While the technology giants of Silicon Valley are its poster children, big data is not just for big businesses. Despite the growing realization of this fact, some midsize businesses still suffer from a few myths about big data. This post busts three of them.
Big Data doesn’t require Big Bucks
With the rise of cloud computing and cloud-based services lowering the cost of enabling technology and more sources of useful information becoming available as open data, big data doesn’t require a big financial investment.
In his recent Inc. Magazine article What 3 Small Businesses Learned From Big Data, Kevin Kelleher explained that “thanks to falling tech costs and new tools that display complex databases in ways even technophobes could love, smaller companies can unlock more secrets from data. Your company’s databases can be cross-referenced with the expanding galaxy of information drawn not just from the likes of social networks, government databases, and usage patterns on mobile devices, but also from increasingly specialized information sources such as digitized transcripts of call-center interactions, and sensors sending updates from various steps within a supply chain—and do so affordably.”
Big Data doesn’t mean A Lot More Data
Even though the big bang of big data unleashed an expanding galaxy of information, leveraging big data doesn’t mean you have to use a lot more data than you are using now. In fact, using just a little more data will often be big enough. Also, unlike large businesses which often have diversified interests and the bureaucracy that comes with it, midsize businesses often have a more focused business problem to solve and the agility needed to quickly do something about it.
One of the examples Kelleher profiled in his article was the Point Defiance Zoo & Aquarium in Tacoma, Washington. The primary revenue generator for zoos is attendance, which provides a very focused business problem—get more people through the front gates. However, accurately predicting zoo attendance in the Pacific Northwest is complicated by its notoriously variable weather.
“Working with IBM,” Kelleher reported, “Point Defiance parsed its historical attendance records against years of detailed local climate data collected by the National Weather Service. This led to new insights that helped the zoo anticipate with surprising precision how many customers would show up on a given weekend. That in turn helped the zoo determine, down to the hour, how many employees should be staffing front gates, carousels, and other positions on peak days.” This zoo, therefore, didn’t have to go wild with lots of data. A little more data about weather patterns was big-enough-data to make a difference.
Big Data doesn’t generate Big Effects
The most common myth about big data is that it generates big effects—immediately. However, the recent The Economist article Little things that mean a lot revealed the unspoken secret of big data is that small effects can have large aggregated consequences. “Stimulated by all the talk from consultants and sellers of data-crunching software about the transformative potential of big data, managers may have been misled into hoping it will give them massive, instant, Holy Grail solutions. The reality is that big data produces lots of small advances—and that is good enough.” Lots of small wins from big data can add up to something big.
This post was brought to you by IBM for Midsize Business and opinions are my own. To read more on this topic, visit IBM’s Midsize Insider. Dedicated to providing businesses with expertise, solutions and tools that are specific to small and midsized companies, the Midsize Business program provides businesses with the materials and knowledge they need to become engines of a smarter planet.