The mushrooming growth of the Internet of Things, along with the digital tools to measure just about anything, continue to generate data, turning big data into bigger data into bigger data. These numbers, along with the discussion about what to do with them, are ubiquitous.
By now, we’ve been lulled into thinking of data like we do electricity. Most people don’t really know how it works, but sure are glad when it does. The attention data crunching has gotten from media and pundits would make anyone think that big data is the big answer — until, of course, it isn’t.
We just saw that in America’s presidential election. And we see it in everyday aspects of American life, as well. We see it when pop-up ads keep showing us products we’ve already purchased, or are no longer interested in.
Where data and insights go to die (pexels-pixabay1850170)
The Missing Link
Big data is now omnipresent; it’s a fact of life. It can be used well or ignored, can be employed for good or for bad. It can make us vulnerable or strong. It can entertain us and it can entrap us. But this isn’t about the shoulds and shouldn’ts of big data — it’s about finding a missing link.
When people try to take data and apply it to their business, something is often missed. Data easily gets decontextualized from the culture. That leads to ill-informed decisions, wrong assumptions or sometimes, no clear decision at all.
So much has been written about how 2016’s election pollsters didn’t interview the right people, employed flawed prediction models, and interviewed people who introduced even more potential for error into the system. I suggest that it is the context itself that is missing from those approaches.
All the historical models available don’t matter if you fail to view the current cultural environment, potential influences and value motivators. All the issues that ultimately drove the election and voters have been building for years, and have been hiding in plain sight. Allan Lichtman, one of the few prominent pundits to predict the election correctly, uses a version of cultural context to more adequately put data to use. Here’s what I think.
Locked Away in a Digital Drawer
When talking about consumers and the constantly changing marketplace, how one approaches the data must embrace fluidity and complexity. We have to seek out the connections between the data and the culture. For as complicated as a political voice is, it’s still a conscious choice. When it comes to market research and consumer choices, understanding all the factors and motivators gets even fuzzier.
Even more than in politics, much has been written about how important data and it’s crunching are to big business. According to Forrester, though, “between 60% and 73% of all data within an enterprise goes unused for analytics. That’s unacceptable in an age where deeper, actionable insights, especially about customers, are a competitive necessity.”
What does that mean? It means all that data is just wasting away in some digital drawer.
Promises, Promises
When looking at consumer goods, one can see examples of the ways big data has been an unfulfilled promise. Take the curious case of Chobani! Why did otherwise successful yogurt makers disregard the threat of Greek yogurt? They failed to recognize the strength of the shifts in the broader consumer culture. They overlooked the changing taste profile of newly foodie-obsessed customers, didn’t take seriously the growing emphasis on health, wellness and fitness, couldn’t identify sugar as one of the newly anointed dietary evils, and didn’t hear the voices of aging Baby Boomers focusing on healthier foods
Look at the Values
Another example: When Netflix tried to spin off its DVD business (Qwickster) from its burgeoning streaming product set in the fall of 2011, it may have created two monthly bills and separate ratings systems for viewers, not to mention separate branding for a whole new company. This shift made customers suspicious of what felt like a big change, and it took away the simplicity that they had come to know and appreciate. (That’s not a good combination!) A better understanding of the customer values associated with the Netflix brand would have helped to prevent this expensive, embarrassing misstep.
Where to Look
When looking at the failures of big data past, it’s important to keep in mind that answers are rarely in plain site. Often, these days, the data you need to solve a problem isn’t wholly apparent. That’s where dark data comes in. According to IDC, 90% of the unstructured data are never analyzed. These are information assets that are being collected but rarely used, like recorded phone calls, customer reviews, and customer complaints. Certainly, you can gain demographic and purchasing information from these sorts of assets, but analyzing for value motivators will give you the WHY beyond the WHAT. Not only will this data help you create a consistent omnichannel, experience but it can also provide alternate perspectives on your products or services.