Advanced analytics refers to the processing of large amounts of data, progressing from "prescriptive" to "descriptive" to "actionable," according to Bajaj. In the end, "it's about making the right decisions."
The concept has been around for some time, but many companies are just discovering it. What’s needed, says Bajaj, is a combination of higher mathematics skills, skilled data scientists and functional expertise in applying the analytics.
Behind the push for advanced analytics is the need for retail “mass customization,” driven by a new generation of consumers who want their internet orders delivered quickly and on their own terms. “Now we are seeing companies embracing that,” says Bajaj. The goal is to be “fast, flexible and agile.”
Among the advantages of embracing advanced analytics are shorter lead times – the ability to respond to orders more quickly. But to make that happen, Bajaj says, retailers need to share data with original equipment manufacturers and upper-tier suppliers. “You can’t make effective decisions by yourself,” he says. “There’s a need for collaboration in true terms.”
An advanced analytics platform consists of a cross-functional application that’s connected to multiple functional “silos” and databases, Bajaj says. A second requirement is the ability to engage in both descriptive and prescriptive modeling. “With so much data available,” he says, “we need to be looking forward to make the right decisions.”
A third necessity is reliance on the still-developing Internet of Things, which consists of multiple connected devices. “The systems are talking back to you,” says Bajaj, “and telling you what to do. Data is coming to you really, really fast.”
