Seeing Further: Cognitive Diversity Needs a Plan in Pharma's Asymmetric Game
In the world of pharmaceutical innovation, where breakthroughs often hinge on spotting the unseen or connecting disparate dots, I’ve long held to my adage: without a plan, 10 men can see no further than one. This isn’t just Geordie wisdom - it’s a core IDEA Pharma principle I’ve returned to repeatedly, whether framing how teams avoid symmetric traps in “I Never Thought Of It That Way” or urging higher suspicion in uncertain environments in “When is the right time to have a high Index of Suspicion?”.
Today, as we navigate an era of accelerating complexity in drug discovery, this principle takes on new urgency when applied to cognitive diversity.
Cognitive diversity - the range of perspectives, experiences, problem-solving styles, and knowledge bases within a team - has emerged as a powerhouse for innovation. Research shows that teams rich in cognitive diversity can boost inventiveness or creativity by up to 20% and reduce risks by 30%, particularly in high-stakes fields like R&D.
In pharma, where siloed expertise in areas like chemistry, biology, data science, and regulatory affairs can stifle progress, blending these with “outsider” views from behavioral economics, anthropology, or even design thinking can unlock asymmetric learning: that edge where one team’s insights outpace the competition’s.
But here’s the core of the ‘plan’ part - diversity alone isn’t magic. As my adage suggests, without a deliberate plan to integrate those varied viewpoints, a team of ten might as well be one myopic individual, bogged down by miscommunication, unchecked biases, or conflicting priorities. Studies on cognitive diversity in asset management and R&D teams highlight this: while it expands idea generation and overcomes blind spots (think evaluating a drug’s pipeline with inputs from a former journalist spotting market intel or an engineer critiquing manufacturing feasibility), it demands psychological safety and inclusive practices to thrive. Without them, friction erodes the benefits, leading to poorer coordination or even lower performance in some cases.
True leverage comes from what I call asymmetric learning: deliberately pursuing unique sources, cross-domain integrations, and proprietary insights that competitors miss. As explored in “Embracing Asymmetry: Why Symmetric Learning is the Real Default Trap”, symmetric teams (even diverse ones) default to the same conferences, datasets, and echo chambers - leading to commoditized progress. Cognitive diversity, channeled through a plan, enables consilience: “jumping together” across disciplines to synthesize breakthroughs, as detailed in “Jumping Together: Consilience as the Engine of Asymmetric Learning”.
Consider historical parallels. The Manhattan Project’s success wasn’t just from gathering brilliant physicists; it was the orchestrated interplay of engineers, chemists, and military strategists under a unified plan that delivered results. In modern pharma, we’re seeing echoes in interdisciplinary setups. Biotech startups often outperform big pharma here, assembling agile teams that mix quantitative modelers with qualitative storytellers to navigate uncertainty. In a recent podcast interview, I discussed this with a biotech CEO, who felt that having the team in the office - with corridor chats, coffee chats, and unplanned serendipitous sightings - was a real advantage over large pharma’s more remote setups. This aligns with fostering “planned serendipity” through cross-disciplinary collaboration and breaking silos, as in “Lone genius, slow hunch, play and delight”. Similarly, Lilly balances scale with agility by structuring discovery into small, biotech-like teams with dedicated leadership and innovation focus, per my conversation insights in “The large and the agile”.
A recent example: NVIDIA’s collaborations with Merck (KERMT model for small-molecule discovery, pretrained on over 11 million molecules to predict ADMET and accelerate optimization) in late 2025 and Lilly (a $1B co-innovation AI lab announced in January 2026, focusing on continuous learning systems connecting wet labs with AI) highlight planned ecosystems where AI specialists team up with biologists for rapid iteration. These aren’t random assemblages; they’re deliberate integrations fostering shared knowledge.
Tied to the current landscape, the FDA’s January 2025 draft guidance on AI in drug development (”Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making for Drug and Biological Products”) underscores the need for structured diversity. It introduces a risk-based framework, including a 7-step credibility assessment, for AI models supporting regulatory decisions across the product lifecycle - from nonclinical predictions to clinical trial optimizations. This isn’t just bureaucracy; it’s a plan for harnessing cognitive diversity in AI-driven teams. By emphasizing credibility assessments (evaluating model risks against context of use), it encourages pharma leaders to build teams that include AI ethicists, data scientists, and clinicians to mitigate biases and ensure transparency. As we enter 2026, with EMA-FDA joint principles promoting high-quality data and accountable governance, ignoring this could mean falling behind in an industry where AI-augmented discovery is becoming the default.
So, how to put this into practice? Start with intentional team design: audit for cognitive gaps, not just resumés. Foster “debate rituals” like structured devil’s advocacy sessions to surface diverse views without descending into chaos. Measure outcomes not by consensus speed but by insight quality - did we spot that rare disease biomarker earlier? In my experience, companies like Roche’s innovation labs (building on Genentech’s legacy of tacit knowledge accumulation, cross-domain integration, and NVIDIA collaborations for accelerated AI models) exemplify this, blending cross-disciplinary “pods” to reduce attrition in early-phase decisions - as revisited in “The obvious vs the obverse”.
Ultimately, cognitive diversity isn’t about ticking boxes; it’s about seeing further. With a plan, those ten minds become a telescope, revealing horizons one alone could never glimpse. In pharma’s asymmetric game, that’s the difference between incremental tweaks and paradigm-shifting cures.