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Embrace the outliers: Abandoning certainty will unlock the creative qualities of big data
Ben Essen
Admap
Gold, The Admap Prize, June 2014
Embrace the outliers: Abandoning certainty will unlock the creative qualities of big data
Ben Essen
IRIS
The term 'Big Data' implies scale, objectivity and quantification – and in doing so reinforces the creativity-hindering
idea that more data can give us more certainty. But these new channels of data also give us variety, bias and
qualification. Embracing the outliers and the data that make us uncomfortable will help us ask the questions that
unlock true creative innovation.
Before Einstein, our understanding of space was neatly accounted for by Newton's laws of motion. A universal set of rules that
accounted for everything from the motions of pendulums to the motions of planets. An explainable system within which a
comfortable conception of the universe could exist.
As astronomers charted the progress of the planets for the 200 years that followed, the ever-increasing quantities of data
collected around the solar system only helped to reinforce this set of rules. But for one exception. Mercury's orbit rotated
around the planet at the wrong speed.
Title: Embrace the outliers: Abandoning certainty will unlock the creative qualities of big data
Author(s): Ben Essen
Source: Admap
Issue: Gold, The Admap Prize, June 2014
The Admap Prize 2015
This essay was the Gold Award winner of The Admap Prize 2015.
For more information visit the Prize page.
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© Emilie Sandy
Astronomers tried to work out what they had missed – every other piece of evidence was so clear and the laws so certain that
there must be an explanation for the anomaly. They blamed the sun, they blamed Mercury, they even assumed the existence
of the planet Vulcan to help make sense of the phenomenon. But while all other evidence continued to reinforce Newton's
laws, the exception remained.
Then came Einstein's question: what if Mercury was the rule, not the exception? What if the data shouldn't come from the
planets at all, but the space within which they existed? Einstein refused to believe the evidence. He embraced the outlier. And
he discovered that astronomers had been looking at things all wrong. It turned out the uncomfortable exception was the basis
for the biggest scientific leap of all.
We are in the grips of a marketing era you might call 'Newtonian'. A generation of marketers have been brought up in a data-
driven culture, with the expectation that everything should be explainable. With the number of inputs steadily rising, our media
schedules can become more robust, our insights ever more accurate and our creative concepts increasingly bulletproof.
Making a decision which flies in the face of the data is seen as foolhardy. "You really have no excuse to be off point," says
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Amex chief marketing officer John Hayes. For client-side marketers, the modern Holy Grail of marketing is certainty.
Much of the rhetoric about Big Data's bright future is rooted in its ability to accelerate this paradigm. According to PWC, 64%
of global CMOs have changed the way they make big decisions in the wake of the proliferation of data in their sector. It is
increasingly unfashionable to make creative leaps in marketing: 49% of the sample believe that advances in data analysis are
undermining the credibility of intuition or experience. The underlying assumption – that Big Data will resolve the century-old
'Wanamaker problem' of wasted spend and fruitless creative gambles.
There are of course poster-child stories for this philosophy. Google famously reported a $200m boost in revenues following a
data-driven experiment to find the perfect blue for their homepage. Forget designers' instincts, a series of '1% experiments'
testing multiple shades of blue identified the optimum hue for driving click-through. Research studies have shown that using
behavioural data to better target banner advertising can yield a click-through rate improvement of up to sevenfold. Some 700%
more effective, just because of the data. Data equals certainty.
Of course, there's another way of looking at things. The average click-through rate on banner advertising averages around
0.2%. So to use the example above, highly optimised behaviourally targeted advertising is creating click-through rates of up to
1.4%. That still means that 98 people out of 100 are choosing not to click on the ad, or ignoring it all together. And of course,
as all banner advertising rapidly evolves to become behaviourally targeted, any initial competitive advantage from the format
will be lost.
To approach Big Data as a tool for increasing certainty is to treat it not as a catalyst for creativity but as a cure for it. Big Data
becomes a modern 'ad tweaker' used to compensate for and smooth out the inaccuracies of the human, fallible idea. But while
such an approach may drive incremental evolution, it will hinder true transformation and revolution. In the medium term, ideas
won't become better and more effective: they will become safer and more familiar. To quote Sir John Hegarty, "I've spent my
life dealing with people who've got all the data in the world and yet they can't invent anything". And in an era when the
payback on revolutionary creative thinking can be ten times more efficient than that of middle-ground ideas, that's bad
business sense.
