Propuesta didáctica

As with phase one (and as indicated in Figure 4.1), data analysis can be seen as an iterative process. This section provides more detail on the processes of condensing the data and data display. The element of drawing and verifying conclusions will be covered in the following section.

During the research

On completion of the interviews for the first case study, all the interview scripts were reviewed. This led to the development of first cycle coding categories as shown in Table 4.9. These headings were used to produce a summary for this case study which also included some of my own reflections (see Appendix 12). The synthesis of data to produce this summary were done through mindmaps and lists, with one for each of the coding headings (see Appendix 13 for an example). The initial coding emerged from the data and was largely descriptive, but included some evaluation (e.g. what was seen to be helping and hindering career). My initial coding was case oriented. However, as this coding was applied (and further developed) to the other cases, the coding was often variable oriented to synthesize the data across cases (Miles et al., 2014; Yin, 2009). Following case study two, a more detailed version of the coding was developed as shown in Appendix 14. In particular, the second version provided more structure to the analysis of the personal narratives and the career conversations. However, within this I was keen to retain the sense of the story for each participant, an essential feature of narratives (Maitlis, 2012). A simple descriptive summary of each case study

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was also produced to share with the participants and the HR contact. This was not done in the IH case study as the numbers involved were too small to be confident that comments were non-attributable.

Business context Perceived roles Line manager perspective Helping career Hindering career • Goals • Structure • Culture • Individual • Line manager • Organization • Goals • Process • Examples • Individual • Organizational • Individual • Organizational Table 4.9: Phase 2 – First cycle coding post case study one. Post research

On completion of all the interviews a more comprehensive analytical process began. This was particularly focused on capturing data about the career conversations which had been described by participants. The initial coding and the immersion in the interview scripts enabled the development of draft categories. These draft categories were then reviewed against previous research related to career conversations (the career discussion work of Kidd et al., 2001; and the career encounter work of Bosley et al., 2009). This identified some additional categories to explore, particularly with regard to career shaper roles. These data were represented in a conversation analysis matrix which was produced using an excel spreadsheet. The codes used for developing this are given in Table 4.10 below and a screenshot of the spreadsheet can be seen in Appendix 15.

Category Coding

Conversation Trigger 1 = appraisal; 2 = restructure; 3=specific job opportunity; 4 = boredom; 5 = personal development; 6 = other

Conversation Instigator 1 = individual; 2 = own line manager; 3 = HR/academy; 4 = other Other party 1 = colleague; 2 = own line manager; 3 = internal hr/training; 4 =

neMTrk; 5 = external development expert; 6 = other

Process 1 = informal or adhoc; 2 = formal or part of structured process Outcome 1 = positive; 2 = neutral; 3 = negative

Primary impact 1 = career self concept; 2 = career world-view; 3 = career aspiration, direction and action

Shaper role Advisor, Informant, Witness, Gatekeeper, Intermediary One-off conversation or series 1 = one-off; 2 = part of ongoing conversations

Table 4.10: Phase 2 – Coding of career conversations

As the data were coded, further refinements were made to ensure consistent application of the codes. All decisions were captured with examples to support ongoing comparisons. The notes I made during this process can be seen in Appendix 16. In particular, the definition of a conversation was important to be clear on. I decided that it would only be coded as a conversation if it was

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communication which had clearly been conducted as a conversation (rather than via email for example). Thus, a generic comment from CL, regarding ‘strong influential bosses who believed in me and helped me develop’ was not counted as a conversation as they could have supported CL’s development through role modelling or training opportunities. However, if the situation was within an appraisal or a one-to-one it was assumed that it was part of a conversation and was therefore included in the conversation analysis.

As the data were further analysed some of the codes were refined. For example, the trigger code of ‘boredom’ only had two counts and was therefore combined as part of the ‘other’ category. Within the trigger code of ‘personal development’ however, it became apparent that there were two distinctly different types of conversations, one based on current role and another based on future career options. An additional category was therefore introduced as explained in chapter 6. Producing the data in this way enabled easy comparison of categories through counts. As indicated by Miles et al. (2014), this helps in ‘keeping yourself honest’ (Miles et al.,2014:284), ensuring that intuition and insights are appropriately combined with the frequencies found in the data. However, in drawing conclusions from these data, the limitations need to be kept in mind. For example, a different researcher could have made different coding decisions leading to different conclusions. Furthermore, two conversations could have the same coding but be different in other ways, so the limitations of the data should be recognised.

As with phase one, a participant report was written and sent to all participants. This 11 page report was based on the themes emerging from the research, but without detailed reference to the conversations or differences between the case study organizations. It was written to be accessible and relevant to the audience, covering themes from the research such as ‘what generally helps people develop in their career’, ‘how do career conversations help’ and ‘what changes would you like to see’. A copy of this report is available on request.

Drawing and verifying conclusions

The process of drawing and verifying conclusions was highly iterative. In the early stages, a number of decisions were made regarding themes not to pursue in detail. A list of these can be found in Appendix 8. One of these related to the prevalence to be given to the line manager perspective. At the start of phase two it was anticipated that some participants would be interviewed primarily as ‘line managers’. However, most participants were very engaged in describing their experiences as ‘receivers’ of conversations. The discussion on their role as line manager tended to be towards the

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end of the meeting and was generally not explored in as much detail. It was therefore decided that whilst these data provided some input from the line manager as a stakeholder, it would not be given the same prominence as the HR and individual perspectives. Another decision related to the exploration of career capital (Iellatchitch et al., 2003) and its potential influence on people’s experience of career conversations. Whilst it was recognized as an interesting and important area of influence on an individual’s career, there was limited data on this, so it was not examined in detail.

On completion of the field work the analysis was variable oriented, building a rich picture relating to RQ1, RQ2 and RQ3 (regarding alignment of goals, the contribution of career conversations and the nature of positive career conversations respectively). This related directly to the ‘local dynamics’ section of the contextual map (see Figure 4.5) and enabled a review of the helpfulness of this. The analysis also included comparisons against previous research which helped to inform the analysis. For example, Kidd et al., (2003) separated out the analysis of positive discussion experiences for their reporting. The same approach was done for this study which enabled direct comparisons to be made. In this way, the findings were positioned against existing research, identifying the ways in which they supported, extended or challenged previous findings.

Once the variable analysis was largely complete, a separate process of ‘case oriented’ analysis was conducted. This compared each of the case study organizations and related directly to RQ4 (the influence of organizational context). Starting with the nature of specific conversations described (and captured in the conversation analysis matrix), differences between case studies were then considered. The strategy and culture of each organization was also reviewed using frameworks explored in the literature review (e.g. Schein, 2010). Throughout this process the findings from phase one were used to support the analysis. For example, the contextual map was used to help to organize data and the organization’s perspective was reviewed using the appropriate data from the case study’s phase one participant (i.e. the matching HR participant).