3.3.6
In qualitative research, data collection and analysis may take place at the same time and the sample as well as sources of data may not always be clear at the onset of the research (Silverman 2010; Pellissier, 2007). As data is being collected it must be organised in order to make analysis easier. It is recommended that initial data is reviewed and compared with research question to see if subsequent data collection cycles will require more questions to be asked. Reflection and notes are required to ensure that full data is available that will enable focussed analysis. The actual data analysis stage should simply be refining and organising the themes rather than beginning to put data into themes for analysis. In this study, the MKC Relationship Management framework was be used as a guide to data collection to minimise the problems associated with action research where data may be collected in a non-systematic manner that makes it a challenge to understand. Furthermore, the framework will enable the findings to be related back to the theoretical foundations the study is based on (Corbin and Strauss, 2008).
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There are various forms of data analysis that can be used and among them are: ethnographic analysis, case study, content analysis and analytic induction. In this study the thematic data analysis method was used and why this was the case is discussed below.
Thematic data analysis
Thematic analysis is a form of Grounded theory in that it adopts an inductive approach to data. When analysing data using the thematic approach, one begins with a particular and real situation and then seeks to make the findings more general of abstract. Figure 14 below demonstrates how this is done.
Figure 14 Deductive Data Analysis (source: in Saldana, 2009: page 12)
Real Abstract
Particular General
Coding is a critical part of thematic analysis. A code in this context is a short phrase or word that symbolically assigns a summative, salient, essence capturing, and/or evocative attribute for a portion of language-based or visual data (Saldana, 2009). Coding happens in cycles as depicted in Figure 14 above (Saldana:12, 2009). When compared to other forms of data analysis discussed above, the thematic analysis was best positioned to analyse the data gathered in this study. This is because the MKC Relationship Management model already presents the various themes that could be used to analyse the data and in addition to this, data would have been collected within the same framework thereby making the claim by Pellissier (2007) and Silverman (2010) true that in qualitative research data collection and analysis can take place simultaneously. The codes, categories and themes were, therefore,
Code Code Code Code Code Code Category Category Themes/ concepts Theory Subcategory Subcategory
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drawn from the MKC Relationship Management framework even though an open mind was maintained in order to uncover any emerging issues.
The process of thematic analysis that was followed in this study was as follows (Charmaz, 2003:94-5; Gibbs, 2007):
1. The CEBS reports as well as the customer feedback registers from all the branches produced between 2011 and 2013 were read with a view to understanding what customers were saying about customer service and relationship management at SBM. The same was done with data relating to people survey and performance management audits that relate to the same period in order to establish the people/cultural issues that exist within SBM. Questions such as: - What was going on? What were people doing? What were they saying? What were these statements or actions take for granted? How do structure and context serve to support, maintain, impede, or change these actions and statements? - were asked in the process of reading the documents.
2. The general themes were grouped in line with the MKC Relationship Management framework and coded in accordance to the framework’s general areas
a. Customer insights (Ci) b. Business process (B) c. Culture/people (C) d. Processes (P) e. Infrastructure (I)
f. Business Outcome (BO)
3. The general concepts were further divided into concepts under each of the six areas identifies. Data was also be coded in terms of the type of data source and year when data was collected as follows:
Ci-CEBS13pg3
4. Links were established between the various areas to establish the cause and effect relationship between the six core concepts identified.
5. Conclusions were then drawn about how the concepts relate to each other and how possible solutions can be drawn. The specific areas where solutions were drawn was developed in consultation with the business unit head in branch banking, business banking and private banking using in-depth interviews.
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6. Once the first cycle of data analysis was done, the implementation of the solutions drawn was carried out. Focus group discussions were held and reflection was carried out. Analysis of the data from the focus group discussions, financial reports, CEBS results and customer feedback as well as performance audit reports were analysed in a similar manner to points 2-5 above.
7. In the third cycle of this research, which was another planning cycle, CEBS reports, customer feedback registers, performance management audits, financial and sales results for 2015 were analysed in a similar manner to 2-5 above.
The thematic analysis, which is mainly used in psychology and other social sciences studies, can be a very insightful method of analysis. It is flexible and change oriented which makes it compliment well with action research because the data analysis can be modified as you go along (Howitt and Cramer, 2010). This data analysis method was selected because it complements well with the themes that have already been identified in the BCPI model which were used to guide the in-depth study into KM within the case organisation. Apart from this, it is a flexible analysis method that fits well with action research since during action research some unexpected issues emerge that would impact of the initial plans of the study. The process of data analysis will took place throughout the duration of the data collection period to ensure close observation of how each theme was impacting on each other. As analysis took place, reflection meetings were held to challenge the findings and assumptions made as key outcomes (Bjørn and Boulus, 2011). As such reflexive critique and dialectical critique were key components of the data analysis process. Under reflexive critique, focus is more on reflecting rather than on criticism or scepticism – it is more than systematic reasoning but more about critiquing even one’s own reasoning and practices. It includes critiquing rhetoric, tradition, authority and objectivity. Dialectical critique on the other hand, is a term that was coined by a German philosopher, Hegel, and was originally used to explain the reality of tensions in all things co-existing. A simple example of this would be the fact that while all human beings are generally born male or female, each of them have traits that are also masculine of feminine. During this study, some elements under study presented such challenges where tension needed to be resolved through consultation with the participant (Winter, 1989).