Our next guest blog for the Data & Analytics theme is written by Julie Wittes Schlack, SVP of Product Innovation at Communispace. Julie provides insight into the collaborative advantage strategy and its role in big data. Interested in guest blogging this month? E-mail taylor[at]mitx[dot]org.
Julie is one of the founding members of Communispace Corporation. By day, she leads an innovation team whose mission is to discover, develop, and test new techniques and technologies for engaging people in online and mobile collaboration and insight generation. By night, she is a published author of fiction and narrative nonfiction. And 24 hours a day, she is a devoted fan of storytelling and meaning-making in all of its myriad forms.
What’s the difference between Big Data analytics and consumer collaboration? And can these two very disparate approaches to consumer insight and innovation play well together?
Let’s start with a definition provided by one of the biggest, best-established practitioners. Local Big Data analytics firm, Opera Solutions, has described its Vektor™ software as “a secure and flexible Big Data analytics platform that extracts powerful signals and insights from massive amounts of data flow, and then streams analytically enriched guidance and recommendations directly to the front lines of business operations.” Now this is a heady claim – and quite likely a valid one – but it’s a description lacking a human pronoun. There are no people in this process.
But in the business world, in the political world – everywhere that people and companies like mine are engaged in ongoing conversation with consumers – we’re doing it with the ultimate goal of not just gathering facts, but of moving people, of changing people’s minds and behaviors. That’s what marketing is.
The huge promise of Big Data also lies in its biggest limitation. In some respects, it is so useful because it’s entirely passive – it doesn’t rely on the self-reporting of flawed, biased and forgetful respondents, but on observable behavior. It doesn’t ask people what they’re going to do; it measures what they’ve already done. It doesn’t rely on sophisticated statistical analyses because there’s so damn much of it that algorithms and extrapolations aren’t necessary. In short, Big Data stands a good chance of replacing large-scale survey research in many domains, and I’m actually pretty excited about that.
But while Big Data can tell you what, it can’t tell you why. Its analytical scope is limited to the realm of what’s available and observable, but it can’t help you create the future. As David Brooks – someone with whom I rarely agree – observes in What You’ll Do Next, “If you are relying just on data, you will have a tendency to trust preferences and anticipate a continuation of what is happening now.” And as Joel Gurin writes in his excellent primer, Open Data Now, unlike Open Data, which is “public and purposeful … consciously released in a way that anyone can access, analyze, and use as he or she sees fit … with Big Data, the data sources are generally passive, and the data is often kept private. Big Data usually comes from sources that passively generate data without purpose, without direction, or without even realizing that they’re creating it.” (Full disclosure: Joel Gurin has been a friend of mine since high school, but is a very smart guy nonetheless.)
This is not a polemic against Big Data. On the contrary, there’s a very complementary and synergistic relationship between that methodology and intentional, interpersonal, conscious collaboration between consumers and brands. Big Data can render traditional quantitative research methods obsolete, but it simultaneously underscores the need for empathy and insight, for a human voice to make meaning and tell a story that moves the people behind the brands in a way that simple data, however beautifully visualized, cannot.
The risk that we always run – even with the best of intentions – is that when we turn actions and words into data, behind the numbers and visualizations we tend to lose what’s shifting, what’s subjective and how people interpret and choose to act on their own experience.
For more on how these two methodologies can work together, I immodestly refer you to “The Collaborative Advantage.” Then weigh in with your passionate arguments and examples. After all, data alone doesn’t move people. People move people.