Do you have time to think in your leadership role?
I first read this book over a decade ago, but it made such an impact that I have kept coming back to it over the years.
It is not specifically about customer insight, although it’s implications for how to create a ‘thinking environment‘ should be of interest to researchers and those designing customer experiences. However, for me the biggest lessons from this book are for leaders (including customer insight leaders).
As you read through the initial chapters on the ten components of a thinking environment, it’s easy to be struck with how different these are to the typical corporate working environment. Giving colleagues time to think for themselves, use of appropriate incisive questioning to help them problem solve and giving regular appreciation can all feel very alien from being ‘part of the machine’. (more…)
It may seem like one of the curses of modern corporations but org design and regular reorganizations are now a fact of business life. I’m sure as an insight leader you will have seen your fair share.
As you’ve risen up the hierarchy you’ve probably changed in your role with regard to these events; from recipient to author. If you haven’t experienced this then I would encourage you to seek to be an author of such change.
From my experience two major opportunities exist for customer insight functions in this regard.
The first is to bring together the different technical areas who can best collaborate to provide deeper and more actionable insights. These include teams that are often located in different functional “silos”.
In line with my definition of Customer Insight, I would recommend bringing together: Customer Data, Analysis & Modelling, Research and Database Marketing teams. Suitably integrated and with an outcome focussed culture, these teams can together for an ‘Insight Engine‘ that produces not just technical output but actions that result in both commercial impact and improved customer experiences. (more…)
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.
Leading insight for a major life & pensions provider for many years, you become painfully aware of the added difficulty in reaching strong insights on B2B customers. Although at first B2B insight can just appear less developed as a market, with a much smaller quality data provider market and still more of a focus on sales management and brand (almost where B2C was 5-10 years ago); on reflection this is not the case.
It is more challenging to develop as robust analysis (mainly due to data challenges driven by both less capture and matching challenges) and more challenging to interpret robust research (mainly due to multiple relationships and opaque decision making hierarchies/influences). However, on closer inspection, some of the challenges being attempted for B2B insight are both more challenging and able to create a bigger commercial impact if achieved.
Earlier this year I attended an event run by them entitled “The Great Debate” (part of a series of such events), with this one being held at Greenwich. I was reticent to write too much on my thoughts from this; as it is a Chatham House rules meeting. However, Peter has usefully shared the key anonymised lessons learnt on his blog. The above link is well worth reading.
Any other thoughts from those who like me have had the challenge of both B2B and B2C insight? Did others also find the approach to NPS needed to be tweaked? Do reply with your comments.
Following my presentation at Edgbaston, last week I also presented at the Gloucestershire County Cricket ground in Bristol. Clearly the CII favour the view over a green for their regional market forums. Anyway, it was another opportunity to share my thoughts on Behavioural Economics and why it matters for Insurers. Another positive response and good engagement from a mixture of insurers, brokers and related agencies; which promises well for this industry engaging with the FCA’s challenges in this area.
To help spread the word further, below I share the presentation that I used:
Happy to offer training or consultancy to companies wanting to engage with this challenge. To my mind expertise in this area is a natural and needed fit with customer insight teams within Financial Services.
I believe in the importance of data visualisation, both because most people can more readily understand a visual representation than tables of numbers and because it is a useful language with which to communicate not just analysis but story. In other words, the challenge to appropriately visualise data or analysis, encourages the analyst to get closer to insights.
Anyway, I’ll blog more on that wider topic another time, for now I just wanted to share links to two agencies whose work on infographics have impressed me. If you’ve not come across them before, see if these spark any creative ideas…
There is always a risk that fashion obscures function, so I am aware of the risk that some people now equate data visualisation with infographics, which would also be a mistake in my book. So, as promised, more on data visualisation to following a later post, with the obligatory reference to Edward Tufte.
For now, please do feedback with your experience of infographics. Any tips?