"But what about House of Cards?" I hear you ask. Folklore tells us that the concept for the hit Netflix remake came from
creatively crunching data from the platform: the idea synthesised from a unique combination of popular genres, actors,
directors and even plot devices. But in truth, the show was the brainchild of producer Dana Brunetti, who credits not Netflix'
data for the idea but 'the bliss of ignorance'. The concept had been dreamed up and pitched to the big studios long before
Netflix was involved. Data was used at the end of the creative process, to justify the spend. Creativity creates. Data validates.
So how to avoid Big Data becoming the nemesis of creativity? A great place to start would be the name. The term 'Big' Data
(capitalised, of course) only serves to reinforce its status as the great Provider of Certainty. It implies scale – a macro mass of
data too large to easily manipulate. It says quantification: numbers and patterns, not detail and nuance. And it suggests
objectivity: its breadth makes it true and irrefutable – beyond control or influence.
We should look at it another way. The key characteristic of this new raft of data isn't its scale, but its variety. It is unique not
just in its quantity, but its quality. The data may provide more breadth of knowledge than ever before, but it also gives us more
depth than ever before.
Take the healthy activity advice the US government gives its citizens. Current guidelines are limited to the advice that people
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should take '150 minutes of moderate exercise a week', with no details on the specific behaviours – for instance, the balance
of time one should spend standing and sitting. But recently, government researchers turned to wearables to add a new layer of
insight to their research, and are using the data to create a new wave of guidelines full of detailed advice that resonates with
citizens' modern lives.
Now new connected devices such as the Melon headband are entering the market, which will measure our EEG brainwaves to
track our focus, and provide insights, such as which music is best for our concentration. Big Data, when produced in this form,
is not just quantitative, but qualitative. It introduces the possibility of a whole new method for delivering surprising and
provocative insights about modern lifestyles. Where personal data is used to deliver more personal revelations than any other
form of observation. 'Data Ethnography', if you like.
The original moment when 'big' data entered the world of advertising was captured in a recent episode of Mad Men.
Referencing the dawn of agency computer services, a giant machine was introduced to Don Draper's office that "could count
more stars in a day than we can in a lifetime". Don's retort summed up the creative viewpoint: "What man lay on his back
looking at the stars, and thought about a number?"
Likewise, Big Data doesn't have to be about numbers. It provides a level of depth and variety that takes it beyond the
computer science of Don's time. And our approach to it can evolve beyond percentages, and into meaning. The creative
opportunity will come from viewing the data with a human eye.
Take the award-winning British Airways 'Magic of Flying' billboard. Suddenly given access to a vault of real-time flight data and
the ability to connect it directly to electronic poster sites, the great temptation for Ogilvy's development team would have been
to default to 'Big' as the answer: aggregation and utility. To treat the data as a complete whole, perhaps creating a stunning
visualisation or building it into a functional tool. The magic was that they did the opposite. They thought small and specific,
identified a single piece of data and applied a simple human thought: 'I wonder where that flight is going?'
Which brings us to objectivity. Through terms such as 'Data Scientists' and 'Data Mining', the lexicon of Big Data presents it as
a scientific truth to be dissected and analysed. Big Data is objective, correct, unquestionable – a powerful mass we are
intimidated to handle. Yet to make it useful in the creative process, we need to see data as a tool – not a master.
The truth is, data isn't as objective as we like to make out. To quote Nate Silver, "Numbers have no way of speaking for
themselves. We speak for them" – data is meaningful only through human interpretation. In her book "Raw Data" is an
Oxymoron, Lisa Gitelman observes that data is never as neutral as we like to think. In order to collect data in the first place,
we need to decide both what to track and how to track it. Simply by making these decisions we have already cooked bias into
the data. Data is created by people – and so it has people's fingerprints all over it.
With this is mind, we shouldn't see it as sinful to apply our own bias to the data we access. The world needs Data Scientists,
whose job it is to analyse data as impartially as possible. But the world of creativity needs 'Data Curators' – who approach the
data with an agenda, with a point of view and with a remit to play with it.
The gallery curator must interpret, contextualise and frame the work he or she displays in order to provoke a more meaningful
response from the audience. The best curators leave their stamp on an exhibition, juxtaposing pieces in surprising, illogical
and sometimes disrespectful ways to provoke entirely new interpretations of the work. Likewise, to provoke the most
interesting new ideas, the Data Curator must juxtapose and collide the data, while adding their own bias and opinion. In his
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award-winning ESOMAR paper, Adam Riley warns that "if you are remaining neutral, not only are you not adding value, you
are taking it away". To drive new thinking, perhaps we should learn from the 'crazy walls' of Sherlock and Homeland's Carrie
Mathison – where the breakthrough insight only comes when data is assembled and offset in unpredictable and counter-
logical ways.
