Bill Belichick doesn’t use analytics. What can pharma learn from this?

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How much does the most successful coach in NFL history rely on analytics when he makes in-game decisions? “Less than zero,” he says.

We’re deep in the Moneyball era. Advanced analysis of large data sets informs decision-making in every major sport and has upended decades-old practices that relied on a coach’s sixth sense. So, it was surprising to hear New England Patriots head coach Bill Belichick recently pooh-pooh the use of analytics.

“I’m not saying it’s a gut thing. It’s an individual analysis based on the things that are pertinent to that game and that situation,” Belichick said. “I don’t really care what happened in 1973 and what those teams did or didn’t do. I don’t really think that matters in this game.”

Belichick’s preference for experience and intuition isn’t all that unusual. This attitude crops up from time to time in our work with emerging pharmaceutical companies, especially when it comes to mapping out sales territories. After all, experienced sales leaders will have a pretty good idea how their territories should look without reviewing a recommendation from an analytical model.

This may sound odd coming from a sales and marketing consultant who uses advanced analytics every day, but this point of view is valid. Just as data fuels an analytical model, experience fuels the human brain’s decision-making processes. And the human mind is a machine of unmatched power, especially in its ability to recognize patterns. Technologist  Kevin Ashton describes how the most advanced practitioners of complex crafts (an NFL quarterback or a radiologist, for example) make sound decisions quickly by recognizing and processing patterns: “[Experts] think more efficiently. The practiced brain eliminates poor solutions before they reach the conscious mind.”

So, we can view Bill Belichick’s brain – with its massive amounts of accumulated knowledge about the game of football – as a powerful analytical model. Belichick is subconsciously processing the millions of variables at play in any game situation.  He performs situational analyses constantly to come up with the decisions that he believes give the Patriots the best chance of success. Just as a robust analytical model does.

Of course, not every team or pharmaceutical company has a Bill Belichick at the helm. So, companies need to strive for balance between an analytics-only approach and an approach entirely dictated by experience and gut instinct.

If an analytical model could account for every variable – and each nuance within every variable – it could provide flawless recommendations to a football coach or a pharmaceutical commercial team. However, a model can’t quantify the play-by-play implications of a left tackle’s slightly sore hamstring. It also can’t perfectly assess the impact of a major hospital system’s evolving policies on sales rep access to physicians. That’s where human input comes in.

That said, analytics can provide helpful guideposts. It can, for example, ensure a commercial team only chooses from the range of options that give it the highest likelihood of success. Our Meridian Alignment Suite helps companies optimize their territory alignment and sales force deployment efforts. The platform, built on advanced analytics, helps clients target the highest-potential markets, allocate field sales representatives optimally across territories, and balance workload and sales opportunities for these reps. And it helps commercial teams accomplish all these important tasks much more efficiently and effectively than they could if they based their efforts entirely on instinct and experience.

In an ideal territory alignment process, there’s a healthy give-and-take between the Meridian-generated guidance and pharmaceutical commercial leaders’ experience-based insights. A model may recommend two territories in Ohio, but experienced sales practitioners will know if the health care professionals in one of those territories are truly promising targets. If they’re not, the company probably only needs to create one territory for the state. The intersection of these two forms of analysis is essential in creating territories that set the company up for success.

So, instead of choosing between Moneyball analytics and Belichickian intuition, pharmaceutical companies (and football teams not led by Bill Belichick) need to embrace both. Human ingenuity and experience-based understanding of patterns can augment an analytical model and help a team or company score touchdowns and product sales.

Author

Dan Schulman is an associate partner at Beghou Consulting. He leads the firm’s San Francisco office.