There’s a problem at the heart of commercial pharma — and if you’re in a leadership role, you’re probably already feeling it. Performance is slipping. Brand teams are under pressure. Marketing is questioning targeting quality. Sales leaders are hearing frustration from the field.

It’s not always clear where the disconnect is. But more often than not, it starts with the same assumption that’s shaped commercial strategy for decades: the belief that a static list of high-decile HCPs is enough to build campaigns, assign reps, and allocate budget.

The Limitations of Static Lists

We’re still building targeting models the way we did in the 1990s. Once or twice a year, a list is created — usually with the help of consultants — ranking physicians by their historical prescribing volume. The field works from that list until the next one comes along. And we hope it reflects reality. The trouble is, it doesn’t. And the longer we wait to replace this model, the more we lose.

After more than 30 years in the industry, I’ve seen how ingrained this approach is. But I’ve also seen the consequences of sticking with it too long. At best, static targeting leads to wasted effort. At worst, it means missing the patients who need us most.

Let’s be honest about what this approach is costing us.

When you rely on data that’s three to six months old to define your highest-priority HCPs, you’re already behind. You’re looking at who used to matter in a given therapeutic area — not who’s emerging, who’s changing behavior, or who might be newly relevant this month.

Prescribing volume only tells you one part of the story. You know who wrote the most scripts last quarter. What you don’t know is who just changed their treatment behavior, who visited your brand’s website, or who is seeing a surge of relevant patients in their practice right now. You don’t know who matters today, only who used to. And that’s a costly delay.

This rearview-mirror approach to the market has real consequences. Campaigns are based on the wrong assumptions. Reps walk into calls with stale information. And you fall into what we call drift — the widening gap between the customer strategy you design and what’s actually executed in the field.

One of our customers at ODAIA described it this way: “Thirty days after the plan of action, the field is off track.”

‍Not because they aren’t following instructions, but because the reality on the ground has changed — and no one adjusted.

The Case for Dynamic Segmentation & Targeting

When we talk about the need for AI and real-time data in pharma, this is what we mean. It’s not about adding another layer of dashboards or handing reps more information. It’s about giving leaders the ability to sense and respond faster, so you can keep your teams aligned when it counts. That’s the real value of dynamic targeting.

Dynamic targeting means building models that run continuously in the background and take in new information as it arrives. It identifies relevant signals and reprioritizes engagement accordingly. 

Instead of ranking HCPs once or twice a year, you’re adjusting weekly. Instead of chasing volume, you’re spotting relevance.

You can respond in days rather than months when there’s a change in prescribing behavior, a spike in digital engagement, or a shift in local market activity. You can bring new HCPs into focus before a competitor does. You can align sales and marketing in real time, not just at the start of each cycle.

And you can finally answer the questions that static models never could: Why this doctor? And why now?

To get there, you have to go beyond traditional data sources. Structured data like claims and prescribing history still matters, but it’s no longer enough. You also need to account for unstructured behavioral signals like diagnostic activity, brand engagement, benefit verification checks, or attendance at an event, and layer them together at the territory level.

We’ve seen this work in practice. When dynamic targeting is implemented well, reps don’t just get new lists, they get new confidence. They get a new list and the reasoning behind it. They get the signal. But more importantly, they get the why. And that trust changes behavior.

In one case, a rep was preparing for a call with a physician who had been previously tiered as low-value. Our system flagged new diagnostic activity for a different indication, revealing that the doctor was now seeing patients for another approved use of the brand. The rep changed their approach. Dynamic targeting opened up a new opportunity that the old model would’ve missed entirely.

The targeting model is the foundation. If it’s outdated, every layer above it — sales, marketing, omnichannel — starts to drift off-track.

Leading Effective Change

From a leadership perspective, this is exactly the kind of alignment we’re all trying to create. Marketing activity generates interest. Sales reps follow up. Omnichannel efforts reinforce the message. But none of that coordination works if we don’t agree on who matters, and when.

Engagement becomes inconsistent. Field effort doesn’t match marketing intent. One customer told us their company contacted the same HCP 80 times in one month. That kind of overlap doesn’t just waste budget, it frustrates reps and erodes their trust in headquarters and with HCPs.

Compare that to how other industries operate. In retail, a customer browsing a website triggers coordinated engagement: an email, a push notification, maybe a discount. Each follow-up is timely, contextual, and relevant. It doesn’t happen by accident. It’s powered by systems that detect signals and adjust targeting on the fly.

We should expect the same sophistication in pharma. Our customers — HCPs — are just as digital, just as time-constrained, and just as sensitive to overcommunication. But unlike retail, we’re not just selling shoes. We’re helping doctors make life-altering treatment decisions. Timing and relevance matter more.

Especially in rare disease and specialty categories, where patient populations are small and competitive pressure is high, missing the moment to engage can mean missing the patient altogether. You may not get another chance. That’s why dynamic targeting isn’t just a field enablement strategy but a commercial imperative.

It’s also a leadership issue. Change doesn’t happen just because you buy a new platform. It happens because executives push for new ways of working. They challenge legacy processes. They insist on faster feedback loops, better data hygiene, and tighter integration between strategy and execution.

I’ve seen what happens when that leadership is missing. Targeting stays frozen. The field tunes out. Marketing gets frustrated. And by the time anyone notices, the quarter is over and the next list-building cycle begins.

But I’ve also seen what happens when leadership steps in, when teams move from planning to piloting to full-scale implementation, when reps help shape the build, and when insights actually inform action. The entire model starts to feel different. It’s faster, smarter, and more connected.

Next Steps & Resources

We’re at a moment in the industry where leadership agility is going to separate the winners from the rest. It’s no longer about who has the most data. It’s about who can act on the right data at the right time.

Dynamic targeting gives you that ability. But only if you’re willing to break from the old model and build something new. And the time to do it is now. For a deeper dive, read The Essential Guide to Dynamic Segmentation & Targeting.

Ready to upgrade your targeting approach? Start with an Opportunity Analysis to see the difference dynamic targeting can make.