Business analytics software provider FusionOps has launched what it called a "prescriptive analytics" tool that it says leverages big data to help businesses make better supply chain decisions.
The Mountain View, Calif.-based company said yesterday that it will offer the analytics tool as an extension of its cloud-based business intelligence platform used by such customers as Columbia Sportswear Co., wholesaler H.D. Smith, and pharmaceutical giant Merck & Co.
Analytics is a fast-growing area, but most companies lack the computing resources or IT expertise to apply data-mining techniques to their disparate applications and departments, the company said. FusionOps said it solves the problem by creating one pool of data and then applying thousands of proprietary algorithms to provide users with actionable information. The company retrieves user data, processes it in the cloud, and then converts it into what Shariq Mansoor, FusionOps' chief technology officer, called "intelligence models," allowing customers to fine-tune inventory levels, reduce costs, and improve service reliability.
The algorithms simulate different supply chain scenarios to go beyond "diagnostic analytics," or "Why did it happen?" and "predictive analytics"—"What will happen?"—to "prescriptive analytics," which recommends the best course of action, according to FusionOps.
Until recent years, this approach would have been impossible for all but the largest corporations. However, the rise of cloud computing democratizes the process because of the cloud's ability to handle massive amounts of data.
"New models are emerging so users can do a root-cause analysis to see why things happened. You can't fix a problem unless you know why it happened," Mansoor said. "By looking at the data and using machine learning, you can predict every SKU of demand."
With that level of analysis, companies can avoid being stuck with warehouses stuffed with excess inventory when demand changes suddenly due to changes in weather, fashion, seasons, or commodity prices, FusionOps said.
