I'm writing a paper at the moment about the stand-off between Management Science, which has always grounded itself in the Systems theory tradition (think of Beer's use of Ashby and Shannon), and 'pure' cybernetic/systems theory which continues to develop, although rather removed from operationalised practice.
There is a problem. This rests in the fact that Management Science, despite some successes in the workplace (but more failures) rarely revises its own theoretical presuppositions. Instead it validates itself on the impact on business health - profits, productivity, wellbeing, etc. That is considered justification for the validity of the theory which underpins the methodology. But there is usually little causal connection that can be defended between the impact of systems interventions and the underlying theory of the methodology.
The paper argues that there is a need to 'close the loop' in management science interventions by assessing the meaningfulness of those interventions to the people who are subject to those interventions. It argues that meaningfulness can be assessed through analysing the communications in the organisation (something which I've been talking a lot about recently in my blog). If the methodology for analysing meaning produces results which can be compared to the predictions of the underlying theory of the systems methodology, then there can be a reasonable comparison of where the theories have explanatory and predictive power, and where they do not. That, I think, might help to make management science methodology a bit more scientific (I think the 'science' label current is misplaced - it simply alludes to the fact that the management science methodologies are 'inspired' by systems science, rather that denoting a branch of enquiry intent on improving and developing its own knowledge base).
But beyond the paper, I have begun to think that there is a pattern between those disciplines which practically orientate themselves in the world - for example, Management Science methodologies - action research and the like - and those disciplines which seek to develop a more solid theoretical grounding, but often not practically realised: economics springs to mind as a classic example. Yet knowledge and action in these cases is deeply entwined: successful Management Science yields positive economic results. But who gets to claim the credit for positive economic results: economists? or Management Scientists? (or technologists? or teachers?)
Neither economists of Management scientists have a legitimate claim to cause positive results, because neither has the capacity to causally link things that happen to why they think things happen. Keynes's theory, for example, postulates about the motivation for spending and saving, and suggests economic policy as a result. If growth results, Keynes will say "I told you so!" and (let's say...) he's rather pleased with himself! But exactly what did he tell us? Does it really fit the deep story of what happened? How can we find out? How can we take a closer look at the theory?
The issue rests on our ability to analyse and make sense of the messy business of reality. In my recent posts, I have been arguing that the messy business of reality is meaning. In a world of immensely rich data, all of which must have been meaningful to someone at some point (just as this blog post is meaningful to me right now), it may reasonable to assume that the meaningfulness of information is left as an imprint on the form of that information. Uncovering the imprint may be an important step to bridging the gap between knowledge and practice, and making our theories better.
There is a problem. This rests in the fact that Management Science, despite some successes in the workplace (but more failures) rarely revises its own theoretical presuppositions. Instead it validates itself on the impact on business health - profits, productivity, wellbeing, etc. That is considered justification for the validity of the theory which underpins the methodology. But there is usually little causal connection that can be defended between the impact of systems interventions and the underlying theory of the methodology.
The paper argues that there is a need to 'close the loop' in management science interventions by assessing the meaningfulness of those interventions to the people who are subject to those interventions. It argues that meaningfulness can be assessed through analysing the communications in the organisation (something which I've been talking a lot about recently in my blog). If the methodology for analysing meaning produces results which can be compared to the predictions of the underlying theory of the systems methodology, then there can be a reasonable comparison of where the theories have explanatory and predictive power, and where they do not. That, I think, might help to make management science methodology a bit more scientific (I think the 'science' label current is misplaced - it simply alludes to the fact that the management science methodologies are 'inspired' by systems science, rather that denoting a branch of enquiry intent on improving and developing its own knowledge base).
But beyond the paper, I have begun to think that there is a pattern between those disciplines which practically orientate themselves in the world - for example, Management Science methodologies - action research and the like - and those disciplines which seek to develop a more solid theoretical grounding, but often not practically realised: economics springs to mind as a classic example. Yet knowledge and action in these cases is deeply entwined: successful Management Science yields positive economic results. But who gets to claim the credit for positive economic results: economists? or Management Scientists? (or technologists? or teachers?)
Neither economists of Management scientists have a legitimate claim to cause positive results, because neither has the capacity to causally link things that happen to why they think things happen. Keynes's theory, for example, postulates about the motivation for spending and saving, and suggests economic policy as a result. If growth results, Keynes will say "I told you so!" and (let's say...) he's rather pleased with himself! But exactly what did he tell us? Does it really fit the deep story of what happened? How can we find out? How can we take a closer look at the theory?
The issue rests on our ability to analyse and make sense of the messy business of reality. In my recent posts, I have been arguing that the messy business of reality is meaning. In a world of immensely rich data, all of which must have been meaningful to someone at some point (just as this blog post is meaningful to me right now), it may reasonable to assume that the meaningfulness of information is left as an imprint on the form of that information. Uncovering the imprint may be an important step to bridging the gap between knowledge and practice, and making our theories better.
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