FEATURE8 January 2013
FEATURE8 January 2013
Visual communication skills are alien to some in the research industry, but they needn’t be. Data visualisation can become part of the research process through smart hiring, skills training and expert partnerships.
CNN took top honours in the Kantar-sponsored Information is Beautiful Awards earlier this year with its visualisation ( see above, or visit CNN.com ) connecting US casualties in Afghanistan and Iraq with the towns they came from back home. In doing so, they also connected back in time with the first great wartime data visualiser – Florence Nightingale. Lamp-carrying activities aside, Nightingale’s Diagram of the Causes of Mortality ( reproduced below ) played a crucial role in her campaign to show that many more soldiers died of preventable disease than of their wounds. A keen statistician since childhood, she recognised that while words could build an argument, a single visual could convey the essence of that argument in an instant.
That is precisely the opportunity that data visualisation offers the insight and research business today. As data piles up around us in ever-growing quantities visualisation has been hailed as a way to cut through the clutter and shine a light on the insights that matter. And of course that’s precisely the kind of clarity that time-poor, data-rich clients are craving.
But we should be careful not to over-claim for this stuff. Data visualisation should not be regarded as an end in itself. It’s not just turning data into pretty pictures. The real point to data visualisation – the value that it brings to research buyers and suppliers – is as an aid to storytelling. It’s about seeing the patterns in the data that flush out a story and then help you to start telling that story. Only by doing that can you move data off the spreadsheet and out into the real world of consumer behaviour and preferences. The data visualisation helps. But it doesn’t get you there. It’s all too easy to fall into the old cliché of “show rather than tell”. What we’re really talking about is, “showing in order to tell it better”.
The best analogy, I think, and the one I use most frequently, is with journalism. It’s no surprise at all that Kantar’s data visualisation partner David McCandless was a journalist. And it’s no surprise either that many great examples of data visualisation come from the publishing and media sectors. Journalists face the same challenge that we do of sifting large amounts of often conflicting data to arrive at a truth ( or an insight, in our case ). But if they don’t present that truth within a narrative that hooks the reader and imbues trust in their findings, they won’t find much of an audience.
So we need to think of data visualisation as an aid to creating compelling stories that move our clients to act. It’s about arriving at a point of view. And this has huge implications for the way we recruit and train our people.
Visual communication is frankly alien to some people in the insights industry. Concerned – correctly, of course – with the integrity of data, many researchers are suspicious of the introduction of right-brain thinking. They worry that visualisation risks trivialisation.
And yet it is perfectly possible to encourage people, through training, to discover creative talents in both visualisation and storytelling that they had no idea they had. At Kantar we’ve put about 250 people through workshops with McCandless and it’s been a joy to observe people realise that not only do they get it, but they are also perfectly capable of doing it. Such is the hunger to get involved with data visualisation that a group of our people have set up a global network of champions across all our companies. They are now holding monthly virtual meetings and webinars to share their latest outputs and best practice.
However, it seems certain that in terms of hiring policy, the industry will have to “swing to the right ( brain )” if it is to capitalise on the potential of data visualisation – and other creative tools. It is a rare recruit who exhibits equally left- and right-brained traits. Anyone who can deliver the desired fusion of numbers, words and visuals is going to find themselves in serious demand.
Overall I think it’s a moot point whether we will deliver data visualisation outputs through in-house resources ( as a couple of our companies do ) or pursue partnerships with the agencies that specialise in the field ( as many more of our companies do ). But as with any other creative product, you have to understand it to commission it.
The great challenge down the line is how data visualisation skills can be embedded throughout the research process. There’s a great deal of software now available – the so-called charting engines – which generate credible data visualisations that are certainly better than the average PowerPoint effort. These packages can lend consistency and facilitate more clarity and engagement. And they are helping to take data visualisation out of the creative ghetto. There’s a democratising influence, much like the early days of desktop publishing.
But I suspect most of the bigger research companies will want a look and feel in their outputs that is properly connected to their brand and product portfolios, so will opt for a more bespoke approach that addresses client needs more exactly. And the sheer number of datasets that many companies are now trying to integrate means that visualisation packages are more likely to be custom-built.
This requires investment of course. But the automation of many outputs will by definition reduce the number of man-hours required so ROI should not be too hard to prove.
Money, though, may not be the only investment required. The effective application of data visualisation brings with it some big issues around work process and planning. Companies may have to adopt a much more agency-like approach to scheduling and time-budgeting, rather than treating data visualisation as an add-on applied at the end of a project, which I suspect is often the case today. This could bring with it an element of positive disruption.
It’s only two years since Kantar partnered with McCandless and a year since we co-created the Information is Beautiful Awards. The pace of development in data visualisation has been unrelenting, especially in the area of interactive visualisations. This is clearly the dominant trend, accounting for a surprisingly high number of awards entries. Interactivity opens new vistas of discovery in enabling clients and researchers to find the stories themselves and will bring with it huge benefits in terms of engagement and partnership.
Ultimately we’ll enter the age of live, active data visualisation brought to us through always-on feeds. When do I think this will happen? Hard to say, but it’ll be a lot less time than the 150-year gap between Florence Nightingale and CNN’s work on the human cost of war.
Aziz Cami is creative director of Kantar and before that co-founded brand strategy, design and innovation agency The Partners
Horse racing fans will know that the trifecta is the ultimate bet. Correctly pick which horses will finish first, second and third and you are guaranteed exceptional returns. That’s how I feel about data vis – if we can win on three counts, we win big.
Data visualisation is about more than just illustrating numeric concepts. It’s symbolic of the change going on in our industry. It’s a manifestation of the growing importance of design and artistry in brand building – both for our clients’ brands and for our own.
Eileen Campbell is global CEO of Millward Brown