of certainty to propositions stating facts about the empirical or logical (that is, mathematical) world, to social beings who act in certain ways to exhibit knowledge, whether that is a skill, a fact or a body of theoretical knowledge. We have third persons who use words like 'knowledgeable' to describe those people and their 'usefulness' (although being a know-all is not necessarily of utility).

From this kind of analysis, we arrive at definitions of knowledge which essentially describe those pieces of mental matter (Sparrow, 1998) which give us the ability to decide and act. Davenport and Prusak's (1998) definition is a useful working approach to analysing knowledge:

Knowledge is a fluid mix of framed experience, values, contextual information and expert insight that provides a framework for evaluating and incorporating new experiences and information

Let us turn this paradigm to information systems. In a 'pre computer systems' phase, there is a shared, socially constructed reality which populates the organisational business world with invoices, orders, opportunities, job roles and relationships. This allows groups of people to work together, more or less effectively, as there is a commonly shared language and behaviour which projects a reality that all participants share and which is support by reinforcing and corrective social acts. The information systems project begins with an attempt to define that reality as a 'system', often in a context where no one has ever perceived a 'system' to exist. Through an information systems project, this social and procedural 'system' will go on to become an 'information system'.

It can be argued that an information systems (IS) project creates a social reality through the organisational modelling it undertakes, a model that is informed with the particular world view and background of systems designers and consultants (Hirschheim, Klein et. al, 1995; Westrup, 1996; Wingrad and Flores, 1986) and which uses their particular formal representations to achieve objectivation (Fichman and Kemerer, 1992; Robillard, 1999).

In IS projects the objective social reality is a new and explicitly constructed one and has objectivity through negotiated agreement between participants. Under normal working conditions, this agreement can largely be tacit (Schoen's 'optimal fuzziness') and indeed be defined through lack of disagreement. Disagreement may remain hidden until, in the process of articulation, the respective views are 'put on the table' for common viewing. This can be seen as a 'crisis of legitimation' (particularly at systems implementation): which version of reality is the correct one, when 'social routines are disrupted and the implicit becomes problematic' (Richardson in Banville, 1991).

Conventional definition describes an information system as a collection of technological components such as a computer, an application, a database and so on, (perhaps also referring to the people who use it but still as components rather than as social actors). However, it is only in the context in which these artefacts are used that we understand their true meaning ('meaning as use', Wittgenstein, 1958). We gain greater insight if we consider these components as part of a wider network of relationships. This view is the basis of soft systems thinking:

An information system is a social system which has embedded in it information technology ... it is not possible to design a robust, effective information system incorporating significant amounts of the technology without treating it as a social system (Land, 1985, p. 215, as quoted in Checkland and Holwell, 1998, p. 98)

It therefore follows that the properties of the information system emerge as we proceed in the analysis and design of a business system (Boarder and Laming, 1995; Checkland, 1999; Stage, 1991). However, contemporary design methodologies do not use the conceptual tools or language of social construction: they use the language of engineering, a discipline which builds lasting structures of steel and concrete. A methodology which caters for the construction of social objects in software must address both the emergent nature of that reality, the negotiation, understanding and legitimation and roles involved, as well as indicate how the players' attitude to the reality qua information system must be shaped: its longevity, adaptability and place in the general scheme of a social information system.

The process of analysing how a shared model of reality is built is an exercise in the sociology of knowledge, which we will define as 'the analysis of the functional interrelationship of social processes and structures on the one hand and the patterns of intellectual life, including the modes of knowing, on the other' (Dictionary of Sociology ). This framework enables a focus to be maintained on the process of moving and agreeing knowledge between participants in a social process. In order to automate a process and render it amenable to computerisation, we need to isolate those portions of a commonly agreed social system which are of relevance to the stakeholders. The sociology of knowledge offers us an apparatus to do this within the framework of the social-constructionist paradigm. The question then becomes, can we use these concepts in a methodical and systematic way to improve IS project outcomes? If so, we have evidence from a complex and critical organisational activity, that such a model may be a valid model of organisational knowledge transfer, with the potential to inform and improve knowledge management in a wider organisational environments.

The model of knowledge transfer and creation

This section presents knowledge transfer as a set of flows between processes which are performed in order to develop, gain or pass on knowledge. The linking of these processes in this form allows us to systematically identify, itemise and group factors relevant to the successful execution or breakdown of knowledge transfer. This paper does not attempt to order these factors. They are presented simply as examples.

This model has been derived from the sociology of knowledge, in particular the work of Berger and Luckmann (1991). Berger and Luckmann's seminal work proposes a series of process to describe how the 'intersubjective' gap between people is overcome and how socially constructed realities, which comprise the knowledge of any social group, are shared and achieve day-to-day objectivity. It shows how language and symbolic behaviour embody permanent solutions to the permanent problems of a given collectivity or group.

Figure 1: The knowledge transfer model

Each element of the model is discussed in the remainder of this section. The discussion includes a definition of each element, followed by examples of other authors' propositions about the successful execution or breakdown of knowledge transfer, classified by us according to the elements of the model and described as 'Sample guidelines'. While many of these examples have been drawn from case studies of information systems success or (more often) failure, others have been drawn from the broader literature of knowledge management.

