The Big Data Craze Is Just as Qualitative as It Is Quantitative
One of my favorite recent movie scenes takes place at the end of Moneyball, when Oakland A’s general manager Billy Beane (played by Brad Pitt) is summoned to Fenway Park to meet with Red Sox owner John Henry (played by Arliss Howard). Henry, impressed with Beane’s highly improbable success in overseeing a major regular season comeback, sums up the establishment’s outcry over Beane embracing analytical models to shape the team’s roster.
“This is threatening not just a way of doing business, but in their minds, it’s threatening the game. Really what it’s threatening is their livelihood, their jobs,” Henry says.
“It’s threatening the way they do things. And every time that happens, whether it’s the government, a way of doing business, whatever it is, the people who are holding the reins — they have their hands on the switch — they go batsh*t crazy.”
In digital marketing and communications, the same can be said of the big data craze that is permeating the halls of PR agencies, corporations and government institutions alike: it has taken too long to embrace data scientists who identify the “why” behind a trend, event, point of criticism or support. While this type of conceptual modeling has been around since the Mad Men days, the availability of real-time data is now the lifeblood of effective marketing and communications strategies. However, online analytics are quickly becoming commoditized.
What Google did for search, Facebook for social networking, LinkedIn for resume sharing, Salesforce.com for CRM — online analytics firms are developing new models that aim to fully organize the noise and chaos online.
Today, albeit for a cost, it’s relatively easy to measure where conversations are happening across the social web, who’s having them and what specifically about a brand, product or public policy issue is resonating (or falling flat). I have no doubt that in the next five years, anyone with a smartphone, tablet or laptop will be able to access highly-detailed, yet intuitive big data analytics for little or no cost.
Sounds exciting, right? Millions of people will have access to tools and platforms that take content consumption, networking, decision-making and overall connectivity to a whole new level.
But for brands, political campaigns and advocacy organizations that aim to have data-driven conversations with audiences, it will be more important than ever to apply qualitative logic and human reasoning to online analytical models. In short, subject matter expertise and deep knowledge will matter more than ever before given the rise of big data.
As communicators, even with what we have at our fingertips today, we need to immerse ourselves in the substance that contextualizes big data and allows us to make sense out of it. This means committing more time, asking more questions, consuming more content and never losing sight of the fact that data without actionable insights is meaningless.
Don’t get me wrong — analytics becoming automated and commoditized is a good thing. However, the likelihood that we will rely on what’s being fed back to us without taking the time to think about its impact on a strategy or business decision will only stand to increase. The promise of big data then quickly becomes the all-you-can-eat buffet of lazy or non-existent insights. If we let this happen, it’s akin to missing out on one the greatest technological developments since the proliferation of the modern day Internet.
My vote is to build on Beane’s approach, visit Fenway Park whenever possible and take an unconventional path in online analytics. We need to take the time to connect the dots and cultivate the insights that make us smarter and more effective in our daily jobs.
It’s easy to rest on our laurels when the obvious answer might appear to be right in front of us. But disrupting the status quo is just as qualitative as it quantitative — in this case, it’s the only way that we make big data work.
Original post seen on Huffington Post.