SPEAKER:
Steph Plowright, Director of Strategy & Innovation, Nazaré, part of Inizio Engage
Wil Procter, Director of Strategy & Innovation, Nazaré, part of Inizio Engage
KEY TAKEAWAYS:
· Only 24% of field teams achieve the multichannel effectiveness the industry claims as its priority
· Metrics systems actively reward volume behaviors that leadership says it is abandoning
· 89% of organizations remain stalled at AI pilot with the barrier being prioritization
· 84% of leaders have no Gen Z HCP engagement strategy, despite a closing competitive window
· The differentiating organizational capability for 2026 is not AI or omnichannel, it is deprioritization
Three-quarters of the pharma industry is operating below the field excellence standard it has already agreed to. That figure drawn from Nazaré/Inizio Engage proprietary research across field excellence leaders, is not a capability issue, it’s a governance and prioritization challenge. The organizations surveyed understand what great looks like. They have read the same playbooks, aligned on the same strategic direction, and commissioned the same capability investments. The execution gap persists anyway, and the research from Wil Procter and Steph Plowright at Pharma 2026 makes a specific, uncomfortable argument about why: the measurement systems governing daily field behavior are actively contradicting the strategies those systems are supposed to serve.
"The vision, we understand what great looks like," Plowright said, "but where we're struggling is closing that gap between what we believe great looks like and actually executing on that gap." The instinctive response to that kind of gap; more training, more pilots, more technology investment, is precisely what this research identifies as the wrong prescription – and would only succeed when paired with shaper organizational prioritization.
Twenty-Two Priorities Is the Same as None
The pharma industry's default response to underperformance is capability investment. Skills gaps get training programs. Execution gaps get enablement platforms. The Nazaré research suggests this reflex is not solving the problem, it is unintentionally perpetuating the problem when organizations add capabilities faster than they remove competing priorities.
Consider what happens when an industry tries to define what a great field rep looks like in 2025. Procter described the outcome directly: "22 priority skills, far too much for one individual to really hone in on. But it feels like we're getting some kind of consensus around the most in-demand skills, and those most in-demand skills are these power skills that actually cut across the roles." The T-shaped model Procter proposes generalist power skills spanning all roles, specialist depth within functions, is a reasonable structural response. The more revealing data point, though, is the 22-skill list itself. That list is not an HR planning failure. It is the field-level expression of an organization that has not learned to say no. Every capability added to the profile reflects the increasing difficulty organizations face in making clear trade-offs about what matters most.
The consequence shows up at the interaction level. When 64% of leaders say they are prioritizing customer-centric engagement and 50% are prioritizing communication excellence, those numbers look like strategic clarity. Procter's counter-evidence lands differently: " STEM analysis shows that 74% of calls with HCPs are not fully exploring their needs." The gap between stated priority and observed behavior is a diffusion-of-attention failure. When field reps are accountable for 22 concurrent priorities, none receives the sustained practice required to become automatic. Investment without elimination produces the appearance of progress.
The same dynamic explains the AI adoption numbers. Among the organizations surveyed, 89% remain stalled at pilot phase, a figure that has not meaningfully shifted year-on-year. "A lot of organizations are still stuck at pilot phase," Procter acknowledged. "When we asked similar questions last year, we saw a proliferation of pilots, everyone very excited about it. But it seems this year people are still kind of stuck at that stage, except for the leading organizations who again are prioritizing ruthlessly." The differentiator is not what the 11% added. It is what they stopped.
The Metrics Dashboard Is Running Your Strategy
If capability overload explains why field teams are confused about where to focus, the research surfaces a harder finding about why they stay confused: the measurement systems governing their daily behavior contradict the strategy those systems are supposed to serve.
"What we're saying we want is those cross-functional partnerships, that collaboration, the customer centricity, the real value driving over a long period," Plowright observed. "But what we're actually rewarding is that volume we talked about in the first trend." Dashboards tracking call frequency, reach metrics, and activity counts send an unambiguous behavioral instruction that overrides what the current strategy deck says about quality engagement. This is not a measurement lag. It is an active contradiction that many organizations continue to reinforce through legacy measurement systems.
Plowright's framing that "metrics are just not neutral, they really drive behavior" redefines the entire conversation. If every KPI is a behavioral instruction, then a metrics dashboard built around volume metrics is not a neutral reporting tool. It is a policy document that has not been updated since the previous strategic era. When that policy conflicts with stated strategy, the policy wins. It wins every quarter, every performance review, every coaching conversation.
