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Ten lessons from my MBA Project

It’s blog time – that moment when I put fingers to the keyboard and reflect on my research journey.  An insight that has been re-emerging (as I wrote a blog entry on this topic previously http://web.me.com/kiwicito/Site/My_Blog/Entries/2010/7/19_Becoming_a_Researcher.html) is that the MRes part of the PhD is all about becoming a researcher, and is not dominated by the topic of interest.  I suppose this should be obvious, but if you have the end in mind – then a contribution to knowledge in an area of interest, then research journey can look quite different.  I can explain this by saying that right now, I am learning much more about research itself.  Research philosophy, methodology, and method is omnipresent, rather than it being about organizational identity in the project environment.  I can see this shifting over-time, but it is not the current centre of my universe.


When I look back on my MBA, the emphasis was about learning the language of business, and the crown jewel was assembling a dissertation that involved doing some research in an area of interest to business.   But the emphasis was business first, and research second and I realize now that the dissertation could only have reached a sufficient quality that matched ones research skill level.


In my research project I did an auto-ethnographical study, and my being a bit narcissistic I loved that.  I had little access to negotiate, accept for some interviews I conducted, and the internal access question of how much I was willing to confess to myself, and therefore to others through my writing!


Now, the picture looks different with Research Philosophy and Method classes under my belt.  So today I take a look back on this research and offer a blog sized critique, extracting the extant lessons for me.  First the positives,



Under advisement from my advisor, I did maintain a clear separation of the coaching experience, and any literature review, or research during the coaching.  This enabled the experience to be genuine and not interfered with by concepts or others experiences.


Data Collection

I used multi-method (interview and auto-ethnography) not that I really appreciated the significance at the time.  I recorded and transcribed all the coaching transcripts – a great source of data to analyze, and I used my actions list between the coaching sessions as another source of data to see progress in-between sessions.  Lesson 1: Real life events are excellent sources of insight.


Data Analysis

While I might have lacked scientific rigour, I was pushed by my advisor to do a second order analysis – and too be honest I was not sure what that was at the time.  From this second order analysis, a model of my personal experience did emerge.  Returning to viewing the literature in light of my findings, and extracting other models previously published, then comparing and contrasting these was most productive.  One contribution I feel from the project was the idea that the coachee ‘unconsciously assimilates’ the skills of coaching from the coach.  As I went back into the literature it was here I discovered a link between coaching with adult learning theories, a particularly cool outcome.  Lesson 2: Research is iterative.



This for me was the most enjoyable part of the project, and not at all in the spirit of writing perfect English grammar either, but instead from the creativity, empowerment, and digging back into my memory bank to write the non-fiction vignettes that I used as a rhetorical tool for taking the reader through my story.  What worked really well was sharing often my writing and getting feedback!Lesson 3: Always get feedback on writing from others.  Now the negatives,



My understanding of my philosophical position was non existent.  I picked the phenomenon under study – executive coaching, a coachee perspective, and thinking that a pure way of getting an insider view, and therefore auto-ethnography was selected right of the bat!


My method therefore, implicitly came under the umbrella of an interpretivist framework.  Looking back now, it would have been interesting to review the data again, however, under a social constructivist paradigm.  Under this paradigm, one will be able to extract how the coach and the coachee co-construct narrative and see the processual nature of the coaching experience.  Interviewing the coach would have been a useful addition to support this philosophy. Lesson 4: Make your ontological and epistemological position explicit, and think though all the options.



I made a judgment error here by not following the advice of my advisor.  I had early on been influenced by a friend that for research to be credible must have multiple voices.  I was after a distinction level project so as a sort of risk aversion, I chose to run semi-structured interviews to support the auto-ethnography.  With a word limit of 16000 words for the dissertation, this clearly was a serious compromise, and one I would be careful to repeat in future.  Lesson 5: Follow your supervisor’s advice!


Data Collection

The semi-structure interviews were poorly run, I never felt that I really connected with interviewees (they were all bar one – over the phone), and I never understood until now the unique power relations between interviewer and interviewee, and therefore did not account for it.


Perhaps through lack of experience, I also added questions near the end that formed a primary part two of the questionnaire on tools.  I sent these via email to gain the missing data and in hindsight was a bit sloppy.  This might reflect the messy iterative nature of data collection and analysis…


Overall, I will admit I really lacked (and still do) skill in this area.  If interviews become a part of future research (and I think they will) then I need some practice and skill building.  Lesson 6: Work on your interview skills, and run a pilot that includes analysis to see how it fares, or perhaps even better consider the use of multi stage interviewing – e.g. one before any analysis and one afterwards where you can legitimately add questions relating to emerging ideas, and co-construct/validate the narrative.  I think in this way the participant can become a researcher, a collaborator, especially in light of the interpretation of their own story.


