In pharmaceutical organisations, data availability is rarely the problem. We are drowning in it.

​

The real challenge is timing—understanding when change is happening, not just that it has already happened.

​

Many of the most difficult leadership moments occur not because decisions were wrong, but because the understanding came too late. By the time a trend hits the commercial dashboard, the behaviour is often already cemented.

​

We miss these early signals because we often confuse two very different things: Prescribing Patterns and Prescribing Behaviour.

​

1. Prescribing Patterns (The "What")

NHS prescribing data is widely used but often interpreted at surface level. A prescribing pattern is the observable shape in the data:

 

• Volumes rising or falling

• Flat or plateaued usage

• Short-term fluctuations

• Regional variation

​

Patterns are factual. They answer the question: "What is happening right now?" But on their own, they are noisy, reactive, and easy to misread.

​

2. Prescribing Behaviour (The "How")

Prescribing behaviour is the interpretation of those patterns over time. To see change coming, you have to look beyond the single data point and analyze four stable dimensions:

 

• Direction: Is prescribing moving up, down, or flat?

• Persistency: Does that direction continue over time?

• Consistency: Does the pattern move coherently or frequently reverse?

• Volatility: How noisy or stable is the movement?

​

When these dimensions are considered together, prescribing patterns translate into behavioural states.

​

Why Change is Invisible to Commercial Data​

In healthcare systems, change rarely appears suddenly. What typically happens is:

 

1. Prescribing behaviour begins to shift at the molecule or pathway level.

2. That shift persists and stabilises quietly.

3. Commercial, operational, or access impact becomes visible months later.

​

This time lag is not a failure of execution. it is a structural reality of healthcare systems.

​

If you rely solely on commercial data, you are waiting for the outcome. NHS data, when viewed through a behavioural lens, shows you the change in real-time.

​

Where Merlinn Fits In

This is the specific gap Merlinn was designed to close. Merlinn processes NHS data to reveal these behavioural insights alongside existing commercial views.

​

Merlinn focuses on:

• Molecule-level shifts

• Therapy-class evolution

• Pathway and access behaviour

• System-wide prescribing change

​

The Goal: Eliminating Surprise By understanding prescribing behaviour, organisations can reduce overreaction to short-term noise. It also helps avoid the late recognition of slow, structural change.

Behavioural insight does not remove uncertainty but it does remove surprise.

​

A Leadership Perspective

Merlinn functions as a leadership awareness layer. It enables Commercial, Medical, and Market Access teams to align around a shared understanding of how the treatment system is evolving before those changes are reflected in brand-level outcomes.

​

The Bottom Line In complex healthcare systems, the challenge is rarely reacting faster. It is recognising what is changing early enough to have a meaningful choice.

​

Organisations that understand behaviour earlier are not predicting the future. They are simply less surprised by it.