At most companies, key supply-chain data resides in transactional systems. “No one knows how to use it, or what to do with it,” says Phull. The result is “islands” of analysis, frustrating efforts by top executives to foster cooperation across disciplines. Big data needs context to be of use, she says. Only then can it be deployed to create specific analytics, with both leading and lagging indicators to paint a true picture of demand.

Big data has always been around, albeit under other labels. What’s different now is the degree to which companies are connected. Data that used to be harbored within a company’s walls has now “exploded” across organizations, regions and trading partners.

The trend demands more cooperation among entities in the supply chain. It’s a business-process problem, says Phull. She notes the increasing popularity of formal sales and operations planning, one of the few processes that links the entire organization by its very nature. The result is a common set of analytics and conclusions that can be acted upon by key partners.

“If you don’t have one wall of truth,” says Phull, “you’ll never be able to drive accountability in the organization. Data is data – it can’t be actionable in itself.”

The first step toward achieving transparency is to create a common data guide. The effort ensures that all partners share a common definition of the customer. Step two is to achieve “true integrity” in the data, while allowing access to all relevant individuals. The third step is the use of shared analytics.

“Once you bring the entities together,” says Phull, “it automatically creates a level of transparency. Then you can work with the technology stuff.”

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