Operationally, one final, criticism relates to my lack of control on interview data.  I carefully recorded the interview scripts, and took notes throughout.  As I neared the end of my analysis (thankfully) I accidentally deleted my interview transcripts from the audio recording device without back up.  This meant I needed to rely on my hand written notes, and analysis completed to date.  Out of embarrassment I never let this error out of the bag! Lesson 7: Keep back ups of your data!


One serious criticism, in both interviews, and my being a researcher – I failed to maintain a researchers diary where I could record, review, reflect, modify my approach.  At one stage my advisor said… “that is not the way it happened” – when I sent subsequent drafts of my dissertation, and I had innocently got caught in the trap of rewriting history in a sequence that perhaps sounded more interesting, or logical.   Lesson 8: Keep a research diary and be reflexive.  This blog is in part helping me be true to the PhD researchers experience, but I know that once I start designing and executing the next research project, this will not be enough.


Data Analysis

This is probably my biggest criticism – a vagueness on how the analysis was actually executed.  Recently after reviewing 169 organisational identity studies – I must say that many share this vagueness – but it could also be short word counts for publishing articles.


Simply put, I was never explicit on how the findings emerged from the auto-ethnographic data.  This is what I wrote in my paper:


“From the personal data store of my own experience I carefully reviewed transcripts, journals and field notes to check relevance and indication of changing behaviours or thought patterns, looking at dialogues, volume and tone…. With different coloured highlighters I coded themes from coaching sessions, insights, key actions, overall value, energy levels, moods, and my confidence levels.  This analysis resulted in the creation of the coaching journey map to piece together a holistic overview of my coaching journey. Next I recorded my experience in story through a process of careful event selection and creative non-fiction writing..”


Later I wrote:


“Once all interviews were completed, I then listened to the recorded interview transcripts, and analysed others’ experiences in conjunction with my own experiences, looking through for commonalities and differences in the use of words, phrases and intellectual or emotional connection. I reviewed self data and participant data to discover which of “tools” were most instrumental in achieving change within the coaching journey. I identified these as “keys” that appear to function by unlocking the doors to change within individuals.”


The truth is, the ‘keys’ kind of just jumped out at me.  My method of coding was intuition based yet lacked reflexivity (see lesson 8), and questioning the coding was not undertaken.  I don’t explain the second order analysis either…. Not even sure how I missed this point.  My second order analysis was from ideas that emerged, and a need to demonstrate some sort of model or hypothesis.


Overall, I just get the sense that my data analysis was not scientific enough!  I don’t mean this from a positivist position.  What I mean by this comment is that even from the subjective and interpretivisit standpoint, one can and must bring rigour and transparency to data analysis.  I think it is ok that ideas just “pop out”, but at least one can track where and when it did so.  Lesson 9: research how qualitative data analysis can be performed, understand it, design it, and document it.  



I think within the writing part of the project, I remain confused and dissatisfied overall.  I read an amazing auto-ethnography by Carol Ronai – ‘On loving and hating my mentally retarded mother’ (accessible online) – and I had set my sights on something similar of that nature.  However, I was being asked to re-write my coaching experience so that it did not appear as a story or sequence, and instead to write it from a thematic perspective.


My initial goal to communicate via story on how a coaching experience unfolds and leave the interpretation of the included subjectivities up to the reader, this goal was either an incorrect thing to do in an MBA research project or it was misunderstood.  This requires future scrutiny.  Lesson 10: Understand the purpose and genre of your writing that will represent your research.

In sum, I have tried not to be overly critical on my Masters level research project, yet at the same time make an honest blog-sized appraisal of the strengths and weaknesses of the attempt.  The conclusion reached within the research itself I still regard highly, as useful and informative, perhaps even explanatory, however, it could have been significantly stronger.  You can find the link to the project here: http://web.me.com/kiwicito/Site/MBA_Project.html


Here are the lessons again, from my very first research attempt:

  1. Real life events are excellent sources of insight.
  2. Research is iterative.
  3. Always get feedback on writing from others.
  4. Make your ontological and epistemological position explicit, and well though through!
  5. Follow your supervisor’s advice!
  6. Work on your interview skills, and run a pilot that includes analysis to see how it fares, or perhaps even better consider the use of two stage interviewing.
  7. Keep back ups of your data.
  8. Keep a research diary and be reflexive.
  9. Research how qualitative data analysis can be performed, understand it, design it, and document it.
  10. Understand the purpose and genre of your writing that will represent your research.


One final admission, from my experience with a remotely located supervisor.  You need to be bold to admit when you don’t know what your supervisor means – I remember quite a few times I would read, then re-read emails to try and understand a point made – yet not go back and ask what seemed like a silly question!  So what is second order analysis then?


I hope you find these useful, and I would love to hear from you and similar lessons learned, or feedback on these ones.

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