SPEAKERS:
Stephen Onikoro, Chief Operating Officer, PharmaForceIQ
Peter Finlayson, Vice President, Marketing, Palvella Therapeutics
KEY TAKEAWAYS:
- Field-brand misalignment is a perspectives problem as functions optimize rationally for different time horizons with different information—neither team is wrong, both are blind
- Strategically briefed, transparent, and incentive-aligned orchestration deployments achieve 80–95% completion rates
- Every additional portal a rep must open is a discrete adoption barrier; embedded tools eliminate the resistance
- The real output of effective orchestration is physician-ready hypotheses that can be tested and drive value rapidly in the field, not engagement dashboards
When field teams receive strategically briefed, metrics- and incentive-connected orchestration instructions, completion rates reach 80, 90, even 95 percent. That figure will seem implausible to any commercial leader accustomed to single-digit engagement on pushed digital content and recommendations—and it should prompt a direct question about what those high-performing deployments are doing differently.
The answer is not the platform. "For clients who are able to get that buy-in from the start, and we actually tie incentives to all of those initiatives that we're sending through from HQ or from the orchestrator, you get a really high adoption rate," said Stephen Onikoro, COO of PharmaForceIQ. "So you're thinking 80, 90, 95% completion rate on all of those instructions and actual feedback rates because the reps know, hey, this is important for us."
Peter Finlayson, VP of Marketing at Palvella Therapeutics, arrived at the same diagnosis from the brand side. Sales and marketing teams, he argued, are "looking at different slices of reality." Neither perspective is wrong. The time horizons and information sets simply differ, making misalignment a structural feature of how commercial organizations are designed. The question the leaders raised is not which platform to buy. It is whether your organization has done the pre-work that makes any platform effective.
Different Slices of Reality: Why Sales and Marketing Are Both Right
Most pharma organizations treat the sales-marketing gap as a communication problem. The standard remedies—cross-functional workshops, shared dashboards, quarterly alignment summits—address symptoms while leaving root causes intact. Both speakers' evidence points to something more structural: timelines differ, compensation cadence drives metric selection, metric selection drives channel behavior, and divergent channel behavior produces two teams with incompatible definitions of what success looks like in the same quarter.
Finlayson's account of how this plays out is specific: “The way that a salesperson is incentivized is really different, both from a financial perspective as well as a measurement framework, from how a digital or marketing person is incentivized.” Marketing teams, thinking on an annual basis, default to measuring what's quantifiable on that scale—clicks, email opens, engagement rates. Sales teams think in quarterly cycles, optimizing for prescribing behavior change within the current window. Neither team is behaving irrationally. Both are doing exactly what their functional structures reward.
The compounding problem, as Onikoro named it, is that this divergence is invisible to the people executing in the field. "A lot of things happen in HQ, and a lot of discussion is happening in HQ, but the folks in the field actually have no idea what's getting implemented, what those strategies are." The field team doesn't experience a strategic disagreement. They experience irrelevant content arriving at the wrong time, which trains them to treat the next push from headquarters as equally irrelevant. Over time, rational disengagement hardens into cultural resistance that no technology deployment can dissolve on its own.
This dynamic intensifies at predictable organizational inflection points. In companies scaling from specialty to primary care, field team size outpaces marketing's capacity to personalize. Rare-disease companies preparing a first launch face the inverse: a small field force operating in a physician universe where relationships are unusually consequential and information asymmetry between medical affairs and commercial teams is most extreme. The larger the gap between what headquarters optimizes for and what reps experience daily, and the less transparency in the system, the more entrenched the resistance will be by the time a technology vendor arrives.
What would actually close this gap? Finlayson pointed to two keys. First, “It's really important as a marketer that every communication that you have with your field colleagues is really focused on communicating clearly the intent behind the activity or the action.” Sharing the what and the why of a recommendation breaks down one traditional black box.
He also offered a provocative challenge: "Best might be how can we think about what's actually best for the patient and actually best for the company holistically? Maybe it's not your quarterly revenue target or my annual revenue target. Maybe it's something else." This is directionally correct and structurally difficult. Achieving a patient-centric shared metric would require mindset, compensation, and measurement redesign for two functions that report through different organizational hierarchies—which most commercial organizations are not positioned to execute in a single planning cycle.
The Portal Test: Why Most Omnichannel Investments Fail Before They Launch
"Is the tool another portal that they have to use... Because if it is, that's many more barriers right there to adoption." Finlayson's diagnostic should stop any commercial technology procurement conversation in its tracks. The default industry pattern—select a platform, configure it, ensure download or single sign-on access, train the field, measure adoption, diagnose underperformance—buries the adoption question at the end of a process that should begin with it.
The sequencing inversion that actually produces results is more demanding. "Before we even get to the tactical level, they should be bought in at the strategic level," Onikoro argued, "both the field leaders as well as the field reps themselves who are actually going to take part in this execution." Strategic buy-in, in operational terms, is not a town hall announcement or a training deck. It means the field team understands why the initiative exists, what it replaces, and how their completion of instructions connects directly to the performance metrics they're already accountable for. That pre-condition separates the 80–95% adoption cohort from the industry's typical single-digit engagement rates, not just the sophistication of the orchestration logic.
