Discussing the Undiscussable: Book Review
I came across the work of Chris Argyris at the start of the year and in a twitter conversation with Benjamin Mitchell he suggested that Bill Noonan’s 'Discussing the Undiscussable' was the most accessible text for someone new to the subject.
In the book Noonan runs through a series of different tools that Chris Argyris originally came up with for helping people to handle difficult conversational situations more effectively.
I really like the way the book is written.
A lot of books of this ilk come across to me as being very idealistic but Noonan avoids that by describing his own mistakes in trying to implement Argyris' ideas. This makes the book much more accessible to me.
He also repeatedly points out that even though you might understand the tools that doesn’t mean that you’ll be an expert in using them unless you spend a significant amount of time practicing.
These were some of the ideas that stood out for me from my reading over the last few months:
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Advocacy/Inquiry - Noonan suggests that when we’re discussing a topic it’s important to advocate our opinion but also be open to people challenging it so that we can learn if there are any gaps in our understanding or anything that we’re missing. This seems quite similar to Bob Sutton’s 'Strong Opinions, Weakly Held' which I’ve come across several times in the past. One anti pattern which comes from not doing this is known as 'easing in' where we try to get the other person to advocate our opinion through the use of various leading questions. The problem is that they tend to know exactly what we’re doing and it can come across as being quite manipulative.
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The Ladder of Inference - I’ve written about this previously and it describes the way that humans tend to very quickly draw conclusions about other people based on fairly minimal data and without even talking to the other person first! When Jim and I worked together at ThoughtWorks University we were constantly pointing out when the other was climbing the inference ladder and it was quite surprising to me how often you end up doing so even when you don’t realise it! What I find most interesting is that even when I was absolutely sure that my inference about a situation was correct it was still frequently wrong when I discussed it with the other person. They nearly always had a different perception of what was going on than I did. I think it’s a step too far to believe that I won’t ever climb the inference ladder again but it’s useful to know how frequently I do it so at least I’m aware that I might need to climb down from time to time.
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Recovery time - There is constant reference throughout the book to our recovery time i.e. how quickly do we realise that we’ve made a mistake by participating in a defensive routine. Argyris' tools are quite useful for helping us to reduce our recovery time because they are reflective in nature and when we reflect on a situation we tend to see where we’ve gone wrong! Noonan suggests that it’s inevitable we’ll make mistakes but the key is to try and detect our mistakes sooner and then hopefully reduce the number that we make.
Of course there are several other tools that Noonan describes, such as the left hand right hand case study approach, double loop learning, espoused theory vs theory in action and the mutual learning model.
I still make loads of the mistakes that the book points out and I’ve noticed that I only really reflect on how my conversations are going when I’ve been flicking through the book relatively recently.
It’s also useful to be hanging around other people who are studying Argyris' work as you can then help each other out.
One of the initial books that Chris Argyris published describing these tools was 'Action Science' (available as a free PDF).
I initially tried reading that before this book but I found it a bit hard to follow but I’ll probably try it again at some stage.
About the author
I'm currently working on short form content at ClickHouse. I publish short 5 minute videos showing how to solve data problems on YouTube @LearnDataWithMark. I previously worked on graph analytics at Neo4j, where I also co-authored the O'Reilly Graph Algorithms Book with Amy Hodler.