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Mark Earls – From “me” to “we”

Thanks to Mat kindly donating his ticket, I was able to go and see Mark Earls give a seminar entitled From “me” to “we” at the Royal Society.

herd by mark earlsRather shamefully, I am still yet to read Herd – the book (and associated research) on which the talk was based. This is despite regularly reading the Herd blog and even having a copy in the Essential library. As I said, shameful.

Despite this, I think I was the target audience. Along with a Q&A only notable for the rather aggressive questioning of a lady accusing Mark of ignoring “the female perspective”,  the session offered a fairly gentle precis of the book’s central theory which, if I had read it, I would of course have been familiar with.

The talk

A tenet of the book is that we’re bad at changing other people’s behaviour. To highlight this, Mark recalled a few statistics from his research:

  • Only 10% of new products survive longer than 12 months
  • Only 30% of change management programmes begin to achieve their aims
  • Mergers & Acquisitions lessen shareholder value two thirds of the time
  • No government initiative has created demonstrable and sustainable change

This is particularly worrying because behavioural change comes before attitude change – our thinking comes after the fact. We (post)rationalise rather than act rationally.

Therefore, in order to change attitudes, we need to change behaviour. And to be able to do this, we need to understand who we are. Only then can we can create solutions that work.

The Herd thesis draws upon the Asian culture of believing that humans are naturally social. We are fundamentally social with only a bit of independence, not vice versa.

Although it doesn’t sound particularly controversial, this thinking does run contrary to some well established tenets of both marketing and social theory.

According to Mark, thinking is much less important in human life than it seems. He likens us and thinking to a cat in water – we can do it if we have to, but we don’t particularly like it.

This is because it is easier to follow than think. We know our judgement is fallible and so we outsource the decision by following the crowd. But while this may work in some situations – many illustrated by James Surowieki – it is also arguably a contributing factor to the financial crisis, as financial institutions copied one another without comprehending the implications.

We therefore need to design our theories and tools to accommodate this social behaviour. It is much more rewarding to understand how social norms are created and perpetuated than it is to work on the assumption of cogito ergo sum.

Some initial thoughts

While brief, the talk certainly conveyed the need for me to read the book fully. Perhaps then some of my questions regarding the theory will be answered.

In particular, I’m interested in knowing where movements originate and whether this herd behaviour can be predicted.

For all the sheep, there must be a shepherd somewhere. Are these shepherds always designated as such – the almost mythical influentials – or do we alternate between thinking and following?

Rarely are our choices as clear cut as choosing whether to join the corner of the party where people are talking rather than the one where people are sitting in silence. Instead we have multiple choices and herds – how do we choose?

Is it a level of proximity? In the Battle of Britpop, Northerners sided with Oasis and Southerners with Blur? However, I’m from the Midlands, so was my choice one of the rare occurrences of rational choice (which would make a rather unconvincing deus ex machina) or is it purely random?

If random, then the work of Duncan Watts becomes pertinent. His modelling has suggested that in situations where groups vote up and down their favourite songs, there is no objective winner. Different simulations create different patterns. Purely random.

This creates difficulties for researchers as we like our statistical certainty. We like to have a set answer that we can post-hoc explain given the evidence. Duncan Watts’ research would suggest that research tools that build in mass opinion – such as crowdsourced tagging or wikis – are effectively meaningless. Rather than ultimately deviate towards a “correct” answer, they simply reflect the random order of participation and interaction.

Can mass behaviour be effectively incorporated into a research programme? I’ll report back with some thoughts once I’ve read the book


We’re bad at changing other people’s behaviour

Only 10% of new products survive longer than 12 months

30% of change management programmes begin to achieve their aims

Mergers & Acquisitions lessen shareholder value 2/3 of time (pwc)

No government initiative has created demonstrable and sustainable change

Behavioural change comes before attitude change – thinking comes after the fact

In order to change attitudes, change behaviour

We need to understand who we are so we can create solutions

More rationalising than rational

Cognitive outsourcing – memory is a distributed function so only remember slivers

We are fundamentally social with a bit of independence, not vice versa

Asian culture is inherently social

Gandhi said that humans are a necessarily interconnected species

Thinking is much less important in human life than it seems

“lazy mind hypothesis”

We can think independently, we just don’t like it – like a cat to water

Behave according to other people’s actions e.g. go to busy shops

We know our own judgement is fallible so “I’ll have what she’s having” – wisdom of crowds or financial crisis

Leads to social norms

Need to design our theories and tools to accommodate social behaviour

Genesis random – Duncan watts

Is it proximity that leads us to follow a herd, or example of using rationally weighing up the pros and cons

Herds originate from somewhere – must be a leader. Are these leaders the same in each situation, or are we all capable of being shepherds

Research application – crowdsource answers. But random – no statistical certainty as only one situation

Wikis to collate group opinion?

