Right-sizing Big Data*

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The ad business is driven by sound bytes and buzzwords. And I don’t have to tell you that one of the buzzes of the moment is “Big Data”. You can’t swing a cat without knocking into a half-dozen “experts” touting its intrinsic value and huge ROI potential. The run up in ad tech investment and VC funding in the area might be creating the next tech bubble. And marketers and agencies are all shouting, “Big Data is the answer!” But I don’t know if they even know what the question is.

The thing is that “big data” is a tool – and like any tool, it has uses and limitations. Firstly, it’s helpful in certain tasks – but not for all of them. Second of all, it functions like the proverbial hammer, i.e. “if all you have is a hammer, everything looks like a nail”. People need other tools to complete complex jobs. And finally, and most importantly –like all tools, it requires a human hand, and heart, to guide it.

Limitations of Big Data
The benefit of Big Data is to leverage computational power to process quickly and nimbly huge amounts of data to make it accessible to people. It allows us to begin to divine insights and understanding around information that is available but too plentiful and dispersed for human perception, shining a light on that which was not visible. And it can automate actions that were difficult, time-consuming or even impossible just a few years ago.

But Big Data seems to assume that all data is great – and that more data is better. But bigger is not always better – just ask the 74% of brands, according to a World Federation of Advertisers study, who are saying that they are overwhelmed by big data and unprepared to take advantage of it. And always consider the Einstein quote, “everything that can be counted does not necessarily count; everything that counts cannot necessarily be counted”. Just because you can now measure something doesn’t mean you should.

In addition, Big Data tends to be a tactical tool, rather a strategic one. Because data-based ad technology is allowing us to automate around measurable actions, behaviors, activities and realities, it’s a great tool for optimization – creative versioning, ad placements, a/b testing, etc. But don’t expect it to start giving you high level strategic answers, compelling messaging ideas or brand platforms.

One other issue is that once a KPI/data point is selected, people start optimizing towards them vs. towards overall success. While this has always been the case (think of brands that developed ads to “beat the copy test” vs. to inspire or engage) – this becomes even more of a worry once robots and data scientists take the wheel.

Bottom Line: Ensure you’ve appropriately assessed the data you’re collecting, wisely chosen KPI’s, and properly identified the role of Big Data in your marketing efforts.

Small data is just critical
While the aggregation of Big Data is important, small data remains just as important. Think of outside information, anecdotes, industry intelligence, or analogies – these are things that can help color opinion, drive creative thought, and inform the data more than more reams of it ever could. In fact, relying on current data alone would have put you in tech stocks in 1999, in real estate in 2007, and in Bieber albums in 2013. That’s why the small data of experience, a finger on the pulse, and a surprising a-ha can provide the insights and additional dimensions needed to make better, more complex decisions.

And while data enriches understanding, it doesn’t substitute for instinct, insight, or human touch. Machines can’t make a gut decision.

Bottom Line: Make sure you are not run by data alone – but are keeping eyes and ears open for insight, ideas and inspiration outside of your data sets.

Human element necessary
In well-defined, predictable situations, Big Data can help drive the best way forward. But what category or domain is well-defined and predictable today? Most face uncharted territory and rocky, ever-changing realities. No amount of data alone can drive future strategy or big ideas. In fact, in uncharted territory, data derived from past examples or activity can give a false sense of confidence. That’s why I like the concept of “sensemaking”, proposed by Christian Madsbjerg and Mikkel Rasmussen in The Moment of Clarity.

Sensemaking requires “the ability to lead open-ended discovery, to sense both soft and hard data, to use your judgment skills, to connect the dots, and to see the big picture in a vast ocean of sometimes conflicting data.” This requires a combination of data and soft, human skills and thought.

But more importantly, data is unlikely to “stir the soul”, create inspiration, or drive creative breakthroughs. And that’s what leads to the innovation and disruption necessary for significant success today. Big data can help shine the light, but humans create the new ideas that emerge.

Bottom Line: Don’t expect your robots to find you the answers. Instead, leverage the data-driven insights to inform your creative mind.

* originally posted in TalentZoo 4/9/2014

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