Using The Knowledge Management Maturity Model (KM 3 ) As An Evaluation Tool

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1 Using The Knowledge Management Maturity Model (KM 3 ) As An Evaluation Tool Draft Paper Dr. Séamus Gallagher * Division Of Management & Information Systems School Of Management & Economics The Queen s University Of Belfast BELFAST BT7 1NN Tel: & Shirley-Ann Hazlett Division Of Management & Information Systems School Of Management & Economics The Queen s University Of Belfast BELFAST BT7 1NN Tel: * All correspondence should be directed to this author No part of this document can be reproduced without the express written permission of both authors 1

2 Introduction This paper is the first in a series related to the broad area of Knowledge Management (KM). Specifically, the present study attempts to develop and test a mechanism that will assist managers in evaluating their current KM capability and thereby facilitating effective measurement of the impact of KM initiatives upon (strategic and operational) business performance. We propose that in order to possess effective measurement capability, the organisation must first evaluate. It is our belief that the KM 3 framework, discussed in greater depth throughout this paper, represents a more integrated and holistic approach to address the problems associated with evaluation and ultimately measurement. The paper begins by presenting a brief overview of KM and the problems associated with implementation and measurement, before discussing the models (KMƒ and KM 3 ) that are currently being piloted in this particular study. Finally, the paper presents the findings from the exploratory interviews and discusses future research directions. Knowledge Management An Overview Whether one considers KM simply as a competitive necessity (Romberg, 1998a), a strategic resource (Earl, 1994; De Long & Miller, 1997), or the source of competitive advantage (De Long & Miller, 1997; Gantz, 1998; Nonaka, 1991; Wharton, 1998; Davenport, 1996; Seemann, 1996; Parlby, 1999a; Havens & Knapp, 1999), it is evident that it represents an important business issue. Briefly, KM is considered to involve an explicit and systematic approach to capturing information and knowledge about a company, its processes, products, services, markets, customers, and 2

3 competitors; and storing this in a place where relevant personnel can find it, distribute it, and make use of it (Nonaka, 1991; Wharton, 1998; Romberg, 1998b; Bushko & Raynor, 1998; Seemann, 1996). KM seeks to ensure that the right information is available to the right people, in the right places, at the right time, and that the individual knowledge elements are leveraged and multiplied in value (Chait, 1999). The so-called business improvements, or benefits, which are said to result from KM include: increased profits, improved organisational, performance, innovation, responsiveness, productivity and competency (De Long & Miller, 1997; Wharton, 1998). Difficulties Associated With Knowledge Management There is much debate in both the literature and practice on what constitutes 'knowledge', how one should approach KM implementation, and how it should be evaluated. A plethora of definitions, models, methods and approaches exist each with their own unique perspective (see for example, Bushko & Raynor, 1998; Nonaka & Takeuchi, 1995; Pasternack & Viscio, 1998; Martiny, 1998; Scheraga, 1998; Puccinelli, 1998; Chait, 1999; Havens & Knapp, 1999; Frappaolo, 1998; Greco, 1999a, 1999b). One particular concern centers around the practical issue of measuring the effectiveness of knowledge management initiatives (Hiebeler, 1997; Amidon, 1998; Fitchett, 1998; Hiser, 1998; Bowen & Scannell, 1999; Crainer, 1999; King, 1999; 3

4 difficulties associated with measuring the return on investment and performance improvements resulting from these initiatives. Both Davenport (1996) and De Long & Miller (1997) report that the vast majority of knowledge managers have to rely on anecdotal data in order to justify knowledge investments simply because they have not been able to develop sufficient quantitative metrics. Seemann (1996: 6) stresses that any knowledge-oriented initiative can and must be measurable - both qualitatively and quantitatively. Indeed, Scheraga (1998: 27) holds that the whole concept of measurement is not as difficult as it first appears and that it should employ the same practices that are used to determine the value of other parts of the business. However, he offers little in the way of practical application concerning how best to proceed. Bushko & Raynor (1998) note that measurement is an important, but as yet unresolved, issue within the wider KM sphere. Other writers (Parlby 1998a; 1998b; 1999; KPMG, 1999) also emphasise the importance of evaluating current KM practices and processes. However, this research holds that there is a symbiotic relationship between the notions of measurement and evaluation and that the two cannot be examined effectively in isolation. KM & KM3 As A Response An Overview The Knowledge Management Formula (KMƒ): There is much agreement in the literature that managing KM effectively requires a time-consuming, multidimensional perspective. Since knowledge is rooted in human experience and social context, managing it well means paying attention to people, culture, and organisational structure, as well as to the information 4