1. Overview

   The model connects all knowledge processes in a temporal sequence, although there is no unambiguous start and end point. There are some limitations to be mentioned at this point: (a) being a model, it is a simplification and does not attempt to explain all aspects of knowledge and knowledge transfer; and (b) there is no discussion of the interplay between guidelines within the processes and how they may work in combination.

2. Personal knowledge

   Personal knowledge is the total of an individual's perceptions about the social and physical world in which he/she is a participant. The classical understanding of knowledge is 'justified, true belief', but in recent times has been extended to include physical skills, competence and those mental, interpretive models we have of the world, which give us 'the capacity to act' and decide. If we ignore these facets of knowledge, we will miss a number of important insights into how to manage knowledge transfer.

   Sample guidelines

   1. The more complex the knowledge (defined as the number of operations required to solve a task), the greater the difficulty in knowledge transfer (Zander and Kogut, 1995).
   2. The greater the causal ambiguity of the knowledge, the more difficult the knowledge transfer.

3. Process 2 - Externalisation

   Externalisation is the expression of knowledge in a symbolic form into the physical world, such that others can absorb it . This can happen in several ways, either in a written form, speech acts, or through diagrams or gestures. It can also occur in a variety of contexts, such as meetings, workshops, interviews, the coffee room or pub. These contexts may have an impact upon the meaning of whatever is externalised.

   Sample guidelines

   1. The presentation form, or the physical instantiation of the knowledge, may affect the transfer of the knowledge. "The knowledge that somebody has about something can be communicated more effectively when appropriate representations are used' (Sparrow, 1998, p. 75).
   2. Formal models, such as those used in computer science, do not lend themselves to wide dissemination of knowledge and require a joint tradition of development between business and ISD (information systems development) staff .

4. Process 3 - objectivation

   Objectivation refers to the creation of an objective, social knowledge that represents a social group's, rather than an individual's, knowledge of a business process or situation. It gives the knowledge an objective existence independent of the individual. Often concomitant with objectivation is the phenomenon of abstraction.

   Sample guideline

   1. Establish the levels of organisational objectivation (through examining 'standardisation' and 'codification' prior to the ISD design process and develop a strategy for increasing objectivation if required.

5. Process 4 - Legitimation

   Legitimation is a 'second order objectivation of meaning', a process whereby objective and externalised knowledge is authorised and meanings are validated as 'correct' or 'standard' . The classic and fundamental analyses of legitimacy are to be found in Weber and Rousseau. Where no religious or utopian vision provides legitimacy, it is provided by tradition, leadership or rational discourse and agreement. Unless Legitimation occurs, the reliability and authenticity of knowledge is always open to question.

   Sample Guidelines

   1. If there is no clear source of business legitimation for requirements, then there is a high risk of rejection of a subsequent system by some groups of stakeholders
   2. There may be actively competing and mutually hostile social realities within organisational sub-groups which must be reconciled.

6. Process 5 - Internalisation

   The successful completion of the knowledge transfer process is the absorption of knowledge by a recipient. This depends upon the capability of the knowledge recipient to internalise, or absorb the knowledge that has previously been externalised and objectified.

   Sample guidelines

   1. Prior related knowledge affects absorptive capacity . Szulanski (1996) conducted extensive empirical research confirming that absorptive capacity is the major determinant in effective internalisation.
   2. The earlier the build-up of absorptive capacity, the better the learning rate.

7. Process 6 - Knowledge creation

   Individuals, within their organisational environments, continually create knowledge. The sophistication of knowledge creation can be viewed as a spectrum, ranging from the mundane development of assertions and conclusions through logic, guesswork and assumption through to the radical creativity and purposive innovation associated with paradigm shifts.

   The active creation of reality is performed daily by all human beings in organisational contexts and can be constituted from an understanding of explicit organisational knowledge combined with the particular background, logical and analytical ability, experiential and psycho-social knowledge of an individual. These are combined to lead to a certain understanding of a particular business process or organisational situation:

   Rather than being highly structured and routine, many daily tasks are fluid and contingent, requiring workers to develop local strategies and forms of collaboration... (Clement, 1998)

   Sample guidelines

   1. Clear management guidelines for a project, such that the boundaries for establishing new business processes and exploring new technological possibilities are set (Cooper)
   2. Establish a close connection between the source of the need for innovation (for example, the user) and the supplier (for example, IS staff)

8. Process 7 - Reification

   Reification is 'the apprehension of human phenomena ... as if they were things...' . This is how much of human social reality, although not physically real, seems to take on an existence beyond humans and becomes 'alienated' from them. Reification is the process by which, for human institutions, the abstract becomes concrete in its presence and palpable in its apprehension.

   Reification will be present in business where the following statements can be heard:

   • 'We don't do it that way'
   • 'Read the manual'
   • 'We've always done it this way' - that which is not invented here will not be used here
   • 'Don't ask why, just do it.'

