It’s my first time at Nudgestock, Ogilvy’s behavioural science conference.
I’m in a room with 450 people, a lucky dip of marketers, academics, researchers, students, brand and operations peeps from the private, public and third sectors.
We’ve all travelled to Folkestone, which is sleepy, welcoming. It’s a 10 minute amble through the faded Victorian grandeur to Leas Cliff Hall. Beyond the stage and I can see the sea, which is unexpectedly turquoise.
Today is about the cross pollination of ideas. The presentations reach across industries and disciplines. Our job is to laterally apply these, to connect the dots. Rory Sutherland is the host and compere, his charisma contagious. We sip our coffee and try and take it all in.
Here are my takeaway ideas:
1) Big data contributed to Nokia and Hillary Clinton’s failure
Management need generalities to survive. The context-free certainty of a spreadsheet is alluring as it offers illusory control. “No one gets fired for being logical”
But big data is backwards looking, extrapolating from the past. Cost benefit analyses by McKinsey were behind Nokia’s strategy to focus on the featurephone rather than the smartphone. By comparison, an anthropologist seeing refugees sacrifice half their income to get hold of a smartphone pointed to its game-changing potential. But McKinsey had more datapoints: they won the argument. As Sutherland pointed out “’Iceberg! Dead ahead!’ is one data point… but an important one!”
Similarly, Bill Clinton suggested the Hilary campaign team visit the Midwest to take the mood of the people in 2016. Something felt amiss. The request was rebuffed by the with“my data beats your anecdotes.” We all know how that turned out.
2) Don’t look for rules, look for patterns
Common patterns that make sense in one context can be used to understand others.
There is no grand theory which explains all human behaviour. For the management cadre a set answer based on a mathematical model is more pleasing than stitching together lots of subjects to try find the truth. John Kay pointed out, when you hear economists say it is “The fault of the world, not of the model” you know you have a discipline in turmoil. We should embrace a wider spread of models to explain why people do what they do. Sutherland and Kay are keen on evolutionary psychology (see #9).
“The drive to be rational has led people to seek to find political and economic laws which are akin to the laws of physics — universal, unchanging over time and applicable at any scale. Experts love such universal principles — as they allow them confidently to pronounce on things of which they have no direct experience.”
3) Context & scale often determine how people think, feel and act – not the rational if/then rules modelled by economists
This is best summed up by a quote from Vincent Graham to explain his view of politics:
‘At the federal level I am a Libertarian. At the state level, I am a Republican. At the town level, I am a Democrat. In my family I am a Socialist. And with my dog I am a Marxist — from each according to his abilities, to each according to his needs.’
4) Real world social networks have huge power: what your friend’s friend’s friend experiences will affect you
Nicholas Christakis (Director of the Human Nature Lab at Yale) summarised 30 years of research into 40 minutes. His research provides evidence to show if you put something in a network it will make more of it – whatever it is. Love, kindness ideas – or ebola, fake news or hate. But it has to be seeded – need to start the thing off.
Connections and the structure of network matters. Take graphite and diamonds: these are just carbon atoms with different arrangements. Connected one way they are soft and dark (graphite) or hard and clear (diamond) – but crucially, these are properties of the connections not the atoms themselves.
It is the same with human social groups. In one context you can connect in positive manner and achieve good. Or vice versa. Good or bad outcomes however can be seen as emergent properties of the network, not properties of individuals. The whole is greater than the sum of its parts.
In this conception innovation and other positive outcomes come from ties not the people themselves. Our experience of the world depends on connections!
5) There are 3 strategies to affect a social network
§ Connection – re-structure the wiring diagram, who is connected to who;
§ Contagion – changing the flow (e.g. seeding an idea);
§ Position – changing the location (e.g. using the existing structure & ensemble of individuals, can we reposition people to maximise benefit – like a seating chart)
6) The adoption of new products/services is non-linear, and often follows an S shaped curve
Network modelling shows the diffusion of innovation follows an S-shaped (“sigmoid”) curve (see pic):
§ In the beginning no-one you know is using a product/service;
§ You see others using it so you try it;
§ Suddenly everybody is using it;
§ Growth plateaus.
In other words: social proof accelerates growth.
Q: If the adoption of a new product or service is non-linear, how should we phase marketing budgets? There is a danger investment is pulled too early. Clients may have more patience knowing about the sigmoid adoption curve.
7) Tinder’s rise was exponential
US dating app market share 2013-2014: data courtesy of 7 Park Data
Eliding nicely with Christakis’ themes, Mark Brooks gave us a 10 minute presentation covering the 20 years he has worked in the online dating business. Tinder was a game changer because swiping is fun, automatic, a game – system one all over. When you think about it, the paradigm shift it introduced is obvious: almost overnight, completing a match.com profile feels like writing your UCAS form, system 2, yawn. He flicked past his market share chart so I googled this one. Wow.
8) Facebook dating is the next game-changer
Facebook are launching a dating service imminently. It can prevail because it addresses the three prevailing challenges dating sites face.
§ The feedback problem: sites don’t know when they have been successful. People just leave the site. Facebook will know who, when, and how long resulting relationships are.
§ The limited information problem: matching based on what people say they want rather than what is important. Facebook has every conceievable attitudinal, behavioural and psychographic dataset.
§ The continuity problem: you do a good job and you lose your customers. A peverse incentive. Brooks thinks the future of dating sites is to move from helping you “keep it together” not just get it together – helpful nudges and relationship support (like “it’s your anniversary, why not try this place she likes…”)
9) Human intelligence is collective, not individual
John Kay discussed evolutionary psychology, giving us comparative insights into our species. Consider the comparative development of primates: two chimpanzees don’t do so much as carry a log together. Humans can build Airbuses: coordinating tens of thousands across continents in an act of decentralised wonder. No 1 person can do it, only the collective working together. That is the nature of human intelligence, not found in any other mammal species. It is what makes us different. A conference is collective intelligence in action.
10) Business coaches are using behavioural science to help people in the workplace
Caroline Webb, author of the bestselling How to Have a Good Day discussed how under stress you switch to a mode of selective attention. Information automatically and unconsciously gets filtered. We’re not aware of this process by definition (that’s the whole point – it’s a survival mechanism!)
The kicker: under stress you notice things that are already top of mind for you: so if you are in a crap frame of mind, you’ll not be picking up positive cues. This is confirmation bias writ large.
You can solve this by consciously resetting your perceptual filters, boosting your sense of competence and control:
§ What do I know for sure? (e.g. I have speaker notes for my talk)
§ What can I shape or control? (e.g. my attitude)
§ What are some ‘no regrets’ actions? (e.g. I can still make my train if I leave now)
11) You can hack your future memories: apply the peak end rule
The peak end rule says we tend to remember an experience according to its most intense moment and the way it ends, rather than the experience in its entirety. You have control over how your day ends: just think about 3 good things that happened that day to manufacture your memories. In Webb’s words: “The way you remember your days is the way you remember your life” What could be more important than this?
Takeaway: why not apply this at the end of a workshop or debrief: what are the 3 things you have learned today?
All great stuff. Thanks to Ogilvy for organising. Time for a lie down.