5 technology (Havens & Knapp, 1999). This is broadly similar to the work of Chait (1999) who believes that KM requires the concurrent management of 4 domains:- Culture, Content, Process, and Infrastructure. Indeed, our research thrust extends the thinking behind Earl's model (1994) that knowledge management requires a combination of technological and social action. It also reflects the work of many other writers in the field, most notably Davenport, De Long & Beers (1998) and the work of Puccinelli (1998: 41) in stressing the need to successfully navigate the political, organisational, and technical challenges, as well as appreciating the depth of the cultural change required. In proposing this formula the authors accept Parlby's (1999) sentiments warning against prescriptive approaches and therefore do not suggest that it is the solution to knowledge management. Rather, the formula should be viewed as a template to apply those principles and techniques of most use in particular organisations. The KMƒ formula (see figure 1, overleaf) offers a more comprehensive basis for knowledge management implementation and progression because it normalises the central overlapping concerns of Ki, Kc and Kt (Gallagher & Hazlett, 1999). These components refer to the organisational infrastructure, culture and technological issues respectively. 5

6 External Environment Internal Environment Customer Supplier Competitor Informs CORPORATE STRATEGY Vision; Mission Knowledge Stock Provides Provides Direction Support (Why) (How) IMPLEMENTATION PROGRAMME Knowledge Management Strategy [KM: The Process] Detailing Expected Benefits Encompasses "Promotes development of" "Provides basis for" Ki Kc Kt "Facilitates access to" Figure 1: The Knowledge Management Formula (KM ) Since it is not the intention of this paper to focus on the thinking behind the KMƒ the following discussion provides only a limited overview [a more detailed discussion can 6

7 be found in Gallagher & Hazlett, 1999 and Hazlett & Gallagher, 2000]. Following Cohen & Prusak (1996), McElroy (1999), Parlby (1999), Martiny (1998) our formula holds that the corporate strategy must provide the direction for the knowledge management strategy (the why) and the knowledge management strategy in turn must provide the support for the business strategy (the how). Thinking of 'knowledge as strategy' (as Earl, 1994, suggests) can not only help to understand the role of knowledge management, but also to justify expenditure on it. What is required is an integrated approach to knowledge management that offers organisations the means to ensure that they are doing the right thing, at the right time, for the right reasons, and in the most effective manner possible. Knowledge Infrastructure [Ki] There are two aspects to this KMƒ component. The first involves the actual structure and processes of the organisation, while the second focuses on the knowledge stock. This coupling is based on the premise that any organisation attempting to implement KM must first understand its current structure and processes, and also what knowledge is required to make those processes work. Such a process-oriented view has also been mentioned by other researchers, most notably Coen (cited in Scheraga, 1998: 27), De Long & Miller (1997) and Carnelley (cited in Romberg, 1998b). Puccinelli (1998) proposes that knowledge management processes, incorporated under this Ki component, necessitate changes in organisational structures that go beyond technology. Further, this has direct implications for how a company '...designs its organisation and defines managerial roles and responsibilities 7

8 within it, Nonaka (1991: 101). And so, this 'Ki' dimension necessitates an examination of the organisation's structure and hierarchy. As with any physical construction there needs to be a firm foundation. Organisations can conduct a knowledge audit to establish where gaps lie in their process provision. While not adding value in and of itself, a certain amount of infrastructure is needed in order to create value later (Davenport et al. 1998). The second component part of Ki, Sourcing Knowledge, broadly reflects what Seemann (1996) refers to as finding knowledge in the organisation and 'mapping' it and can be achieved by performing a knowledge mapping exercise based on the value chain. This knowledge map helps organisations capture and access their knowledge', (Seemann 1996:2) and is used as a guide to what knowledge is important and where it can be found (Martiny, 1998: 74). De Long & Miller (1997: 10) report that even if management accepts that knowledge is an important ingredient in competitive advantage, difficulties may still exist in identifying core competencies. Knowledge Culture ('Kc'): Organisations contemplating adopting a KM philosophy must develop ways of ensuring that the culture is conducive to knowledge sharing (Wharton, 1998). This view is also shared by Martiny (1998: 71) who holds that the human side of KM is the hardest part. Indeed, according to Wah (1999) the key issue is to instill a corporate-wide culture that encourages knowledge sharing. This is a process that cannot be left to grow and develop on its own. Knowledge sharing begins with vision 8

