"Big data is all about taking information from a variety of different sources, both structured and unstructured, and using that information to make fact-based, meaningful decisions," says Sharpe. To get to that goal, companies must clear a number of hurdles, however. The first "daunting task" is to figure out how to effectively collect, analyze and distribute data from many different sources so that it makes sense and is actionable, he says. Once that is accomplished, the next barrier is to get cross-functional agreement that the data fairly represents each department's operations.
The important thing to keep in mind about big data is that it includes information not only from large, structured data bases that companies know well but also data from new sources, primarily mobile devices, Sharpe says. "There has been an exponential growth in the amount of data from these new sources, and it is being captured in a variety of ways," he says. "The challenge is to combine that unstructured information with the structured information and provide additional insights that enable a company to make better decisions."
For example, he says, if a company is able to understand which customers or delivery locations are profitable and which are not, it can develop very different strategies for serving these customers, he says. "The same is true for products."
To demystify this subject with clients, Sharpe says he starts by helping them think through key strategies they want to pursue - increasingly profitability is on everyone's list. "Then we focus on how we can use this data to look at their customers and products in a different way," particularly determining the total cost to serve, he says. All this gives them the ability to adjust operations, not necessarily in radical changes, but with very intelligent changes that will drive bottom line performance. "So it is really all about the generation and the protection of profits."
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