Are “no-see” physicians actually as hard for reps to get into see as the name suggests? A new report suggests that label may have become a bit of a misnomer for many of the physicians it has been assigned to, as 73% of respondents to the 2019 Emerging Pharma Pulse Report from Beghou Consulting said their field sales representatives are successful at seeing so-called “no-see” HCPs.
For the report, titled What to Do With All This Data?, Beghou Consulting surveyed more than 100 pharmaceutical companies, 66% of which had annual sales of under $250 million, about the challenges they face surrounding data and their sales forces. But one aspect that they don’t find challenging is gaining access to physicians that many companies have classified as inaccessible.
“The ‘no-see’ label stems from past rep interactions when companies thought it smart to assume some physicians were ‘no-sees’ and tried to determine which ones to avoid assigning as targets,” says Beghou Partner Steve Trokenheim. “But it spiraled out of control. Reps started flagging not only the physicians they couldn’t get in to see, but also those they didn’t want to call on. Our report finds ‘no-see’ labels should be taken with a grain of salt. We recommend pharmaceutical companies assign reps to see these physicians—and if they can’t, then it should be noted. But it’s not a good idea to ignore some physicians only because they’re flagged in a database.”
While the report revealed this one area where some emerging pharma companies excel, it also found several areas where they struggle, particularly in the areas of data and analytics.
Underutilization of Advanced Analytics
For the most part, emerging pharma companies fail to fully utilize advanced analytics. Nearly 60% of respondents said they use advanced analytics “somewhat” or “to a limited extent” to generate commercial insights. However, companies realize that data management is a pressing concern for their organizations, and 29% of respondents named “organizing and storing data” as one of their top three commercial challenges.
“A lot of companies can get lost in this data deluge,” Trokenheim explains. “We’ve seen pharmaceutical companies purchase a variety of different data sources and then tell us that they don’t use them. One reason for that is because they don’t have good data management processes or a data management warehouse in place.”
The report suggests that one way companies could get more out of their data is by moving to the cloud. However, while 43% of companies surveyed manage their sales and marketing data warehouse in the cloud, a large number (34%) continues to rely on an on-premises server for a data warehouse. According to the report, this means those companies are missing out on some of the efficiency-enhancing features of the cloud—including increased mobility and access to data, as well as easier and more frequent updates.
“The cloud has only been around for a few years and offers great potential for conducting analytics powerfully and flexibly, but some companies have already voiced concerns about the safety and privacy of their data,” Trokenheim says. “Companies need to realize the lack of information and awareness in terms of the cloud’s many advantages and minimal security risks. Companies that run cloud platforms, such as Microsoft and Amazon Web Services, understand how to address data security issues.”
Inability to Retain Sales Force
A majority of respondents also said that analytics and modeling only play a “moderate” role in their incentive compensation plan design. And at the same time, the report found that many companies struggle to retain their sales reps. More than 30% of respondents identified “retaining sales people after launch” as a top challenge, and 36% said their companies have annual sales force turnover of more than 20%.
Trokenheim provides a recent example of how the lack of analytics and modeling involved in an incentive compensation plan design could ultimately hurt a pharmaceutical company’s bottom line. As he explains, when one of the products wasn’t doing well, it increased the bonus for that product. But a few quarters later, another product was struggling, so it bumped up the incentive for that one. Only that move caused the first product to fall behind. Trokenheim says this situation can be prevented.
“Instead of making changes haphazardly, the company should have reviewed all available data, simulated various scenarios, and determined how to optimize its portfolio’s performance,” Trokenheim says. “That’s one example of how you can analyze data, look at the big picture, and determine the ultimate path forward—instead of following a more simplified approach that can lead to trouble.”
Trokenheim adds that this same lesson could be applied to territory alignment, where only 21% of respondents said they use advanced analytics. A poorly executed territory alignment can lead to disparate payouts in neighboring territories, which can also negatively impact a rep’s motivation and cause them to leave.
“There is a lot of room for improvement,” Trokenheim concludes. “Emerging pharma companies often develop very niche, specialized products and operate with small and lean teams that can really benefit from using advanced analytics to its full potential. And if they don’t use it, then they may find their competitors doing something they’re not—and risk falling behind.”