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12 Responses

  1. Watts’ arguments are a little more subtle I think – basically he’s suggesting that success breeds success, but that the initial seed of that success may well be close to random and that “quality” isn’t a particular factor.

    I’m definitely becoming more Wattsian (I’m in Duncan’s herd!), and I think the social internet – with its reduction of “social interaction” to rating and ranking – amplifies the effects he detects. In essence it gives us a lot more opportunities to follow.

    I’m not sure whether Earls would think that’s a good or bad thing – I guess I need to read the book.

  2. Cheers Tom – I’m evidently only superficially aware of Watts’ hypotheses.

    I may be wrong, but I don’t think Earls was making a qualitative judgement as to whether following is a good or bad thing. Merely we should recognise its existence and consider its effects when devising policies and strategies.

  3. This all sounds far too interesting – both Earls and Watts – so as you suggest. I probably ought to read the book(s) before weighing in. Oh, go on then…

    How does Watts align what he’s saying with the incredible analytical power granted by well-designed aggregators and interpreters of other web content? Isn’t this at the heart of Googlenomics (or whatever you want to call it)? What is different about opinions? Can social media not become an extra resource for (admittedly limited) quant reserach, with patterns or the lack of them that can then be put into context with some intelligent groundwork?

  4. All good questions Dave, though I’m not sure on the answers! Why, for instance, do some videos become “viral”/”spreadable” but not others. Luck in the way it is distributed across the social web, or is there a more definitive pattern?

  5. My understanding of Watts’ POV on virality is basically that the more you seed it the more likely it is to spread – but I haven’t read his stuff on this.

    I don’t think there’s any great misalignment between what Watts is saying and the success of aggregators.

    Watts’ point is that people tend to check out what other people are seen to be checking out. So if you have 5 things, A B C D and E, and 101 people look at D compared to 100 each for the others, D goes to the top of the rankings. More people then look at D because it’s at the top.

    What Watts did was to run the experiment several times and he found that this initial advantage breeds sucess whichever of A B C D and E receives it. He also asked people to rate the different items (in his experiment it was songs) and found that there was little or no correlation between quality and success.

    This is all from memory so apologies if I’ve got crucial details wrong.

    Now, the thing about the aggregators we’ve got is that we don’t get to re-run the experiments again and again: we get one set of results, with all the historical initial advantage long built in, and we have to judge the success of the aggregators based on that. My – perhaps cynical – hunch is that they’re likely to FEEL tremendously powerful and useful WHATEVER the results are, because of the cat-in-water stuff Simon quotes Earls on above!

  6. I appreciate I’ve not lived in Asia for too long – but whilst the herd mentality exists [from a public perspective] my view is that [1] this is more for appearances sake because the real ambitions of the people are much more individual – at least in more developed Asian countries and [2] the reason this herd expression happens is not to do with human’s social instincts but the fear of appearing individualistic – something that is not embraced for reasons that go back thousands of years.

    I mention this not to poor scorn on Mark’s great book … but because it highlights to me how the behaviour of the Asian culture is becoming more relevant in the wider World without many people really appreciating the intricacies of why it happens.

    I don’t know what the point I’m trying to make with this post, but there you go.

  7. Thanks for stopping by Rob, and for making a couple of excellent points.

    Obviously, Asia is a big place. I’m not sure whether Mark was referring to all 4bn people and diverse cultures and backgrounds when he mentioned Asia – the only specific example he gave was a Gandhi quote.

  8. And there lies my issue …

    Asia too often is classed as one country, but the differences between cultures is extreme, often people in the same city can appear to be from different planets!

    I’m not questioning Mark – or Gandhi – but these are the sort of generalistic comments that have resulted in a hell of a lot of companies losing a hell of a lot of cash.

  9. And please note I haven’t sworn on your blog, ha!

  10. Great idea. Review first. Read the book later.

    But didn’t Lewis Carroll get there first?

    Still, I still might be able to ‘borrow’ the idea for a review of Herd I’ve been asked to do.

    ‘Thanks to Simon for giving me my opening remarks about Herd which he hadn’t read at the time …’

    [Only 480 words go].


  11. Glad to be of assistance 🙂

  12. Rob feel free to swear on my blog I need all the hits I can get. OTOH , if you do, I swear I’ll cut all words not found in full in Guardian news pages.

    Simon, respect. I copped out and am reading Herd in traditional boring front to back way before venting.

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