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Medical Science Liaison

Map and tier KOLs in therapeutic area

Enhances✓ Available Now

What You Do Today

Identify rising stars, established thought leaders, and institutional champions in your geography — build tiered engagement plan

AI That Applies

AI maps KOL influence networks from publication co-authorships, conference panels, guideline committees, and clinical trial leadership

Technologies

Veeva LinkH1 PlatformIQVIA KOL Management

How It Works

The system ingests publication co-authorships as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.

What Changes

KOL mapping is dynamic and network-based instead of static lists; AI identifies rising influencers before they're on everyone's radar

What Stays

You validate the AI's mapping with your field knowledge — personal relationships reveal influence that publication metrics miss

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for map and tier kols in therapeutic area, understand your current state.

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Map your current process: Document how map and tier kols in therapeutic area works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
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Identify the judgment points: You validate the AI's mapping with your field knowledge — personal relationships reveal influence that publication metrics miss. These are the boundaries AI won't cross.
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Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Veeva Link tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long map and tier kols in therapeutic area takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your VP Operations or COO

“What data do we already have that could improve how we handle map and tier kols in therapeutic area?”

They're prioritizing which operational processes to automate

your process improvement or lean lead

“Who on our team has the deepest experience with map and tier kols in therapeutic area, and what tools are they already using?”

They understand the workflow dependencies that AI tools need to respect

a frontline supervisor

“If we brought in AI tools for map and tier kols in therapeutic area, what would we measure before and after to know it actually helped?”

They see the daily reality that AI tools need to fit into

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.

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