9 and direction from upper management - only they can create an environment that encourages and supports sharing, and knock down the cultural barriers that exist today. (Puccinelli,1998:40). Building an effective 'Kc' involves recognising the importance of the role of individuals as carriers of knowledge and nurturing and empowering them to share this knowledge for the good of the organisation. Focusing explicitly on the knowledge culture component of KMƒ forces theorists and practitioners to address the very complex, yet crucial people issues in conjunction with the infrastructure and technology aspects. Furthermore, it is proposed that addressing the cultural aspects of KM should precede any technological considerations - the technology will only succeed if people believe that other people's knowledge is beneficial for them and their work (De Long & Miller, 1997: 8). Knowledge Technology - Kt This component of the KMƒ relates primarily to the technology that is implemented in order to collect, store, and disseminate knowledge within an organisation, or in the words of Kao (in Gurteen, 1998), IT is the medium for representing, organising and deploying knowledge. It can be considered to encompass all the traditional elements of IS and IT strategies within IS strategic management, and encapsulates an entire plethora of choices in relation to platform, telecommunications, systems, security, and the like. For example, the growth of web-based technologies such as the internet, or intranets, is considered to be a major factor supporting individual, group, intra- and inter-organisational learning and knowledge transfer (Carayannis, 1998; Gantz, 1998; Romberg, 1998a). Greenberg (1998: 14) even proposes that it was only with the 9

10 advent of the intranet that employees had a systematic way of sharing knowledge. Without such technological mechanisms, organisations (particularly those that are quite large and distributed) may never realise the full value of its knowledge (Scheraga, 1998). Synergy between the components: Recognising that knowledge is not separate but is one of the critical enabling factors to a more powerful management model, is the first step to getting it right. And so, our model holds that it is not the separate units themselves that create knowledge and add value, but the synergistic nature of the whole, the value of which is ultimately greater than the sum of its constituent parts. Enormous benefits have the potential to occur when the balance between the 3 components is achieved. Having presented the KMƒ the following sections deal specifically with the KM3 and the findings of the exploratory interviews. KM 3 The KM 3 framework is a mechanism that is being developed in order to assist in evaluating current KM capability and thereby facilitating effective measurement of the impact of KM upon (strategic and operational) business performance. We believe that the KM 3 offers a more comprehensive basis for knowledge management evaluation because it normalises the central issues of Ki, Kc and Kt - knowledge infrastructure, culture, and technology respectively. (Gallagher & Hazlett, 1999). In this manner the KM 3 can be considered as the operationalisation of the concepts 10

11 embodied within the KMƒ. Amongst other things, the KM 3 can be used as a diagnostic mechanism or self- assessment tool to allow organisations to chart their current and planned KM progress. Its relative simplicity means it can provide a balanced analysis of the 3 components of the KMƒ and in this respect offers a holistic rather than function-specific focus. Further, it forces managers to continually question KM and thereby provides explicit focus on the issue of change. In contrast to other maturity models, relating specifically to IS usage, the KM 3 forces explicit consideration of the human dimension - through Kc - and its interconnectedness with technology and infrastructure. Theory & Practice Anecdotal Evidence Informs Conceptual Framework - KM Knowledge Infrastructure Knowledge Culture Knowledge Technology Techniques to check 'KM in Action' Helps us to develop techniques to do 'KM in Action' KM Maturity Model - KM 3 Evaluation & Measurement KM in Practice KM Implementation Programme Figure 2:- Operationalising The KM Components This framework draws from attempts in other disciplines to evaluate the current state of practice within a particular firm and thus enable that firm to continually improve. Exemplary examples of such practice can be drawn from a variety of different disciplines. These include (1) the SEI's 'Capability Maturity Model' (Paulk et al, 1993) for software development, (2) KPMG's 'Knowledge Management Framework Assessment Exercise' (KPMG, 1999); KPMG's characterisation of the 'Knowledge Journey' (KJ) (Parlby, 1999a&b), (3) Microsoft's 'IT Advisor for Knowledge 11