The knowledge management health assessment methodology and tool

If we consider the model and the guidelines, we see three levels at which the model can be used and strategies can be developed to counter inefficacious knowledge transfer conditions:

1. A particular process may not work well
2. The capability and the motivation to make a process work well may not be present.
3. Particular causes for ineffective knowledge transfer processes, such as low trust levels or the spatial distribution of a team, may be present.

The use of a methodology based on the above model would consist of three steps:

1. An initial knowledge transfer health check, or audit.
2. An evaluation of the results of the health check.
3. A set of strategies to address the outcomes.

The following figures show some screens from a prototype knowledge environment assessment and strategy development tool designed to guide knowledge managers, business managers and project managers through these three steps. Figure 2 shows the entry point into the tool, via the model overview.

Figure 3 is a sample of how the knowledge sharing environment might be assessed for a particular process, in this case externalisation (paraphrased as 'sharing'), using a set of guidelines and an electronic survey instrument. Apart from coming under a general category such as 'learning' or 'sharing', the guidelines are sorted into sub-categories. These generally refer to capability or motivation, and are the two major, most common dimensions of knowledge transfer. They refer to the questions:

• Capability - Can I perform this knowledge act?
• Motivation - Do I want to perform this knowledge act?

Figure 4 is the summary report for an information systems development project. A project manager or analyst can see how the project compares to a good, average or bad score. Appropriate action plans can be developed from the strategies screen (Figure 5), which presents suggestions for each question asked in the survey section.

Figure 2: Model overview and tool entry point

Figure 3: Sample assessment survey for knowledge sharing

Figure 4: Summary scores for a project

Figure 5: Suggested strategies from which to develop an action plan

Limitations of the methodology

The proposed methodology, and the tool based on it, is neither prescriptive nor exhaustive. The implementation of solutions will still depend upon the judgment of the managers involved, and the ability to change knowledge management conditions may lie beyond the authority or competence of the manager who is using the tool.

The tool, itself, is quite basic. In its current prototype form it consists of a series of linked Excel Worksheets. Assessment of KM health represented by each item in each sheet requires only the judgment of a single manager; it has not been developed to measure and compare judgments of several auditors (although this is feasible).

At a more theoretical level, the interrelationship between factors is not well understood. Interrelationships are not built explicitly into the model, which is based on the factors themselves. The relative importance of knowledge guidelines is difficult to objectively ascertain, but clearly some factors are more important than others. Szulanski for example concludes that prior related knowledge (i.e., competence) is more importance than other factors in the internalisation of knowledge. The relative importance of each factor is represented in neither the model nor the tool.

The utility of the tool

Despite these limitations, the model and the tool derived from it can be applied in a number of useful ways. Over the past 18 months, the tool has been presented at several meetings of professional bodies representing computing and information systems development professionals and knowledge managers. The audiences at these meetings have confirmed the following advantages of using the tool:

• Information systems methodologies can be enhanced by adopting a systematic approach to knowledge transfer based on established theories of knowledge
• Knowledge transfer criteria can be applied for assessing the efficacy of any information systems methodology
• Associations can be determined between the success of information systems projects and performance in the knowledge transfer processes described in the model
• The model can be used as a 'learning' tool: the experiences of an organisation in conducting projects can be integrated as guidelines appropriate and specific to that organisation.
• In post-modern organisations , where speed of reaction and ongoing change are the dominant characteristics, the efficient transfer of knowledge becomes increasingly critical. The guidelines in this research can be used to optimise this.

A unit within a large Western Australian public sector organisation is using the tool as it prepares for a new information systems development project where much of the work will be outsourced. The project manager has found the framework provided by the model has increased his understanding of the whole knowledge environment within which the project sits and of the processes which need to be understood and managed if the project is to be successful. He has found the guidelines easy to understand and assess, and has been able to overlay use of the tool on the information systems development methodology to be used for the project. While he believes the project will be more successful because of the additional understanding and rigour which has emerged from use of the tool, the final test will, of course, be in the extent to which this understanding and rigour will be reflected in actual execution of the project. Nonetheless, this manager's confidence in the value of treating systems development as a knowledge transfer process, and managing it using the tool, suggests that this tool has practical as well as theoretical value.

Conclusion

Finally, what is new about this approach, and how might it help library and information professionals who are acting as their organisation's knowledge managers? At a conceptual level, the model clarifies the difference between the approach taken by modern writers about knowledge management and the knowledge activities often undertaken in organisations: the modern conception of knowledge management is founded on principles of social or collective human understanding of organisations and their processes, but most organisations continue to attempt to implement systems which ignore these social constructions, attempting to engineer systems as if organisations and processes were constructed of components or objects which exist outside their social context. Until now, this social conception of organisational knowledge has been associated more with philosophical argument than practical tools for diagnosing and improving knowledge transfer. The tool described here, however, translates the concept of social construction of knowledge into a simple, practical tool which can be used to assess the knowledge management health of an organisation, at the level of a project, a team, a unit, or a process. This tool identifies critical social processes in the effective transfer of knowledge, and presents them in the familiar form of an audit checklist. The checklist differs from those presented in the general KM literature in its grounding in theory and the extent to which it is able to integrate the propositions of observers of knowledge transfer processes across several organisational functions.

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