Limitations and Further Research

In this section, the limitations of the research are acknowledged and discussed. The research has also identified avenues for further research.

1.8.1 Limitations of the research

This research has a number of limitations. Each of these is discussed next.

1. The initial assessment tool, KIAT, is derived from a single type of industry, that is Oil and Gas and from one single firm, namely Schlumberger. The generalisability, therefore, needs to be treated with caution. The choice of the research site is based on a theoretical, not a statistical, sampling (see section 1.3.2). The criteria used to choose the research site was pre-determined to address the research questions. While conducting a research in one organisation is a limitation, I found that in building an instrument such as KIAT, the in-depth study within one organisation helps to focus on the specific Factors that form the instrument. In Project Three, the KIAT Factors were refined through field testing in different business settings. Nonetheless, care must be taken when generalising the KIAT Factors to other KM initiatives.

2. The number of cases, while theoretically sampled, is few in number. Therefore, it is not possible to understand the correlation between experience in knowledge management and readiness level. Schlumberger with a lot of experience shows a high degree of readiness to implement KMS. However, Power International, which has more experience in KM than Friends Provident, shows less readiness than Friends Provident. To draw a meaningful correlation

a study using statistical sampling techniques needs to be conducted. This merits another research for further investigation which is discussed in the next section of this chapter.

3. I was a senior manager in Schlumberger when Project One was carried out in the company. This situation may have given rise to a certain bias during the data collection and the data analysis. I was, however, never part of InTouch development or deployment teams. Blaikie (2000) terms a researcher in my situation as an empathetic observer; in which case I can still aim to achieve some kind of objectivity and can place myself in the social actors’ positions. This situation may bring either advantages or disadvantages to the research project. The advantages are that my in-depth knowledge brings to the research a better understanding of the business setting and that my knowing the interviewees may gain more transparent information during the interviews. The disadvantages are that I may have answered my own questions and that I may steer the interviewees to the answers I want to hear. I used the technique termed as “mirroring or reflecting” (see section 3.1.3) to avoid this potential bias. At the same time with my extensive access to the internal materials related to InTouch, I used other available data for triangulation during the interview gathering and data analysis phases of this study.

4. In constructing the Hierarchical Value Map (HVM) I used a cut-off value of 3. This cut-off value is required to allow the rich meaning represented in the map and yet be simple enough to be represented and interpreted. A different cut-off value could have been selected. However, it has been suggested in this research technique that the criterion for evaluating the ability of the map to represent the data is to assess the percentage of all relevant and meaningful relations among elements accounting for the mapped elements. A minimum of 70% is the recommended reference; in my research this percentage is 82.3%. 5. Ideally, all the interviews should have been done face-to-face. This was the

case for Project Three but not for Project One. 30% of the Project One data collection was conducted through telephone-interviews. I acknowledge that there might be some missing information that could have been useful for the research. To avoid such a situation, all telephone-interviews were recorded and transcribed. When in doubt about the data gathered, I contacted the interviewees for confirmation.

6. In Project Two, the thirty five attributes developed in Project One had to be categorised under the STS dimensions. This required me to interpret the Factors to create the relationships. In order to avoid mis-categorising the Factors, where I was uncertain about a Factor I recontacted twelve respondents to understand the meaning they ascribed to the Factor before constructing the relationship between a Factor and an STS dimension.

7. The KIAT model assumes all Factors contribute equally to organisational readiness to implement knowledge management systems. This may not always be the case. Therefore, organisations using KIAT need to assess the relative importance of Infrastructure, Knowledge Structure and Knowledge Culture dimensions to prepare their organisation for knowledge management.

1.8.2 Opportunities for Further Research

I have identified five lines of further research. One is to examine the relationship between the level of readiness and the effectiveness of organisations in implementing KMS. A number of samples of KIAT application can be collected from different business settings in companies that are about to implement KMS. Following this diagnosis, a follow up study is required to assess the effective use of the KMS. Based on these samples a correlation between readiness level and the KMS implementation effectiveness can be drawn.

Two is the study of different organisations by applying KIAT to acquire in- depth understanding as to how those organisations address the weaker Factors to a higher readiness level. The study can be conducted either in a single business sector in a number of organisations or a larger scope addressing different business sectors. What is interesting to study is the organisational dynamics in moving lower readiness Factors to higher ones. One example is illustrated in Figure 1-4. Factors can be grouped into a matrix of readiness vs Factor complexity. Senior and middle managers with their team may decide which Factors will require complex or significant efforts to address and which ones will not. To ensure readiness, managers’ task is to move the Factors from lower to higher readiness level. Complexity for each Factor may differ from one organisation to another. However, the dynamics as to how managers address those Factors, or as to how managers decide to proceed with the KMS implementation and its timing, may be of an interest to both academics and practitioners.

The above two possible further researches may provide a better understanding for academics of the dynamics required for organisations in implementing KMS, and a benchmarking for practitioners.

Figure 1-4: Readiness vs Complexity for KIAT Factors

Factors with high degree of readiness Complexity High Low Low High Readiness Factors with low degree of readiness Factors with high degree of readiness Factors with low degree of readiness

Three is to study the correlation between experience in knowledge management and readiness level. In my research, the application of KIAT to the three organisations produces different levels of organisational readiness for each of them. With three samples, it is not possible to draw a meaningful correlation between experience in knowledge management and readiness level. The question that can be raised is whether there is a correlation between experience and readiness. To achieve this, research is suggested based on statistical sampling using a quantitative data collection and data analysis.

Four is to study how developing Factors towards readiness induce organisational learning. My research deals with the readiness to create, mobilise and diffuse knowledge. The desire to engage across territorial debates about the distinctions and connections between organisational learning and knowledge management has existed for a decade (Vince et al., 2002). There is a further opportunity for research in understanding the dynamics as to how developing Factors towards readiness induce organisational learning. For example, Sole and Edmondson (cited by Vince et al., 2002) have analysed learning processes in the context of geographically dispersed project teams. Their focus is on understanding how these teams acquire knowledge from the various sites where their team members are located. This fits in well with the concept of structural diversity. I have proposed that implementing KMS needs to include structural diversity in the equation. The study on how developing readiness induces organisational learning may illuminate some connections rather than distinctions between organisational learning and knowledge management. Research can be conducted in either one case or a multi-case study to derive different dynamics in developing Factors towards readiness that induce learning.

Five is to study the dynamics and the development of Communities For Performance (CFP). Weick states, “knowledge is not something people possess in their heads but rather something people do together” (2002:S8). Learning takes place when members of communities create, mobilise and diffuse knowledge. Weick (2001) and Ghoshal and Gratton (2002) further remind us that knowledge is of little use, at least in a business world, if it is not put into action. Weick concludes that to achieve successful performance, a manager “(i) animates people and gets them moving and generating experiments that uncover opportunities; (ii) provides direction; (iii)

encourages updating through improved situation awareness and closer attention to

what is actually happening; (iv) facilitates respectful interaction in which trust, trustworthiness and self-respect develop equally and allow people to build a stable rendition of what they face” (2002:S9). I have argued in this thesis that communities which bring beneficial results to organisations are CFP. Further study is required to illuminate a better understanding about these types of community. Weick (2002) seems to have started the discussion related to this. I have outlined an early understanding of CFP found in Schlumberger’s technical service delivery process and proposed the characteristics of these types of community. Research can be designed to better understand the dynamics of CFP and the organisational development involved in creating CFP.