Procter frames AI's primary field excellence value as making qualitative assessment scalable and enabling the kind of relationship quality measurement that currently depends on a manager's subjective observation. That potential is real but conditional. AI platforms are only as good as the data infrastructure beneath them, and data infrastructure reflects what organizations chose to measure in the first place. AI tools trained on existing CRM data will scale whatever the current metrics incentivize, including the volume behaviors organizations are trying to move beyond. The progressive metrics evolution Procter and Plowright describe, from partnership indicators through quality dialogue to strategic relationships to commercial outcomes, is not a technology project. It is a leadership decision about what gets counted and what gets rewarded, and it requires someone with the authority and the appetite to retire the old scorecards.
Discover more on this topic at Pharma Commercial Data & Tech Europe 2026 (4-5 November, London) Europe's collaborative home for data and tech pioneers. Visit the website here.
Two Windows That Are Already Closing
Two of the five trends Procter and Plowright identify share a characteristic that rarely receives adequate urgency in strategic planning cycles: they represent closing competitive windows, not future-dated initiatives. The organizations that move first build structural advantages that latecomers cannot simply purchase.
The Gen Z engagement gap is the clearer example. "This is not just about age, this is not just about channel tweaks," Plowright argued. "This is about recognizing the people that are going to become the decision makers of tomorrow and engaging with them now so that we are not behind the game before we've even started." The case for urgency is influence infrastructure, as HCP networks shift from hierarchical KOL structures toward peer-based recommendation, credibility is built before seniority rather than after it. Relationships formed now will determine access a decade from now. Against that backdrop, the finding that 84% of leaders have no defined strategy for Gen Z HCP engagement is not a planning gap. It is a decade-long competitive disadvantage being deferred one annual planning cycle at a time if left unaddressed.
Among the 11% of organizations that have moved AI meaningfully beyond pilot, the common factor is not technology investment but decision architecture. Procter describes a three-filter framework for evaluating which AI projects to advance: "The first lens is AI projects that deliver value to the customer. The second is things that address individual identified internal pain points. And the third thing, prioritizing projects that provide a rich layer of data that can be the platform for better decisions and better AI platforms." The filter is notable for what it excludes; AI for visibility, AI for reporting optics, AI because competitors are doing it. Both the Gen-Z gap and the AI stall trace back to the same governance failure: the organizational reflex to treat strategic choices as future obligations rather than present infrastructure investments with compound returns.
The Capability That Cannot Be Bought
The through-line of this research is not ultimately about field skills, AI adoption, or metrics reform. It is about a capability that sits upstream of all five trends: the organizational ability to choose, and to stop. The 22-skill list, the proliferation of stalled pilots, the attempt to pursue every identified trend simultaneously, each is a symptom of an organization that has not institutionalized strategic triage. The 11% and the 24% are the same organizations viewed from different angles, not better-resourced but more disciplined in elimination.
Plowright’s prescription for where to start is deliberately uncomplicated: "If we think about that triple win approach, we want to add value to our organizations, to our HCPs and the healthcare system but most importantly to patients. So start focusing on where the most friction is coming from. Go there."
The structural problem is that pharma organizations are not built to follow that instruction. Consensus-driven governance, matrix organizational design, and risk-distributed accountability create systems where launching a new initiative requires one signature and stopping an existing one requires twelve. The barrier to ruthless prioritization is not intellectual,most field excellence leaders can identify their single biggest friction point in under five minutes. The barrier is that their governance architecture does not give them permission to act on that answer. Every existing program has a sponsor, a budget line, and a stakeholder group prepared to defend it. The fix is not simply a better prioritization framework. It is explicit, senior-sponsored permission to deprioritize – an organizational architecture that makes stopping as legitimate as starting.
Procter’s diagnostic reduces the complexity to one question: "What's the one thing that if I solve this, would make everything further down the chain a whole lot easier?"
For many field excellence leaders reflecting on this research, the starting point may well be their own metrics dashboard. The question is whether their organization is set-up to let them change it.
To get you highlights of Pharma 2026 faster, we are using generative AI technology to summarise the transcripts of the sessions. If you have any feedback about the summary, please contact lucy.fisher@thomsonreuters.com.
Discover more on this topic at Pharma Commercial Data & Tech Europe 2026 (4-5 November, London) Europe’s collaborative home for data and tech pioneers. Visit the website here.