12 Management' (ITAKM) (Microsoft, 1999), and (4) Crosby's 'Quality Management Maturity Grid' (QMMG) (Crosby, 1978) for quality management. These and other models operate on the premise that an organisation will move through stages of maturity with respect to the phenomenon of interest - IS management, Quality management, and Knowledge management. Such incremental models represent an attempt to assist managers interpret their current position, and the significance of that position for the organisation and to fully understand those factors that influence the knowledge strategy. Management's approach will differ from one stage to another and it is suggested that different areas of the organisation can be in different stages at any one time thus necessitating a portfolio approach to knowledge management (Hazlett & Gallagher, 2000). In this way the model can assist managers to legitimise the differences between concurrent KM initiatives. The parallels within all four models are immediately apparent. They define stages of growth, or maturity, that a firm can be expected to pass through in its attempts to improve its processes and ultimately business performance. The CMM concentrates specifically on software development processes, the QMMG considers the integration of quality management with business processes, while the KJ and ITAKM are explicitly concerned with the integration of knowledge processes with core business processes. Despite their explicit focus on knowledge management, both the KJ and ITAKM exhibit caveats. For example, Microsoft's ITAKM (not surprisingly) expends too much effort in trying to address technological concerns. Little emphasis 12

13 is placed upon culture and other general management issues. Meanwhile, KPMG's KJ is too vague and offers little in the way of practical assistance. Benefits Sustained: Knowledge Improvement - Strategic Business Improvement KM Focus CSF i,c,t Path to KM Integration CSF i,c,t K-Optimised CSF i,c,t K-Enabled CSF i,c,t K-Managed Localised: Knowledge Exploitation - Operational Business Improvement K-Aware Knowledge Emphasis Elapsed Time Figure 3: The Knowledge Management Maturity Stages The KM 3 represents an extension of all these techniques in an attempt to integrate and develop current theory and practice. The above figure provides a diagrammatic representation of the stages within knowledge management maturity. It is proposed that a firm's knowledge maturity can be represented by several distinct phases/stages. These range from no awareness of knowledge management to a complete and focused knowledge strategy that is tightly coupled to the business strategy and ultimately results in improved business performance. We hold that a firm seeking to implement KM will progress through these stages in sequence. However, we do not wish to 13

14 imply that progression can always be guaranteed. In certain circumstances a period of discontinuity may occur which can obviously have negative consequences wherein the organisation regresses. However, it is also conceivable that such discontinuity can have positive results in so far as it pushes the organisation to re-evaluate its current position and consciously or otherwise redouble its efforts. Each stage of a firm's maturity can be characterised in terms of the three components of the KMƒ - Ki, Kc, and Kt - and preliminary work is currently underway in order to develop each stage in more depth. In terms of actually applying the model, we propose that a technique akin to Critical Success Factors (CSF) analysis (CSFA) (Rockart, 1979) would be beneficial. This technique has been widely applied, for example in the IS field (Fitzgerald & O'Kane, 1999; Krcmar & Lucas, 1991; Nandakumar, 1996; Phan et al., 1995; Ang & Teo, 1997), for many years and is extremely straightforward to apply and ensures management participation at various levels (Robson, 1997). As traditionally defined (Rockart, 1979) CSFs are "...for any business the limited number of areas in which results, if they are satisfactory, will ensure successful competitive performance for the organisation. They are the few key areas where things must go right for the business to flourish." Yet CSFA is not without its weaknesses (Robson, 1997: 159). For example, CSFA is inherently flexible and it is this flexibility that can lead to casual application and thus generate false or misleading results. CSFA should therefore be applied with the same rigor as other more formal approaches. A further problem is 14

