Kolumne von Adele Gritten Finding genuine nuggets of insight in an increasingly Big Data world

I live in a Western World where "bigger", "more", "immediately", and the need to be constantly switched on are cultural givens. I live in a world of endless possibilities, where an answer to every question that has ever existed is available at my fingertips across my various technological devices. I have been conditioned into thinking that in order to perform my job effectively and to advise my clients insightfully, I need to be on board the Big Data bandwagon. After all, it has been described as the new "oil" and as a worldwide resource.

Big Data, now a ubiquitous term in Marketing vocabulary, is the all-encompassing term for any collection of large and complex data sets that are difficult or slow to process using traditional data processing applications. It is a market that will be worth ca. 50 billion Dollar by 2018, according to various sources. 

Big data is increasingly available as we morph into "the Quantified Self", a term common in the media that refers to people's desire to measure their own behaviours or metrics, such as weight, diet, exercise, energy consumption and so on. As a society, we have certainly found a new, insatiable appetite for personalised data. We are also starting to embrace the buzzword the "Internet of Things" (IoT), which describes everyday objects having network connectivity that allows them to send and receive data. Gartner predicts that there will be nearly 26 billion devices on the IoT by 2020, while billions of devices will be wirelessly connected to it by 2020: this will truly be the Internet of Everything – the IoE! All devices, all connected, all sending, receiving, processing, and storing data.

But is this all a good thing? Whilst a recent Accenture report has posited that the IoT will make people’s working lives more engaging and productive, and that many new job categories will be created, others, like Nassim Nicholas Taleb argues in his book "Antifragile" that more data typically means proportionally more noise and proportionally less signal. The larger the amount of data available at our fingertips, the harder and longer it is to make meaningful and immediate sense of it all. Other gurus like Nate Silver, author of the Big Data bible "The Signal and the Noise", claim that the number of "meaningful relationships" does not increase in step with the meteoric rise in the sheer amount of available data. We simply generate a larger number of false positives – incorrectly identifying positive relationships.

So what does this all mean for our industry? What are some of our big watch outs in relation to Big Data?

It certainly means that data incompetence e.g. incorrect data collection and analysis methodologies can increasingly lead to poor decisions and in turn underperforming marketing strategies for brands. "Bigger", "more" and "immediately" can sometimes sow the seeds of confusion, distraction, and inaccuracy. Insight practitioners need better training to understand the quality and nature of the data collected and increasingly presented.

Big Data requires Big Ideas and Big People. The relatively new term "Data Artist" in our vocabulary refers to individuals and teams who are able to detect patterns in passive and active data streams, and ultimately, find connections to a business model. These people, who tend to be equally adept at left and right brain thinking, are arguably in sparse supply, and do not fit neatly into the agency model boxes of qual, quant or analytics silos still the structure of most big agencies. Better collaboration cross-departments both agency and client side is required to maximize talent leverage and facilitate cross-discipline collaboration i.e. aid more multi-dimensional understanding of data sets.

Much data collected by companies in the Big Data era will remain unused, unstructured and unkempt, and by the time businesses figure out what to do with it (and consumers agree to share it), the golden "IoU" moment – "Insight or Utility" – will have passed. Excessive data requires automated analysis, but if analysts are unable to synthesize automation with creative qualitative intuition, then finding the golden ticket will become more time consuming as large teams of people will need to sift through screens and screens of data – think of the scramble for the final ticket in Charlie and the Chocolate Factory. Our industry needs a better solution to this problem, and it’s not just about machine learning and software taking the analysis lead. It’s about changing the way we as researchers mange, sift through, synthesize, analyze and present data.

Ultimately, insight teams will have to move at a faster pace in the post-digital business era. Companies using evidence-based decision making underpinned by Big Data but analyzed through the lens of thick and small data chunks will win out commercially. These companies will harness Big Data to teach it to be Smart Data and Agile Data, adaptable for changing business requirements. They will be adept at data blending and data synthesis, and will know how to harness technology effectively in order to mine for the golden nuggets. They will understand the power of the simple, and balance the "less is more" argument alongside a more comprehensive view provided by the sheer volume of data. They will be adept at understanding both structured and unstructured data, and will not underestimate the primary business goal: to understand what the data means from a consumer-based decision making perspective.

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