In 2014, the lure of big data solutions will catch many executives in a maze of both useful and useless data, and the result will be a big disappointment if they don’t have the right strategy.
As businesses clamor to participate in big data initiatives, they are risking millions of dollars on software and servers with no certainty of any useful outcomes and, in some cases, any outcomes at all. Building a huge data warehouse is just the start but should never be the goal. William Binney, creator of some of the computer code used by the NSA to spy on international Internet traffic, said recently that the agency knows so much that it can’t understand what it has. “What they are doing is making themselves dysfunctional by taking all this data. The agency is drowning in information,” said Binney. If the world’s leading data collection and analysis agency can have a problem of “too much data,” then it’s not farfetched to assume companies diving into big data may need a life jacket.
All data is not created equal.
There is something to be said for quality over quantity, especially in an age of phony Facebook and Twitter clicks (that’s right—offshore click farms have made a business of inflating social media numbers). If big data held all the answers then companies like Twitter wouldn’t need to supplement the machine-to-machine information they already have access to with user surveys as they currently are doing (i.e. little data).
The Futurist says that big data is a big opportunity but warns that it is“useless” without the ability to “collect, analyze and execute on it.” And don’t get caught in the trap of analyzing your own data only. True value can only accrue from analyzing data streams from inside and outside of your organization.
The Furturist also projects that the amount of data available will increase over 44 times during the next six years. However, more data does not mean better data; much of this information will be useless for making strategic business decisions. Remember the old 70’s adage of “Garbage In, Garbage Out“? Clearly, the challenge to identify what is useful versus what is not is key. It’s really quite simple to qualify data—just ask yourself the question, “Can I use this to make money?”. So, for example, the fact that your company has 25,000 Facebook likes may not have the same impact on your bottom line as knowing that 25% of your target customers are influenced by social media when it comes to their purchase decisions, or that 50% of your customers who use Facebook are planning to spend less over the next 90 days on apparel. It’s about weeding through the clutter and pinpointing the data streams critical to your core business strategy.
Big data tends to be tactical, rather than strategic in nature.
Tracking clicks may help to see how something worked or may work from a digital ad perspective, but it won’t provide C-level insights about issues dealing with customers, the market and competitors. The recent holiday season is an indication of the difference in outcomes between using transactional data and insight derived from an analysis of data from various sources. As the market awaited results from the shopping season, those people who attended the Morgan Stanley Global Consumer and Retail Conference in November got a preview of who the winners were going to be from data mined and analyzed by Prosper Insights & Analytics.
Bottom line: As your mother may have told you, “Just because all your friends are jumping off a bridge doesn’t mean you should too.”
Everybody’s doing it—big data is all the buzz right now. But don’t make the multi-million dollar mistake of building a gigantic warehouse of useless data. Focus on identifying, gathering, correlating and analyzing the right data to help your business grow.
Having foreknowledge from data mining of various data streams, including outside your organization, is key for big data success. Today’s focus on mining internal data/transactional data will leave many users of big data disappointed and out millions of dollars.
Gary Drenik is CEO of Prosper Insights & Analytics, a company that prides itself on turning data into solutions.