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Ian Gibbs Ian Gibbs Independent Data Consultant , Data Stories
Big Data, Smart Data, Fast Data.... Creative Data?

Big Data, Smart Data, Fast Data.... Creative Data?

“You might be making mistakes on the margin of error, but I believe the speed of which you get data and make decisions is more important than the accuracy of the answer you get.”

So said Jorn Socquet, AB InBev's VP of US marketing, in an interview with Marketing Week last month in which he endorsed the use of "fast data" analytics in business decision making. It's a comment that doubtless sent a cold shiver down the spines of research die-hards. Margins of error; statistical significance tests; sampling methodologies: they exist for a reason right? Do we really want to discard years of carefully crafted market research and analysis theory - theory that has been developed explicitly to provide us with an as-accurate estimation of the truth as possible - just for the sake of some quick and dirty real-time insight?

Perhaps this is no surprise? Much comment has been made of late around how we now live in a post-truth world. Facts just simply don't seem to matter in political discourse anymore, as evidenced by the result of the Brexit referendum. So why should they matter elsewhere?

Once you consider the fact that according to KPMG's recently released Global  CEO Outlook Survey 86% of global CEOs say they lack time to think strategically about forces of disruption and innovation, but that 84% also say that they are concerned about the quality of data they have to base decisions on, you have to ask what it is that they really want: fast inaccurate data, or slow high quality data?

This is a glib response of course and I do actually think Jorn Socquet makes a good point. As with everything, it's all about context. If you're making important strategic decisions about the long term future of your business or brand, take your time with the analysis and stay robust. But if you're simply trying to inspire some creative thinking, go fast. And that's the crucial point here: data doesn't just have to point to one single truth, it can simply perform a function in inspiring creative thinking and ideas. In other words it could be used as one of many means to a creative end, rather than the end point itself.

This is just what we've been doing at the Guardian recently. Harnessing the power of our first party data to inspire creative content ideas in our advertiser clients. By placing a DMP generated pixel tag on client digital properties we can now create an advertiser-centric view of our data rather than a Guardian-centric view. In other words we can tell our clients about their audience’s quality content consumption habits to find out what makes them tick. For one educational establishment about to launch a forensic science degree for example, we were able to see that their audience were really engaged with crosswords and "Scandinavian Noir" content (very "Guardian" I heard you say!). What better way to raise awareness of their new degree than through an online interactive crime scene perhaps - sating the desire to solve puzzles and solve crimes simultaneously? We're not suggesting that they stake the future of their business on this one piece of insight, but this kind of data can be provided fast, and it can unearth potentially exciting creative ideas for brands.

I read of a data sceptic once questioning what piece of data drove the decision to use a drumming gorilla to advertise a chocolate brand, but I don't think that this is as far-fetched as it sounds. Data can be a lens by which we make creative decisions: not the be all and end all, but an interesting reference point nonetheless. I see no reason why data can’t inspire such creative thinking. And of course as Cannes Lions are always quick to remind us, creativity matters: it drives real business results.

The final point I'd make is that perhaps fast insight and robust insight aren't going to be as mutually exclusive as they sound in the future. I read with interest last week the news from Savitz  Consulting that through the identification of inliers, research sample sizes can now be reduced without forfeiting robustness: reducing research costs by up to 33%. Music to the ears of many a research budget holder no doubt.

At the end of the day you just need to be clear on your objectives before you set out. If you're a die-hard market researcher or data analyst, don't get too caught up in the detail if the aim is just to inspire some creativity thinking. But on the flip side, if you’re a senior business decision maker or strategist, don't put undue pressure on your analytics people to deliver fast data that might compromise credibility when you're staking important strategic decisions on the outcome.

Get fast with your data, but not loose!

Ian Gibbs Independent Data Consultant Data Stories Bio

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