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 overnight delivery cialis 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 buy cialis no prescription degree to which companies are connected. Data that used to be harbored within a company’s walls has now “exploded” across organizations, regions and viagra usa trading partners.
The trend demands more cooperation among entities in the supply chain. It’s a business-process problem, says Phull. She notes the order cialis increasing popularity of formal sales and order viagra canada operations planning, one of the cialis no rx required few processes that links the cialis vs levitra entire organization by its very nature. The result is a common set of analytics and buy real cialis 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 generic viagra canadian entities together,” says Phull, “it automatically creates a level of transparency. Then you can work with the cialis soft canada technology stuff.”
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