Companies are under-investing in cohesion, and it’s hurting commercialization. New data analyze where the system has gone awry — and how to fix it.
SUMMARY POINTS:
- A crisis of cohesion cuts across teams, data/analytics, tech and experience, new research suggests.
- This under-investment in executional capabilities is hurting commercialization.
- Findings were reinforced by speakers and audience polls at a recent event.
- Top performers advised keeping playbooks ‘always on’ and modular.
- A ‘foundations first’ mentality can enable agile, omnichannel execution.
As the rising tide of instability in today’s business climate reaches a high-water mark, companies are under-investing in the very areas needed to confront that volatility.
That was the takeaway from recent research involving biopharma executives that showed 60% of commercial leaders say they’re launching alongside one or more new teammates, yet only 13% of respondents cited “team readiness” as a top improvement priority.
“We’re definitely under-investing in team cohesiveness,” said AstraZeneca’s Jing Jin at a panel during last week’s Reuters Pharma Customer Engagement event that was designed to premiere and discuss findings from Beghou’s inaugural “Commercialization that Works” research activities.
“One of the biggest gaps I see in industry,” added Jin, who’s AZ’s director of commercial data science and artificial intelligence (AI), “is not embedding your analytics and data science function early enough in the launch phase or launch planning.”
A similar sentiment was seen in the data, with less than half of study respondents saying they’re prioritizing “operational excellence” in the next 12 to 18 months. And while 73% said they form a cross-functional team before launch, that’s not the same as getting that team ready. Indeed, more than half said they’re not confident that their launch planning horizon is sufficient.
This not only suggests a crisis of cohesion — but a technological one, too. By neglecting foundational elements like operational excellence, companies may be holding themselves back from experimenting with next-generation tools, like advanced analytics, AI and personalized engagement. To wit: Leaders said data, analytics, tech and evidence weaknesses had the biggest negative impact on success.
A new baseline
The first survey-based input for our research, which finished fielding in October, was intended to establish a current baseline of what’s working and not in biopharma commercialization. Its 120 respondents were all senior pharma commercial execs, spread evenly across four cohorts: marketing, market access, data/analytics, and commercial operations. All company sizes, from emerging to small/medium to large, were represented evenly.
Although the AI race as well as pricing and policy dynamics have all added to complexity, instability in pharma is far from a fresh phenomenon. Variables such as approval delays, corporate reorganizations and budget shifts, not to mention shifting customer expectations, are commonplace.
Against this backdrop, then, the finding that companies are still under-investing in areas like team readiness and cross-functional alignment was counterintuitive. Nevertheless, it was reinforced by live audience polling: 92% admitted their current teams had never launched together before, and most (69%) said they had been in their current role for less than five years.
If you haven’t worked together before, that weaker muscle memory could make it tougher to reach peak performance in a high-stress situation like drug launch, especially if the structure is also lacking.
At the Reuters Pharma event, the panelists from AZ, Averitas Pharma and Novo Nordisk — who are leaders in data science, medical affairs and marketing, respectively — explained how the undercurrent of instability translates into their roles. They also shared how they address it via four mainsprings — teams, data/analytics, tech and experience — that are the “killer apps” of cohesion.
Teams: engineering decisiveness
“We've really stopped viewing launch as just a milestone,” declared Audrey Carnevale, associate director of medical communications at Averitas.
She described her medical affairs team as a “continuous cycle of always pressure-testing playbooks and strategies, ensuring we have modular content and flexible review cycles that allow us to be adaptable and timely when new medical evidence is available.”
Because of that, Carnevale added, when the team communicates with customers, “It's coming off as a cohesive, continuous and purposeful engagement that's not fragmented or redundant.”
For Novo's Prem Schoff, director of owned channel strategy for omnichannel, instability requires operating in an agile fashion — the “lower-case kind,” he clarifies, rather than the formal, Agile-for-business methodology. That entails a carefully planned structure while at the same time building in plenty of room for flexibility to deal with unforeseen circumstances.
He’s compiled a “channel strategy playbook” for each of his owned media channels with relevant benchmarks so brands and agencies know what good looks like. He also utilizes the drugmaker’s customer data platform to pipe real-time insights directly into a CRM, so that reps can get alerts whenever, say, a doctor is on the healthcare professional (HCP) website looking at efficacy data or downloading a copay card.
Data: aligning on metrics
AZ’s Jin doubles down on instability, almost embracing it.
