Malcolm Gladwell's new book, Blink , is a good read -- it reads like a story, and has lots of good vignettes in it. Gladwell is a popularizer, which is not a bad thing to be, and he does it well. He scans widely for information, and assembles it in a way that makes it accessible and memorable. And even if you are pretty well read in the area of psychology, you're likely to pick up some new ideas.
Mr. Gladwell doesn't really say a lot about what to do with the insights he has gathered. Brace yourselves for lots of misinterpretations and strange justifications based on this book.
There are lessons and implications to be drawn from Blink for the customer experience manager -- people like us.
1. The judgments of sales staff
One of the stories that resonated for me was of the super car salesman Bob Golomb who said "You cannot prejudge people in this business". A successful bank branch manager I knew had started out managing rock bands, and he said almost the same thing to me: "One thing I learned in the music business is not to judge people by their appearance". It's a good lesson for anyone who wants to make a living by serving or selling to others.
Most of the book is about how good we are at the snap judgment. But Gladwell also makes the point that our rapid judgments are not always accurate. This could not be more true when we are talking about the retail environment. Retail banking is a particularly good example.
We can look at people with the visible accoutrements of success (nice clothes, nice car, jewelery) and assume they have money to invest. And we can look at others who appear of more modest means and assume they do not. In fact, those that spend a lot frequently don't save a lot. This has been pretty well documented in research, such as The Millionaire Next Door . It's counter to most people's intuition. But savers are savers -- that's why they have money to invest.
About four years ago I was studying affluent investors who had bought or sold stocks or mutual funds online. One of the biggest surprises was that you would never pick these people out of an airport waiting lounge. I remember thinking about one woman in particular: she was around 50 years old, spoke English with a thick Eastern-European accent, and was dressed in very non-descript clothing, including an overstuffed purse. Not the young tech-savvy professional male that everyone envisioned. If she had said she kept her money in a coffee-can, it would have been easy to believe. I wondered how she had got set up with an on-line account. I was pretty sure no one in her bank branch had suggested this, and no one had called her up to offer her one.
The instincts of most front line staff in retail vary widely in their quality. Relying on them to decide who to serve well is a recipe for missed opportunities. That's why you need to serve everyone to a standard of service that is established by the enterprise, not the individual. If you don't, you are counting on the individual learning, life experiences and instincts of front line staff to be superior to that of your best market strategists and customer experience researchers.
2. Using statistics to improve judgment
Gladwell's story about the doctors trying to diagnose heart attacks at Cook county hospital illustrated that reducing the complexity of data and introducing decision rules can radically improve decision outcomes, even among highly trained individuals. This isn't only true for health care, of course.
This is very much like the process of making credit decisions for everything from a credit card to whether or not you can cash your cheque without a "hold funds".
When banks and credit card companies started using mathematicians to build risk algorithms, what became really clear was that individual judgements based on personal experience were markedly inferior to those based on data. To create a system like this, it does help to start with an expert, who tells you what kinds of patterns they look for. Having got the patterns, you grind and regrind your data on an ongoing basis to look for ways to improve the decision rules.
There are two types of errors that can be made here, called, appropriately enough, Type I and Type II errors. You can accept a credit risk you should reject (Type I) or you can reject a credit risk you should accept (Type II).
People who work in these environments typically worry much more about making Type I errors (generating a bad loan) than they do about missing revenue opportunities (Type II errors). In Gladwell's context, they worry more about sending away a heart attack patient than they do about keeping a well person in a cardiac care bed.
When this type of decision system is introduced, there can be great knashing of teeth over it, as people feel their control is being eroded. But systems like these are much more fair to to customers than the old way -- they don't have race, religion or gender prejudices, and they improve overall returns, while generally improving productivity.
When you look at your service business, watch what kinds of decisions are being made by front line staff. How can you help them improve their decisions using decision rules? And can you condense these to a 3x5 index card?
3. Appearances, hiring and promotion
Gladwell uses the example of US President Warren Harding and classical music auditions to make the point that we judge someone's competence by their appearance at our peril.
When organizations shift their focus from administrative & bureacratic to sales & service they experience some dramatic eye-openers. One of the most dramatic things I have observed in these situations is that our first impressions about who is doing a good job on sales and service are rarely on the money once we really start to track data. Managers tend to see outgoing, energetic extraverted individuals as good sales and service people. And sometimes they are. But not always. And quiet, conscientious, steady-Eddie individuals often achieve more with their systematic focus than we suspect.
It is only when organizations start to track real data does it become clear who is actually paddling the boat and who is catching some rays on the deck.
Using the numbers forces us to try to treat people fairly, whether we like them or not.
These problems of biased judgment are more nuanced when it comes to executive level career advancement, and are affected not just by height, but by all the elements of cultural fit. These are the elements that tend to work against those who fit differently: women and ethnic minorities. But that's a bigger topic than we can tackle today.
An entertaining and thought provoking book, and what more can you ask of a business book?