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Bursts: The Hidden Pattern Behind Everything We Do

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Review of Albert-Laszlo Barabasi’s book which looks at how predictable we are…

Book Review

Predicting human behaviour – is it possible? That’s one of the questions posed by Albert-Laszlo Barabasi, in his book, Bursts.

We are all predictable to a lesser or greater degree. I can tell which topics are going to cause my husband to rant about the government – and I know the rants off by heart. My sister’s husband always does the ironing at 4pm on Sundays. And the chances are if you come into my study at the end of a long workday I’ll be playing some addictive game on the computer. I can also tell you that at some point I will become completely annoyed with myself for wasting time and will remove the game or block the website it’s on, and this will be followed by a period without any game-playing – until another one catches my attention, of course.smile

As a facilitator who uses Clean Language and Symbolic Modelling to help people figure out patterns like these, and to consider what they would like to have happen instead, I know that it’s possible to get right into the detailed thinking patterns that are behind these kinds of actions and this is only possible because the pattern is the same every time. A pattern is, by its very nature, something that repeats and so is predictable. But I am talking about and dealing with the patterns of one individual at a time. Bursts, on the other hand, is about predicting human behaviour en masse, in much the same way we predict the weather these days, with about 95% accuracy.

I was drawn to this book because of the promise that it would reveal ‘the hidden pattern behind everything we do’. A very tempting subtitle! And although I wouldn’t recommend you rush out and buy it (more than half the book is given over to telling the tale of a 16th century Hungarian crusade, which I found very tedious and largely irrelevant, especially when I discovered the ‘prediction’ it was centred upon could have been written 20 or 30 years after the event) it does have a one or two good bits…

Where’s George?

For example, did you know that there’s a website called www.wheresgeorge.com which tracks the whereabouts of dollar bills? If you’re in the States, you may get a bill with this URL written on it, and if so, you can type its serial number into the database, see where it’s been, and add its new location if you feel so inclined. Or you can start tracking a new bill and add write the web address on yourself. Analysis of the database shows that dollar bills tend to hand around in a neighbourhood for a while and then make a sudden leap right across the country. I love this idea of tracking dollar bills (and I’m glad there’s not a good UK equivalent, it’s just the kind of thing I could waste even more time doing!)

Of course, the sudden leap is easy to explain – someone got on a plane and spent the bill at their destination. It’s also an example of the ‘bursty’ pattern that this book is about. Put simply, we do things in bursts. We write a batch of emails then don’t look at our inbox for several hours. We play a computer game several times and then not again until the next day. We even diet in bursts – hence the term yo-yo dieting. And Barabasi argues that knowledge of this pattern (which can be written as a mathematical formula), together with the technological advances which allow us to collect huge swathes of data about individuals and their movements, points to a future where we will be able to predict human behaviour.

Encased in Cement

The bit I liked best, though, adds credence to David Grove’s idea of treating metaphorical language as though it’s literal…

People who are depressed often use metaphors such as, “It’s like being ‘encased in cement, you just can’t drag your body out of bed”. Since doctors have to rely on subjective descriptions like this for diagnosing depression, many people view depression ‘as little more than a sign of personal weakness’. So scientists in Tokyo set out to discover whether there is any physical basis for descriptions like this. They attached ‘accelerometers’ (devices that can detect every movement, no matter how minimal) to the wrists of 25 individuals and measured the amount of movement in those wrists.

They found that our hands follow the same bursty pattern of movement and rest, where most rests are just for a few seconds and some (e.g. when we’re asleep) last several hours. But the average rest period in the depressed subjects was twice as long (15 mins) as the rest periods in healthy subjects (7 mins). So they came to the conclusion that descriptions like being ‘encased in concrete’ are not just figures of speech or illusions, but are based on physical reality.

All of the examples quoted in this book seemed to me to be quite obvious, and I suppose that’s the point. If everything we do is ‘bursty’ it’s highly likely that we’ll recognise our own patterns of behaviour in the examples given.


About Marian Way

Marian Way's avatar

A highly skilled facilitator and trainer, Marian, who founded Clean Learning in 2001, has developed and delivered training across the world. She is the author of Clean Approaches for Coaches, co-author, with James Lawley, of Insights in Space and co-author, with Caitlin Walker, of So you want to be… #DramaFree.

Marian is an expert Clean facilitator, an adept modeller, a programme writer and an inspirational trainer. She has a natural ability to model existing structures, find the connections between them and design new ways for people to learn. Marian was a leading innovator within the Weight Watchers organisation, which included developing the “points” strategy, a local idea that went on to become a global innovation. She is a director of both Clean Learning and Training Attention CIC, world leaders in clean applications for corporate, educational and community development. She designs our programmes and workbooks, leads workshops and teaches on all our courses. She’s trained people in Great Britain, Russia, Sweden, Germany, Australia, Japan and the USA. Marian is also a recognised Clean Assessor.


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