15 the requirement for "...very skilled and very perceptive interviewers to do the abstracting to CSFs...", however, practice will help in perfecting the technique. In the current context such a technique would involve the stages outlined below. CSFA requires the articulation of the knowledge mission and objectives (in light of the business strategy and expected business improvements) before meaningful interviews can be conducted with various groups of stakeholders. This having been done, a content analysis (Carney, 1972; Agar, 1980; Miles & Huberman, 1994; Calloway, 1995) of the interviews is necessary to enable abstraction of the CSFs across the three KMƒ components. Further articulation, clarification and ultimately consensus should be facilitated through additional interviews and feedback sessions. In this way the current KM maturity capability can be established and decisions - in relation to Ki, Kc, Kt - prioritised (Critical Decision Corporate Set Strategy - CDS i,c,t ). This technique is represented diagrammatically below: Knowledge Strategy: Mission and Objectives Conduct Interviews CSF i CSF c CSF t SWOT i SWOT c SWOT t Consolidate & Prioritise Establish current capability in terms of KM 3 15

16 Critical Decision Set - CDS Figure 4: The Critical Success Factor Analysis Technique It is proposed that the above framework can assist with measuring and evaluating the effects of KM by providing explicit criteria and direction for theorists and practitioners alike. This will not only permit managers to position their organisation vis-à-vis KM practices, but it will also facilitate them in improving existing KM processes and hence in attaining a more effective measurement capability and maturity. It is proposed that there is a direct relationship between maturity and measurement with a firm's ability to effectively measure the benefits of knowledge management initiatives improving as it matures. In proposing the above model the researchers are conscious of a number of potential difficulties. Firstly, any model is going to be a simplification and this is certainly true of the KM 3. The researchers are aware of the complex dynamics that exist in all modern organisations and govern the activities therein - knowledge management is no exception. However, if we are to understand this concept we must first abstract and then develop workable solutions. Following the work of others (most notably Havens & Knapp, 1999; Chait, 1999; Earl, 1994; Davenport, De Long & Beers, 1998; Puccinelli, 1998) we have decided to abstract knowledge management to three key issues - infrastructure, culture and technology. We believe that this can be useful in helping us to grasp the essential elements of the concept and offer practical insights. Secondly, some might suggest that the model (in its current form) offers little or no 16

17 practical help. We acknowledge the embryonic state of the model and the obvious need for further development and refinement. However we hold that the KM 3 has the potential to offer a useful lens through which theorists and practitioners can evaluate KM initiatives. Thirdly, the potential exists for a firm to be at different stages of maturity for the three components - infrastructure, culture, and technology. This could be considered a complication within the model. However, we believe that this highlights the models usefulness as a diagnostic tool for performing a kind of knowledge management self-assessment or Gap Analysis. Finally, skeptics may consider the application of such a model to be both time-consuming and difficult. This same charge has also been levied against the CMM. However, we believe that doing nothing in relation to evaluating KM can also be time-consuming and difficult for entirely different reasons. Furthermore, in contrast to the CMM (with its 18 Key Process Areas) we believe that an advantage of the KM 3 is its relative simplicity (with its 3 components). The remainder of this paper concentrates on the empirical results from the exploratory interviews. It begins by providing a brief overview of those data collection and analysis techniques employed throughout this study before proceeding to present the findings. Research Methodology The current qualitative exploratory study represents the first stage of a longer term research project and is based on a number of semi-structured interviews with 17

18 professionals from a variety of disciplines who are directly involved in, or professionally interested in, Knowledge Management. Attewell and Rule (1991: 319) openly advocate interviewing both managers and employees because this will provide a richer perspective on the phenomena under investigation. For this reason, we interviewed employees from a variety of organisational levels. The sample is opportunistic in nature, selected on the basis of perceived relevance and access, with no attempt being made to ensure statistical representativeness. Attwell and Rule (1991) along with Babbie (1995) claim that statistical sampling is often abandoned in field work due to practical constraints. Therefore following Eisenhardt (1989) the researchers decided to select the sample based on the principle that participants would be likely to be significantly and directly interested in and/or involved in the phenomenon under investigation. Hence the sample was selected to provide breath of coverage rather than depth. Our purpose at this stage is merely to identify common themes and to facilitate further interviews and in-depth case-studies as well as the development and refinement of the KMƒ and KM 3 models. Prior to conducting the interviews respondents were provided with an outline detailing the purpose and nature of the study. In addition, since many respondents requested some indication of the types of questions that were going to be asked the researchers, following Faison (1996), provided outline preliminary copies of the interview schedule in advance. This placed many interviewees at ease and the researchers are convinced that this procedure contributed greatly to the willingness of many to 18

