Big Data Business Models Depend on Differentiation, Delivery: Analyst
Many organizations have rushed to embrace “Big Data,” buying up software platforms that digest massive amounts of data and spit back (supposedly) actionable insight. But making the most out of Big Data requires using those tools as part of an effective business model—something that many an executive fails to consider before ordering their IT staff to buy whatever’s shiniest and most popular.
According to R. “Ray” Wang, principal analyst and CEO at Constellation Research, there are three “ideal” approaches for a data-centric business model. Writing in the Harvard Business Review, he suggested the first approach centers on differentiation: “Big data offers opportunities for many more service offerings that will improve customer satisfaction and provide contextual relevance.”
In other words, a company could leverage its data to give customers faster and more comprehensive services. Wang uses the example of “map-based services that link your fuel supply to availability of fueling stations,” but many others abound. While some companies already offer some variation on differentiation—for example, offering recommendations based on how you browse a particular Website—he feels there’s much more room to explore in this particular category.
The second model centers on “brokering information.” While many companies sell user data—either in raw form, or else packaged as insight—the constant flood of information creates an opportunity for other firms to really drill down into customer demographics.
“The permutations of available data will explode, leading to sub-sub specialized streams that can tell you the number of left-handed Toyota drivers who drink four cups of coffee every day but are vegan and seek a car wash during their lunch break,” Wang wrote. “New players will emerge to bring these insights together and repackage them to provide relevancy and context.”
(Not that left-handed, vegan, coffee-obsessed Toyota drivers are necessarily a growth market, but the example stands.)
Wang’s third model centers on delivery: once an organization generates all that data, how can they best deliver it to those willing to pay? “The most intriguing opportunities… may be in the creation of delivery networks where information is aggregated, exchanged, and reconstituted into newer and cleaner insight streams,” he wrote. “These delivery networks will be the essential funnel through which information-based offerings will find their markets and be monetized.”
Some organizations have the infrastructure and will to deliver data and content from cloud to user—not only carriers such as AT&T, but also tech giants such as Apple and Google. However, Wang views the market as amorphous enough to accommodate new players, as well as companies willing to adjust their existing models in order to take advantage of an evolving market.
A handful of companies are actively trying to figure out the best ways to leverage the cloud, Big Data, and other emerging trends. EMC and its VMware subsidiary, for example, recently announced plans to group their collective data analytics and cloud applications into a single entity called the Pivotal Initiative. A new report from research firm IDC, meanwhile, predicted that investments in Big Data could grow to nearly $10 billion in 2013; most of that funding will apparently divert to the development of analytics and discovery tools.