Category: Beghou Briefs

A year ago, we shared how life sciences companies should adjust traditional incentive compensation plans to account for pandemic-driven changes in life sciences commercialization. Now that we’re a little over a year into the COVID-19 pandemic, let’s revisit the state of incentive compensation in the life sciences industry and determine how companies can keep reps motivated amid the shifting commercial landscape.

Over a year into the COVID-19 pandemic, many life sciences sales teams continue to struggle to visit physicians in person. The “new normal” ushered in by the pandemic forced sales reps to get comfortable with a large amount of digital promotion. The “new normal” also forced multiple commercial teams to work more closely together to service customers in a more tailored manner. And it’s unlikely this digital-first world is going away anytime soon. Just as patients and physicians will likely continue to have virtual appointments post-pandemic, we expect digital promotion to remain a significant part of a life sciences company’s commercial efforts, even as opportunities for in-person engagement return.

Sales forecasts often prove the old adage, “Garbage In, Garbage Out.” Fortunately, the amount of helpful patient-level data – combined with recent developments in analytics software and marketing research – gives every company the tools it needs to forecast sales accurately. Think “Gold In, Gold Out.”

Many life sciences sales reps remain effectively grounded and unable to make in-person visits to health care professionals. As a result, companies have shifted to non-personal promotion and virtual meetings with physicians. Though these tactics can be effective, in-person meetings are essential for many reps as they work to develop trust-filled relationships with HCPs and make compelling cases for their products.

Data is the new gold for life sciences companies today. It is the most valued currency. It is the fuel that powers the best forecasts. It is the ultimate hedge against the inevitable vagaries of the marketplace. And commercial teams can never have too much of it.

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.

Companies from all types of industries – from insurance to life sciences to transportation – rely on data to inform their commercial operations. But where do they store, manage and manipulate this data? Many still operate on disparate spreadsheets, emails and off-the-shelf solutions, which typically result in dispersed data that doesn’t serve their specific interests. So, it’s no surprise many life sciences companies, for example, identify data organization and collection as one of their greatest commercial challenges, according to our 2019 Emerging Pharma Pulse Report.

The influx of data in the pharmaceutical industry presents numerous challenges to emerging companies, according to Beghou Consulting’s 2019 Emerging Pharma Pulse Report. We asked over 100 pharmaceutical companies—two-thirds of which had annual sales of under $250 million—about their commercial challenges and goals. I’m excited to share our findings with you.

Thanks to the robust technology housed within mobile devices today, pharma sales forces can access ever-increasing amounts of customer data and information on the go. This accessibility enables sales reps to tap real-time insights and better manage each stage of communications with physicians – from planning outreach to recording information at speaker programs to reviewing talking points at a physician’s office.

Data management processes for life sciences companies are consistently in flux. This era of change presents great opportunities but also significant potential pitfalls. Life sciences companies need not only whip-smart data scientists, but also the right processes to accommodate the rapid evolution of technology and increase in the quantity of data.