“Instability to me, from a data science perspective, is not a problem to eliminate. It’s a signal to harness,” she said. “Our job is to turn the signals into fast learning and then translate that into actions that can be supportive for our medical or commercial teams — to quickly adopt and learn best.”
In our study, 77% of data and analytics execs cited “timeliness of updates as new data become available” as their top success factor for making good launch decisions. For instance, Jin cited the use of propensity score modeling, as part of early launch planning, to determine which HCPs are likely to be the next adopter. That way, “Your sales team can focus their effort on the most likely starters,” she advised.
The panelists agreed that simple data wins sometimes out-perform shiny tech. For example, non-traditional data like electronic health record (EHR) signals, Jin said, can provide very clear indicators.
“That's a simple data point that’s powerful enough to give your rep a very clear action to take to drive the next set of engagements,” she said, adding that AI can orchestrate the ensuing volume of rep-trigger emails.
All three panelists also went on to share some of their most promising technology use cases. The takeaway: “Focusing on the foundation is critical and allows you to build and do more of those exciting capabilities with your mar-tech,” said Schoff.
Tech: buy, build, integrate
For instance, most pharma companies prefer to buy rather than build their AI stacks, our data suggest, and Schoff said he’s reaping big gains from one off-the-shelf tool. Novo, he said, saw a 90% boost in physician registrants for its main professional-facing website by leveraging a third-party AI tool for running test-and-learn trials and serving up content based on a clinician’s digital behavior.
“We used an out-of-the box machine learning element,” he noted. “It wasn't really that heavy of a lift.”
The tool that ran the A/B tests is called Adobe Target, and the Novo property was NovoMedLink, which serves up medical news to HCPs and can also take orders for product samples.
Buy-or-build preferences varied widely by tool type, per our study. Some 80% of the data/analytics respondents said they buy their CRM platforms. But buy rates fell from there, with 60% buying their omnichannel platform and just 3% buying a customer data warehouse. AI stacks were split 50% buy and 50% hybrid (a combo of buy and build).
That said, tech tools work best as part of a unified whole. Some 67% of data and analytics execs in the study said system integration drove success.
On the flip side, late or incomplete data integration, siloed systems, and legacy tech platforms were some of the common problems seen in the research as having a negative impact on commercialization.
A tech stack without proper integration “really could be a weak point,” cautioned Schoff. “We found this out in multiple projects where we went to launch. We had APIs in place, but there was something that wasn’t solved in the beginning that we had to go back and check.”
Experience: scaling empathy
Experience refers to the contextual layer that enables all of the above behaviors to make patients and clinicians feel heard. Tactics like patient hubs, copay card programs and marketing campaigns may fulfill business requirements. But neither patient nor HCP should become secondary to the standard operating model.
On the professional side, Carnevale cited a case where Averitas mined its medical information apparatus to understand questions from HCPs, then tapped market research and med ed to understand their motivations and leaned on the field team to bridge educational gaps.
The example highlights the capability of medical affairs to span silos separating science and HCPs from the commercial group. Carnevale advised leaning into this ability to support strategic imperatives like omnichannel engagement.
But companies may not have developed quite as lucid an understanding of patients’ pain points. In our survey, only 20% of marketers (HCP and patient) said they’re using patient journey and insights to do cross-functional planning, which is where experience enables significant growth and brand connection.
And only 11% listed patient-centric programs and support as top factors for commercialization success. Nevertheless, many are trying to acquire the necessary context for personalized content, which marketers rated as among the top “make-or-break” requirements for a company’s ability to understand and engage with its customers.
These data suggest that aligning systems to support patient success is a work in progress. Likewise, adopting a more nuanced approach to customers across the ecosystem and converting to a more empathetic mindset remain long-term goals.
The Commercialization that Works research is an ongoing project involving surveys, 1:1 interviews, and panels to inform what’s working and not in biopharma commercialization over time. We will continue to share our inaugural insights later this month with a webinar (see below), and Beghou’s LinkedIn page will feature additional content, including the full research report, video interviews with experts, infographics and more.
Register for our webinar, “Rethinking Life Sciences Commercialization for 2026: What’s Working, What’s Not, and What’s Next.” Join Stemline Therapeutics and Beghou on Nov. 13 at 11:30 AM ET for a deeper dive into our initial findings from life sciences leaders on what drives — or derails — commercialization today.
