Presentation on theme: "Dump the questionnaires and make it up: the value of fictional “data” in management research Paper to be presented at the 4 th European Conference on Research."— Presentation transcript:
Dump the questionnaires and make it up: the value of fictional “data” in management research Paper to be presented at the 4 th European Conference on Research Methods in Business and Management Paris, April 2005 Michael Wood, Portsmouth University, UK
I am not arguing that … Fiction is beautiful; empirical data and statistics are ugly; so fiction is best Best approaches based on stories / narrative (different concept from fiction) It’s OK to make data up but claim it’s real Theoretical constructs and abstractions are fictional (perhaps they are but that’s another story). I’m concerned here with fictional “data”: facts, events, etc.
I am arguing that … It’s important to explore possibilities: what might happen or what might be done, as well as what has happened. These possibilities have to be invented not discovered: they start as fictions.
My background Not an avid reader of fiction Not a devotee of literary theory Written book on statistics (samples of size n) but never quite a believer Series of papers on samples of size one Now samples of size zero…
To see why fiction might be necessary, consider …
Approaches for project to investigate how to improve X 1Investigate the current problems with X. 2Investigate how other organisations deal with X 3Taking account of the findings from (1) and (2), and the literature and any ideas within the organisation, and any other sources of inspiration, produce some proposals for improving X. 4Test the proposals to see how they work
Difficulty of step 3 Little advice for step 3 Need to imagine or model the possibilities. Eg –Mental model or story –Spreadsheet models We need to create and analyse fictions – things that haven’t happened (yet) Fictions allow us to go beyond existing situation to consider new possibilities
For example: X is risk management… A tutor’s comments on a student’s proposed project…
The aim of the proposed research project is “to review the effectiveness of the college’s risk management strategy, and to recommend any necessary improvements”. The methods proposed were “qualitative, because this will enable the researcher to investigate the issues in depth and generate insights into contextual meaning for the situational actors.” Quantitative methods were rejected on the grounds that they are “positivist” and “superficial” they “ignore the social construction of reality”. The proposal then went into more detail about the selection of a “purposive” sample of “key stakeholders” within the organisation, about how “in-depth, structured interviews”, and about how the data was to be “triangulated” (checked from other sources in ordinary language). This was to be backed up by documentary analysis of key internal documents, and a benchmark study of another college recognised as “best in class” for risk management. One possibility specifically rejected was looking at any other colleges: restricting it to the student’s college and the best in class college would make the project more “focused” and, besides this, was necessary because the college was “unique” so “cross college generalisations of a statistical nature would be meaningless”
This was all very impressive and pressed all the right academic buttons, and so I gave it an excellent mark. Despite, this, of course, in the real world it’s a complete waste of time because all it will do is recycle the prejudices and biases of the “key stakeholders”. I made a few gentle comments about extending the database with data from other sources within the college and from other colleges, about statistical information having a useful place in this sort of research, and about casting the empirical web as wide as possible so as to find out about as many possible risks and risk management strategies as possible.
Even this really misses the point because it’s all based on what’s actually happened. The problem is that the real disasters to come have probably not occurred anywhere yet. Any research into risk management – particularly for a college of bungee jumping - needs a way of exploring possibilities which have not yet occurred. The research needs to consider what might happen as well as what has happened
Fictions for researching risk management Envisage some possibilities for improving risk management – ideas may come from formal research, lit review, brainstorming. These need fleshing out as reasonably detailed proposals. Then imagine how these would cope with the occurrence of particular risks. Brainstorming, simulations, role plays, etc to elicit ideas about what might happen. Obviously important but all this must be made up. Cannot stick to empirical data – must enter the world of the imagination.
In science Einstein used thought experiments like imagining riding on a beam of light Mathematical theories often start with “Suppose…” General theories need to be tested by application to examples which are usually fictional
In business Fictions allow you to explore possibilities like potential innovations and risks Rigidly sticking to the facts means you may not notice how things might change … or how they should change to improve things
Types of fictions Stories, fables, utopias, dystopias Thought experiments and “examples” Simulations can generate hypothetical data to see what might happen (eg from statistical hypothesis) Spreadsheet / mathematical models can analyse the implications of hypothetical possibilities –Eg what-if models Scenario construction (Goodwin and Wright, 1998) In all cases the idea is to analyse something which (probably) does not exist
Some reasons for using fiction Less research needed for invented cases Testing particular aspects of theory Avoid ethical and confidentiality problems Explore circumstances that have never happened –Eg scenarios involving risks which might occur, proposed innovations, utopias, dystopias For communicating in a memorable way
Another example See written paper…
Taken-for-granted assumptions of “research methods” Empiricism: everything must be based on facts – ie on surveys, interviews, observations Methodism: approved methods only must be used True of all(?) approaches in the textbooks These assumptions outlaw approaches using fictions of any kind. OK for common sense approaches, for TV programs, but not for serious research!
Conclusions Analysis of hypothetical or fictional scenarios is important in almost all fields –Eg for exploring proposed innovations; testing models in different situations Go beyond what has happened and look at what might have happened. But this is contrary to the approved methods for doing research … so … These approved methods need extending to allow various types of fictions as “data” Need a framework of methods for assisting with, and legitimizing, the exploration of possibilities.