In last week’s Pocketblog, we met a thinker, Roselinde Torres, who compels leaders to ask difficult questions of themselves. Chris Argyris was another thinker – an academic this time – who demands we ask difficult questions.
Argyris’ early academic career brought him into contact with the great psychologist, Kurt Lewin, and culminated in academic posts, first at Yale (1951-1971) and then at Harvard. He was a behavioural scientist who devoted much of his research to understanding organisational behaviour and learning, noting that:
‘individual learning is a necessary but insufficient condition for organisational learning’
His early work focused on the practice and development of T Groups; a form of training (the T of T Group) in which managers are able to learn through social interaction. These were popular in the 1960s and 70s for the success they had in shifting interpersonal behaviours of participants. However, Argyris and others became disenchanted as evidence grew that the impact of these interventions was not sustained back in the workplace.
This led Argyris to theorise that the way we behave within organisations is different from the ideas we claim to profess. He labelled the two sides of this distinction: ‘theories in use’ for what we do, and ‘espoused theories’ for what we say. Our behaviours – theories in use – are driven only partially by espoused theories, and to a greater extent by fears, pride, entrenched patterns and the need to conform. Indeed, he suggested that we don’t just behave as we do, rather than as we profess; but we are often unaware of the gap.
His most famous single contribution, articulated in his book, co-written with Donald Schön, called ‘Organisational Learning‘, was the idea of ‘double loop learning’.
Argyris argued that reasoning needs to take pride of place as the basis for decision-making. However, the prevailing model of learning that he and Schön defined as ‘single loop learning’ is an impoverished approach.
In Single Loop learning, we look at the results of our actions and re-think the strategies we chose.
The flaw in this, they argued, is that our chosen approach comes from a deep seated set of interpretations, assumptions, values and models. What we should be prepared to do is to challenge those and search for better, more reliable assumptions and models. This is Double-Loop learning.
Argyris further pointed out that learning comes from either a match or a mis-match. If our actions produce the desired result, then we can learn from the well-selected behaviours. If they do not, then we can learn from the mis-match either by correcting our actions (single-loop learning) or by revising the governing variables (assumptions) that led to our choice of actions (double-loop learning).
You can learn more about Argyris and Double Loop Learning on the excellent infed website.
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