It hardly feels like I need to write a review on this book, as I often hear to recommended at conferences. However, chatting to a few peers in customer insight leadership roles, I realise that many of you have still not read this classic or have stalled part way through reading. So, I hope this helps motivate you.
The first point to admit is this is not as easy a read on Behavioural Economics (BE) as more approachable writing styles like “Nudge” by Richard Thaler. You do get used to the style through the book but there are a couple of things that make it harder for the business reader, the depth of theory that is covered and the amount of case studies (which provider an insiders view of challenging accepted wisdom within academia). I also found that after having read ‘Nudge’ I was initially a little frustrated that this book is not structured around a simple list of biases. It appears to be deliberate as Daniel Kahneman wants you to understand the principles not just pick up some buzzwords.
That said, this is well worth reading. From the initial explanation of System 1 and System 2, through the evidence provided on multiple biases, to how poorly basic statistics and logic are applied in our decision making; this book has much to share. The deliberately more narrative style of the book also does reward the persistent reader, as you begin to see how models and principles interact and build on each other (like loss aversion and framing).
The other advice I would give if that this is a good guide to the pitfalls to beware of when making decisions or seeking to influence key decisions in your company. In that regard it goes much wider than just a textbook on Behavioural Economics. For instance the evidence Daniel shows of a failure to regress to the mean in forecasting is often beyond the scope of popular BE but very relevant.
I would recommend any Customer Insight leader to read this work. This is particularly important for those working within Financial Services, where your regulator requires consideration of how consumers really make decisions and where your research team can help your analysts with interpretation.