19 participate, and also did not generate scripted answers. As each interview progressed responses to individual questions were carefully probed to elicit further details on specific issues (Fearon & Philip, 1998). In an effort to triangulate the data being gathered from the interviews the researchers requested access to company documentation on Knowledge Management. In some cases access to such documentation was impossible due to the fact that it either did not exist, or was considered too sensitive. All interviews were recorded on audio tape and later transcribed. A qualitative content analysis technique (Carney, 1972; Agar, 1980; Miles & Huberman, 1994; Calloway, 1995) was employed in order to extract key themes as well as similarities and differences between responses. Having transcribed the interviews, respondents were given the opportunity to proof read the transcript of their interview to ensure that it was indeed an accurate representation of their views and opinions. (Faison, 1995; Tuunainen & Saarinen, 1997). Following each interview, a Contact Summary Sheet was filled in by the interviewer - this permits the interviewer to develop an overall summary of the main points in the contact (Miles & Huberman, 1994: 51). Having completed an interview, the transcript was coded. The coding scheme used in this analysis is a mixture of an inductive approach and start list approach (Miles & Huberman, 1994: 58). An initial coding scheme for the data was suggested by previous examination of literature, but as interviews took place the scheme was permitted to inductively evolve from the data. First-level coding was 19

20 descriptive with a second-level focusing on the development of patterns from the data. These codes and patterns were then used to develop the KM 3 model. A major question relating to any research project is the generalisability of the findings. Walsham (1995: 79) asserts that...a critical issue for researchers concerns the generalizability of the results from their work. In discussing the generalisability of qualitative studies, Walsham suggests that researchers should not under-estimate the generalisability of their findings. Firestone (1993: 16) also proposes that when it comes to generalisability, qualitative methods are...not at any great disadvantage. While statistical analysis seeks statistical generalisability, qualitative analysis seeks analytic generalisability. (Firestone, 1993). The former involves sample-topopulation extrapolation and necessitates probability sampling. The latter does not rely on probability sampling and involves generalising to a theory. Furthermore, Bryman (cited in Saunders et al., 1997: 225) states that it is the very fact that qualitative studies can be in-depth which adds to their potential generalisability. Having conducted an in-depth qualitative study, a researcher can acquire a level of knowledge that may generate increased understanding when applied to a variety of other situations - thus increasing generalisability. Research Findings Based on the exploratory interviews, it appears that the vast majority of the firms examined are doing something in the name of 'Knowledge Management'. We encountered only one organisation that had yet to begin the KM 'journey' but decided to include it in the analysis for comparative purposes since the respondent was 20

21 enthusiastic about its potential and was clear as to how KM would impact on her organisation. While many of the respondents appeared to be critical of their respective organisation, they did feel that KM initiatives, current and future, represented a significant opportunity to improve their current business performance. Issues such as improved customer relationships, continuity of service, increased internal co-ordination, faster cycle times and increased productivity were all mentioned. For some, KM involves an explicit effort to capture and utilise the knowledge, while for others, it represents nothing more than a '...common sense approach to management'. As one respondent notes '[KM is]...nothing more than a nice term for what people have been doing for years without realising that they are doing it or thinking about it too much.' However, one firm in particular, a large multinational consultancy firm, appeared to have in place what could be described as a well defined explicit KM strategy, with roles, responsibilities, vision and objectives all clearly established at a global level. Yet, further probing uncovered difficulties in operationalising this strategy at both regional and departmental level. The respondent postulated that these difficulties had much to do with (a) a lack of management support and direction (at the lower levels), and (b) cultural barriers. In contrast, many of the remaining organisations have no formal KM strategy in place, preferring instead to adopt a much more informal approach. As one respondent aptly sums up, KM is 'more informal than formal, more implicit than explicit'. Given the above statement, one could be forgiven for believing that many of the organisations who claim to have 21

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