The technology design principle that follows is one PharmaForceIQ has built into its architecture explicitly. Onikoro described a platform that "never ever" asks clients to just adopt a new tool, but instead functions as "an orchestrator that stays in the middle," with execution happening entirely within the client's existing CRM and Veeva workflows. "Whatever instruction is going out to that rep is going out within the best context for what's happening with that rep. It's not isolated from what they have to do on a day-to-day basis. It still exists within the existing workflow."
This is a design philosophy most enterprise omnichannel vendors do not share, because their business model depends on user engagement with their own interface. The tension between vendor incentives—maximize platform stickiness—and client needs—minimize rep workflow disruption—is an underexamined structural conflict in pharma's current technology procurement cycle. When a platform's commercial success requires the rep to open a new tab, that vendor's interests and the client organization's adoption goals are in direct competition from day one.
The practical diagnostic for any commercial team evaluating orchestration tools involves two tests that should precede any feature evaluation: has the field team been strategically briefed on the initiative's purpose and its connection to their incentive structure, and can the tool execute entirely within the rep's existing daily workflow? If either answer is no, the technology will underperform regardless of its capability on paper.
Discover more on this topic at Pharma Customer Engagement USA 2026 (October 27-28, Philadelphia) - where commercial, marketing, medical, data and AI pioneers converge. Explore the agenda here.
The 75% Problem: Reclaiming Physician Interaction Time
The business case for orchestration is typically argued in terms of platform ROI—cost per touchpoint, digital channel efficiency, content utilization rates. Finlayson reframed it in terms that any commercial leader in specialty or rare disease will recognize immediately. "If I only get a finite amount of time with this physician, and I have to spend the first 75% of it developing a hypothesis about how I can add value, what's going on with this customer, what they care about, and what I should be talking about, then I only have this little fragment of time at the end when I can actually do those things. But [what] if I can go in knowing in advance what that customer seems to be engaging about, what they care about, and what HQ interactions happened in the last month?"
That 75% is not a technology inefficiency metric. It is a clinical relationship cost. When physician access windows are narrow and clinical conversations are complex, a single meaningful interaction can shift prescribing behavior in ways that a dozen digital touchpoints cannot. That lost fraction of time represents the difference between a rep who engages as a clinical partner and one who is still orienting when the appointment ends.
The knowledge that matters most in early physician interactions—clinical trial relationships, investigator engagement history, medical affairs touchpoints—lives in systems commercial teams rarely access. "Wouldn't it be great if some of that institutional knowledge was captured and available? So it's not, have you ever heard of Palvella before? And they're like, well actually I was a PI on the trials." The scenario Finlayson described is not a hypothetical failure mode. It is the default condition at most rare-disease first launches. The hypothesis-generation vision requires not just cross-channel signal aggregation but medical-commercial data integration that most organizations have not attempted and many have not mapped.
The redefinition of what orchestration should produce follows directly: "The vision should be equipping our field teams with hypotheses to rapidly test in the physician engagement for in-person interaction and then be able to drive value." Not dashboards. Not engagement reports. Not content utilization summaries. Hypotheses the rep can carry into the next interaction and test in real time.
The Readiness Gap the Industry Hasn't Named
Both speakers' evidence converges on an uncomfortable implication for an industry in the middle of a significant omnichannel investment cycle. The problem is not that effective orchestration tools don't exist. It is that no widely adopted framework exists to determine whether an organization has achieved sufficient incentive alignment and field buy-in to justify deploying them.
This creates a self-reinforcing failure cycle. Organizations invest in technology to solve a coordination problem they haven't yet diagnosed. Low adoption follows. The resulting performance gap gets attributed to the platform—wrong vendor, wrong configuration, insufficient training—triggering another procurement cycle. The speakers' evidence suggests a different interpretation: the technology worked as designed. The organization simply wasn't ready for it.
The actionable sequence that emerges is a staged one. Audit whether field teams understand the strategic rationale behind digital-channel initiatives and whether that rationale connects to their compensation. Assess whether incentive structures create or block the alignment the technology assumes. Test whether any proposed tool can execute within existing workflows without requiring portal adoption as a prerequisite. Define the output not as engagement metrics but as hypothesis-equipped reps entering physician interactions with tested intelligence rather than generic messaging.
The patient-centric shared metric Finlayson proposed remains the aspirational endpoint—structural redesign would make field and brand teams truly coherent. It may also be the endpoint that requires the most organizational runway to reach. The workflow-embedding architecture Onikoro described is the more achievable near-term intervention: it sidesteps structural misalignment rather than resolving it, but it produces measurable results within existing structures.
The principle connecting every argument in this panel is the one Onikoro articulated as a design constraint: instructions reaching the rep within "the best context for what's happening with that rep," embedded in the existing workflow, not isolated from daily reality. Organizations that treat this as a procurement criterion rather than a post-implementation aspiration will be the ones whose next platform investment actually performs. The ones that don't will be back in the same conversation in eighteen months, wondering why the technology didn't work—and buying a different platform to find out.
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Discover more on this topic at Pharma Customer Engagement USA 2026 (October 27-28, Philadelphia) - where commercial, marketing, medical, data and AI pioneers converge. Explore the agenda here.
