I Struggle With Waiting Rooms: The Three-Hour, Two-Minute Reality

Three hours waiting. Two minutes talking.

That’s the reality of detailing high-volume physicians. The ratio feels absurd. Yet reps do it repeatedly because “that’s where the volume is.”

I struggle with this. Not because the maths is wrong -it’s often right. Because the maths is incomplete.

The volume trap

Traditional call planning prioritises high-prescribing physicians. More scripts = more potential = more calls.

The logic is clean. The reality is messier.

High-volume physicians are busy. Their waiting rooms are packed. Access is limited. Every pharma company in the market is competing for those two minutes.

The three-hour investment produces two minutes of attention shared with ten other companies trying to say the same thing.

Volume-based targeting often leads to volume-based crowding.

What Manchanda’s research revealed

Puneet Manchanda’s studies on pharmaceutical detailing uncovered something important: the relationship between detailing and prescribing isn’t linear.

Some physicians are highly responsive to detailing. A few calls produce significant prescribing changes.

Some physicians are barely responsive. Many calls produce minimal prescribing changes.

The difference isn’t about volume. It’s about elasticity. How much does prescribing behaviour shift in response to sales pressure?

A medium-volume physician with high elasticity might be more valuable than a high-volume physician with low elasticity. The medium-volume physician will actually change behaviour. The high-volume physician won’t, regardless of how long you wait.

Responsiveness-based segmentation

Instead of asking “who prescribes the most?”, ask “who changes prescribing based on our activity?”

This reframes the call plan.

High responders (regardless of current volume): Increase frequency. They respond to presence. Give them more presence.

Low responders (regardless of current volume): Decrease frequency or change approach. More of the same won’t work. Either find a different way in or reallocate the time.

Moderate responders: Maintain current frequency. They’re responsive enough to justify attention but not responsive enough to justify intensity.

The waiting room calculus changes. Three hours for two minutes with a high responder might be worth it. Three hours for two minutes with a low responder almost never is.

How to identify responders

Responsiveness can be measured retrospectively and predicted prospectively.

Retrospective: Look at historical detailing data alongside prescribing trends. Did increased calls correlate with increased scripts? For which physicians?

Prospective: Test call frequency variations. Increase calls to a sample group. Measure response. The physicians who change behaviour are your high responders.

Proxy indicators: Certain physician characteristics correlate with responsiveness. Newer physicians often respond more than established ones. Physicians who attend educational events often respond more than those who don’t. These aren’t perfect predictors, but they’re directional.

The uncomfortable truth

Responsiveness-based segmentation means calling less on some high-volume physicians.

This feels wrong. The biggest prescribers are getting less attention? How does that make sense?

It makes sense because attention isn’t the same as impact. A high-volume, low-elasticity physician doesn’t need your calls. They’ve decided what to prescribe. Your waiting room time won’t change that.

Meanwhile, a medium-volume, high-elasticity physician is making decisions you can influence. That influence is worth more than presence that produces nothing.

What I struggle with

I don’t struggle with the logic. I struggle with the implementation.

Telling a rep to reduce calls on their biggest customer contradicts decades of sales training. It requires trust in data that most organisations haven’t built.

And sometimes, the data is wrong. Sometimes, a “low responder” is actually a relationship that hasn’t been built yet. Sometimes, persistence pays off.

The waiting room calculation isn’t simple. But it’s worth questioning.

Every three hours in a waiting room is three hours not spent somewhere else. The opportunity cost is real. The question is whether we’re measuring it.

If we’re not measuring responsiveness, we’re not really managing territories. We’re just scheduling visits and hoping.

Hope isn’t a strategy. Even when it comes with three hours of waiting time.