The Anatomy of Sales Decisions: Blending Data Science and Behavioral Science to Accelerate Sales Results

By Jason Loh On Sep 25, 2018

To learn more about decision-making in enterprise organizations, attend Anaplan CEO Frank Calderoni’s Dreamforce speaking session on Tues, Sep 25, at 1pm.

In the world of sales, decisions are everything. What to sell, where to sell, how to sell: the future of our organizations, as well as the success of our employees, depends on how we decide (and re-decide) these questions, every day.

For years, sales leaders have based decisions on experience and gut instinct. Today we know from behavioral economics that our decisions are often biased. Instead of being rational actors, we’re subject to a host of unnoticed tendencies. For businesses, these biases can be devastating when decision-making is spread across an entire organization, with individual stakeholders locked in functional silos. In these cases, individual biases and assumptions go unchecked, keeping the larger sales organization from acting with more intelligence and better foresight.

Forward-looking sales leaders utilize wide-ranging modeling and scenario planning. These strategies reflect the realization that decisions made in any corner of a business affect what happens to a sales team, and vice versa. Supply chain, finance, marketing, HR, IT: these units are no longer autonomous entities. The decisions made in each directly shape the range of options available to sales leaders.

Sales leaders who can tap coordinated intelligence from multiple stakeholders—who can use their data to distribute sense-making insights throughout the organization—will have first-mover advantage. Advanced calculation engines will process large amounts of data, teasing out the insights that enable smarter, more focused sales strategies. This technology will distribute data in different forms, instantly, to all relevant decision-makers. Advanced modeling will give sales leaders the power to try out different sales scenarios and calculate the most optimal. Machine learning will add insight, helping sales leaders more quickly identify ideal options. Companies that can’t, will find themselves playing catch-up.

Together, these approaches will mitigate bias and extract actionable insights from complex data enriched by the entire organization, making sales organizations as a whole smarter than the abilities of any single decision-maker in them. Teams activating their ability to instantly respond to, and even stay ahead of, changes in the market—wherever in the world those changes happen—will beat their competitors to the finish line.

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