The cheerleader effect
I spend my entire professional life averaging out unattractive characteristics. Let me explain.
Take a look at this picture.
Most people, when asked to rate the ‘attractiveness’ of the three women above, will rate them more highly when they’re presented in a group than when they’re presented individually.
This well-researched phenomenon is called the ‘cheerleader effect’: it’s a cognitive bias that causes people to perceive individuals as 1.5%–2.0% more attractive in a group than when seen alone. And, it applies to all human groups, men and women (and not just cheerleaders) and even to cats.
What this got me wondering, though, was whether this ‘averaging out of unattractive characteristics in groups’ occurs with ideas arising from groups, not just physical appearance. Having run thousands of group processes over decades, I have noticed that there’s an obvious ‘smoothing out’ of eccentricities and outlier positions. Put another way, I frequently see groups self-moderate and bias towards centrist views.
Now, is this a problem?
If the cheerleader effect does exist in group dialogue, does it weaken the capacity of groups to reach conceptual agreement on important issues? My own view is that, on the contrary, it strengthens it, as the studies on cheerleader effects suggest that it relies on three cognitive phenomena:
our perceptual systems are designed to take in ‘ensembles’, or groups, not individual pieces of data;
perceptions are biased towards an average, with our visual systems especially automatically calculating a ‘mid point’;
from our earliest development, we recognise ‘prototype’ images (like faces), that aid our social interaction, so we look for ‘averagely attractive’ faces (or dialogue) that most fits this preference.
Put these all together, and I’m persuaded firstly that the cheerleader effect does occur in many situations where people are asked to evaluate not physical attractiveness, but the attractiveness of a proposal, an idea, or a concept. But, more importantly, I’m also persuaded that this is a good thing: as our capacity to get anything done for societal benefit relies upon our ability to see ‘ensembles’ not individuals, appreciate mid-points not outliers, and build up protoypes that serve our social interests.
Question: How can you actively use the cheerleader effect to gain widespread support for a desired initiative in your organisation?
Telling your story
You know how hard it is sometimes to explain what you do to someone you’ve just met?
Well, just this week, I found a fascinatingly simple way to convey this, that has implications for how we explain the value propositions of entire businesses or organisations.
Troy and Zara Love are originally stand-up comics, and nowadays run large-scale events for companies. I saw them in action at a client’s leadership day and they asked people to explain their work to a partner. People foundered and um’d and ah’d, until Zara explained a simple three-step formula.
“You know how . . .”
“Well, we . . .”
“So that . . .”
The client was the Red Cross’s Lifeblood service, and for them one version of the spiel would go something like this: “You know how we all rely on blood to stay alive? Well, we make sure that there’s plentiful blood — and other biological products — in hospitals, so that people stay alive, especially in critical, life-saving situations”.
The keys are lead with a question that can ONLY invite a ‘yes’ response, and make it plain English (even for a professional audience).
So, for my own strategy consulting work, I could say, “You know how many leaders have big ideas that are hard to turn into reality? Well, I help them wrestle with those ideas until they’re simple, so they can be communicated to other people and become real”.
Question: What happens when you ask your team to try this way of explaining what you do?
More, or less
A nod of admiration from me to you if you know what this is:
It’s a page from the Domesday Book, the 1086 survey of William the Conqueror’s holdings. Its purpose was to calculate the dues owed to the King, what today we’d think of as taxation, but it also formed the basis for property titles. It also happens to be the earliest British example of an exhaustive tally of a population, and it includes almost a quarter of a million people.
I spent an hour browsing through a copy this week (in modern English) and marvelled at the density of information within. A typical entry reads, “In [the village of] Mymms there is land for 13 ploughs. In demesne [are] 4 hides, and there are 2 ploughs, and there can be a third. There 17 villans with 8 bordars have 10 ploughs. There are 3 cottars and 1 slave, pasture for the livestock, [and] woodland for 400 pigs.”
Now, fast forward a thousand years and think about what density of information we hold today.
We are not only counted as individuals but our transactions are counted too, as are our movements. So, on my fairly ordinary trip from Melbourne to Canberra this week, there are records of my Uber ride, my use of the tollway to the airport, my security screening, my baggage, my use of the lounge, my flight passenger data, and no doubt much more.
Unlike a thousand years ago, we’re drowning in data, most of which we’re unaware of. And, much of which the owners of that data are unaware of. Every one of us creates about 2 megabytes of data every second and in the last two years alone, an astonishing 90% of the world’s data has been created. By some estimates, 99% of data generated is never analysed, never even accessed.
This presents a challenge to all of us running, or advising, organisations. If data was any other resource (like money, or people, or even paper), if you used so little of it, you’d be advocating streamlining it radically. Why don’t we do the same with information?
Question: What patterns can see using today’s greater information density?
I enjoy your enjoyment of reading, so do click the ‘heart’ and let me know you’re out there. And, if you feel inspired to drop me a line, in the comments below, or by other means, do that too.
Until we meet again next Friday, spend the week noticing the attractiveness of groups (of people, and cats), and enjoy seeing the patterns in the rich data sets we’re all generating every hour of every day.
Andrew
Thanks Andrew, I especially loved the "You know how... well we... so that..."