Big data moves sales from an art to a science

Sales reps who get big data analytics prior to making a deal can obtain the right pricing and capture the appropriate profit margin.


Image: iStock/dolgachov

The deals that great salespersons make aren't always the wins everyone assumes is the case. From a pure sales standpoint, major wins always seem big, because sales dollars and the number of deals is how sales has traditionally been measured. Nevertheless, in a back office, possibly even six months after the deal was made, someone will discover that the deal's target profit margin was missed after all of the sales costs are totaled. There are many reasons why.

First, sales and finance are on different corporate missions, and the two groups seldom interact with each other. Second, the sales dynamic is to complete the deal and then forget it after they move it over to the operational folks to fill the order.

With big data, there is the opportunity to not only make the big deals but also to ensure upfront that a deal yields the profit margins everybody hopes it will.

"We find that we can help companies leverage data they already have in their ERP (enterprise resource planning) systems by applying analytics," said Edward Gorenshteyn, director of product management for Vendavo, which provides sales profit optimization solutions.

Gorenshteyn said that salespersons today face more sophisticated buyers and negotiators. "To negotiate comfortably in this environment, sale reps need more information," he added. This information might be drawn from data derived from outside business services about a given customer-company, or from a customer's financials, or from the customer's past transaction history and buying trends with the enterprise. "It's all about organizing the data and running the right kind of analytics," Gorenshteyn said.

For this purpose, Vendavo uses a HANA in-memory data platform that it integrates with an on-premise solution. The resulting analytics engine can process several billion rows of data, using over 1,500 value hypotheses to determine the profitability potential of a sale. "We set up playbooks that assist our customers as they learn how to 'fish' this data for results," said Gorenshteyn.

Some companies are seeing results that are building lift into profit margins. Gorenshteyn cited one manufacturing organization that experienced $400 million in incremental profit, and another large enterprise that saw $2.5 billion in incremental profit.

"The analytical data enables companies to identify areas where they're losing profits, such as not charging freight on orders, or offering excessive discounts," Gorenshteyn said. "It also allows companies to look at individual customers and what their willingness to pay is, as well as what the risk factors are. When all of this data is considered in its entirety, target pricing for orders can be predetermined."

The ultimate linkage back to the sales force is delivering the results of these analytics to their mobile devices in the field, where the deals are made. This is the "moment of truth" where it is incumbent on the sales person to get the deal done by obtaining the right pricing and capturing the appropriate profit margin. For many, it's a golden opportunity to put big data to work -- and to make progress in sales "deal management" that had not been possible.