Stephen Thaler's 'Creativity Machine' is largely credited as being the closest humankind has come to generating creativity
through software. Unlike Artificial Intelligence, which works in a logical, systematic and objective way, the creativity machine
works by processing large quantities of data and then 'distressing' it. The machine attacks the data with glitches: add the right
amount of disruption and the machine starts making creative leaps. Thaler claims that: "Creativity cannot be derived in a
logical way, in a step-by-step fashion." If we are to harness the power of Big Data to drive creativity, we must do the same
thing. We must distress the data and add some grit into the machine.
In 2013, Belgian Bank KBC decided to launch a digital platform that collated data of independent businesses in an area – from
cafés to hairdressers to takeaways. But this was no ordinary listings site; instead KBC turned the data on its head. The
platform, called 'Gap in the Market', highlighted not what was there, but what was missing. The audience weren't eager
shoppers but entrepreneurs, seeking gaps and opportunities for their next venture (and a bank to back them).
The platform identified over 100,000 new business opportunities in the market, by crunching a massive volume of data. But the
answers hadn't been found in the data: they were found in the gaps. The data didn't provide evidence that these businesses
would work, but raised the question of whether they could. The data was most powerful when it was used to inspire
opportunities, not find solutions. To paraphrase John Seely Brown of the Center for the Edge, deriving creativity from Big Data
should "involve asking questions, not answering them".
Which brings us back to Einstein. The data anomaly of Mercury's orbit didn't give Einstein the answers he was looking for, but
it provoked new questions that led to an even greater discovery. And unlike the astronomers who came before, Einstein made
his creative leap by avoiding the trend line and focusing on the outlier. He gained insight from the exception, not the rule. So
maybe the next great commercial will feature a soundtrack found on Forgotify – home of the 4 million songs on Spotify that
have never been played. Or like MINI's 'Not Normal' campaign, we could seek creative inspiration from the fans whose
eccentric relationship with the brand bucks the trend.
As we try to make sense of ever more data about people, our products, and the relationship between them, there's a danger
that we acquire a kind of 'infobesity' where we are drawn to the broad patterns at the expense of the specifics. Who has time
for those funny little anecdotes about eccentric customer behaviour when we have such a robust understanding of what the
majority are doing? And as that weight of evidence becomes ever heavier, we will feel increasingly compelled to treat it as
sacred and indisputable. "The data says most people eat our cereal for breakfast. Our communications must talk about
breakfast." We will find certainty, but we will find it in the same space as the competition – the obvious places. The centre
ground.
Evidence tells us what is working. Creativity tells us what will work. So if Big Data is to fuel creativity – true creativity, i.e. the
leaps, revelations and innovations – we must use it to provide more than evidence. Cartoonist James Thurber once told us: "It
is better to know some of the questions than all of the answers." Marketers must resist the industry trend towards using Big
Data for reassurance and certainty, and use it instead to add provocative disruption to the creative process. Instead of being
intimidated by its scale, we must challenge it and play with it. Instead of viewing it as irrefutable and objective, we must treat it
qualitatively, with bias. Instead of following the comfort of the trend line, we must seek out the anomalies at the edges.
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Creative leaps will come when data makes us feel most uncomfortable. Because in the words of visionary trend researcher
Magnus Lindkvist, "Discomfort is the only sure sign that you are really exploring the foggy future that lies ahead."
Judges' comments
The essay had a simple, singular idea at its heart: that to make a creative leap you avoid the trend line and focus on
the outlier
Marco Rimini,
Admap Prize judge
This winning paper reminds us that creativity is helped by discovering what is different, not what is the same. Find
the exceptions, rather than the trends and patterns
Guy Murphy,
Admap Prize judge
About the Author
Ben Essen is head of planning at Iris, where he's spent the past eight years in London and New York fostering creative
innovation for Mini, Adidas, Samsung and Wickes. He is a regular speaker at SXSW and co-authored a study proving the
return on building a Participation Brand.
© Copyright Warc 2015 Warc Ltd.
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Tel: +44 (0)20 7467 8100, Fax: +(0)20 7467 8101
Read more winning essays
Silver
The empathy engine: Big data and the
necessity of understanding
Charlie Ebdy, Vizeum
Bronze
Don't get trapped, like Truman: You are
the star, I am the creator
Finola Austin, Ogilvy & Mather
View more selected essays
Commended
When you think big data, think bigger
creatively
Yeong Yee, BBDO Singapore
Reducing (not removing) risk
Gareth Price, The Social Partners
A period of punctuated equilibrium
inspired by big data
Ian Edwards, Vizeum
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