Unlocking digital influence in pharma: lessons from DOL Finder 2.0

Why legacy models of influence are no longer enough 

Pharmaceutical companies have spent decades refining how they identify and engage Key Opinion Leaders. These models were built for an era of conferences, advisory boards, and relatively stable hierarchies of expertise. Yet the ecosystem in which scientific influence now operates has changed fundamentally.

Digital channels have become central to professional discourse, peer-to-peer exchange, and the formation of clinical opinion. In this environment, influence is no longer confined to formal roles or visible seniority. In my role at CREATION.co I can see that it is shaped continuously through online conversations, shared interpretations of evidence, and trusted networks of peers. The uncomfortable reality is that many organisations are still applying legacy models of influence to this new landscape and, in doing so, they risk engaging the most visible voices rather than the most influential ones.

Influence has become contextual, networked, and directional

CREATION’s experience working with digital healthcare professional (HCP) data and, more recently, redesigning the second generation of the DOL Finder platform, has reinforced a central insight: digital influence does not behave in the way traditional KOL frameworks assume.

First, influence is contextual, not universal. An HCP may be highly influential in discussions around prevention but carry far less weight when treatment sequencing or policy implications are debated. Influence fluctuates by topic, moment, and audience. Static lists or single scores inevitably risk flattening these distinctions.

Second, influence is networked, not hierarchical. Digital influence emerges from how HCPs are positioned within professional networks: who references their views, who amplifies their commentary, and how ideas propagate across communities. Seniority, publication history, or follower counts alone tend to be weak proxies for this kind of influence.

Third, influence is directional, not symmetrical. Some clinicians primarily shape the thinking of others, setting agendas and framing debates, even if they engage other HCPs infrequently themselves. Others play a different but equally important role: they amplify, interpret, and spread specialist insights across wider professional communities. Distinguishing between those who originate ideas and those who carry them forward materially changes how engagement strategies should be designed.

Taken together, these dynamics suggest that influence is not something an individual simply “has”. It is something that is continuously negotiated within networks, shaped by trust, relevance, and timing.

Why metrics alone are not enough

As digital engagement has expanded, many organisations have responded by investing in dashboards and quantitative metrics: post volumes, impressions, engagement rates, sentiment scores. These measures are useful, but insufficient on their own.

Quantitative metrics describe what is happening. They rarely explain why it is happening.

In practice, the framing of an argument, the consistency of an HCP’s narrative, and the degree to which peers treat their contributions as credible are often more consequential than raw activity levels. Without qualitative context, organisations can draw false confidence from high numbers while missing early signals of shifting opinion, emerging concerns or early leadership.

This is one of the reasons many digital influence initiatives struggle to move beyond monitoring into decision support.

What building dol finder 2.0 taught us

DOL Finder 2.0 was launched with the explicit aim of addressing these limitations. While the platform itself is a concrete product, the lessons from its development are more broadly applicable to any organisation seeking to operate effectively in a digitally mediated scientific ecosystem.

The most important lesson was that the challenge is not data scarcity, but interpretation. Making sense of digital influence requires the integration of three analytical dimensions:

• Context: understanding which topics, therapies, or questions an HCP is influencing at any given time.
• Networks: mapping how influence flows between professionals, rather than assuming it radiates outward from a single individual.
• Narrative: capturing the themes, tone, and framing that give quantitative signals their meaning.

In DOL Finder 2.0, this integration takes several practical forms. Influence is assessed through peer-to-peer interactions rather than reach alone. Conversation network visualisations make visible the otherwise hidden structures through which ideas travel. AI-generated digital persona summaries translate large volumes of online activity into coherent narratives that can be interpreted by medical, commercial, and strategy teams to understand individuals better from a qualitative perspective, answering the question; ‘what do they care about?’

The platform does not replace human judgement. Instead, it aims to equip decision-makers with a more faithful representation of how influence actually operates.

Strategic implications for pharmaceutical leaders

For senior leaders across the pharmaceutical value chain, these shifts have concrete implications.

• Medical Affairs teams can move from broad-based engagement to network-aware scientific exchange, identifying which voices shape discourse on specific clinical questions and tailoring engagement accordingly.
• Commercial and omnichannel leaders can detect early sentiment shifts around products or classes, enabling more timely and relevant messaging that reflects how clinicians are actually interpreting emerging evidence.
• Clinical development teams can observe who reference trials, products or treatment methodologies, surfacing signals that may inform engagement strategies.

So what should leaders do next?

For pharmaceutical leaders, the next step is not to replace existing engagement models overnight, but to augment them with a more realistic understanding of how influence now operates. This means testing assumptions about who truly shapes opinion in specific therapeutic conversations, investing in capabilities that surface network dynamics and narrative context, and embedding these insights into everyday decision-making across medical, commercial, and clinical functions. Organisations that treat digital influence as a strategic learning system, rather than a reporting exercise, will be better positioned to anticipate change, engage credibly, and lead with relevance in an increasingly connected scientific ecosystem.For leaders interested in exploring how these principles can be operationalised in practice, the recent launch of DOL Finder 2.0 offers a concrete example of how network-aware, context-rich digital influence intelligence can be embedded into everyday decision-making.

Further detail on the platform and its capabilities is available at dolfinder.com.