Big data is no big deal. Big data has been around for years and years, dominated by financial services firms, telecom providers, and sophisticated retailers. And while incremental advancements in computing speed and software design have enabled us to dice and slice data better and faster, don’t expect a groundswell of new activity.
Here are three fundamental reasons why.
Sensibility. Big data users and believers share a common POV that the cost and trouble of collecting, holding, cleaning, and analyzing data is worth it. And while it's easy to say, it's almost impossible to graph this sensibility onto running companies or agencies who are brand oriented or who have not hired enough numbers guys to influence their go-to-market strategy or the operational aspects of their business.
Embracing big data means embracing an ROI-driven numbers-oriented culture where data trumps opinion; even high-priced, big-ego executive opinion. The best big data users are numbers guys at the core. They believe that if you can’t count it or measure it, it doesn’t exist. It’s a pervasive micro viewpoint where God is in the details.
They are skeptical about big ideas and reluctant to embrace the unknowable magic of creative agencies. They will take a base hit over a home run every day because it's predictable. They live for testing, iterations, and incrementality. It’s a slow, detailed, and often frustrating process. Rarely do the numbers reveal immediate or market-altering insight.
Investment. Big data doesn’t come cheap. And while the cost of computers, software, and even skilled data analysts or outsourcing solutions has come down in recent years, its still not chickenfeed. Beyond the cash outlay and the intense IT landscape, organizations have to attend to the care and feeding of data guys, who need their toys and need to be managed and motivated differently than employees with other skill sets.
The pay-off is rarely immediate and often requires considerable marketing spend to generate enough data to find relevant patterns or to discern the nuances of consumer behavior. You can’t dabble in big data. You have to go all-in.
Interpretation. Data guys think, talk, and act differently. They need to be nurtured and directed differently by managers who understand them and can translate numbers and geek talk into English and into persuasive arguments for meeting or exceeding business objectives. It’s easy to get lost in the weeds if you don’t hire, mobilize, and motivate the right interpreters. More importantly, the interpreters need a seat at the decision-making table so that the analytics pay-off can be recognized and incorporated into the business.
Big Data isn’t a passing fancy. The current hype will wane. Some verticals, like CPG, will dabble a little more or a little less, but don’t expect a mad rush to embrace these tools. In a short, big data will slip below the line, where it's always been.