Engagement OS
Plan, log and measure every scientific interaction in one place.
Shortlist it, send it over — we come back with the shape we'd actually recommend.
What engagement os actually is.
A workflow layer for medical, MSL and access teams to plan engagements, log interactions, and roll up coverage and sentiment across the stakeholder map, without dragging the team back into the CRM ritual.
The operating surface for scientific exchange. Not a contact-management tool; the place the team plans the engagement and reads whether it landed.
- Engagement plan per stakeholder with cadence and owner
- Structured interaction log with sentiment and themes
- Coverage and gap-to-target by segment and market
- Quality measurement alongside volume
- Live wiring into the Stakeholder Graph and Field Insights Engine
Add the pieces you'd want and we'll build a shortlist you can review, reorder and send over. No pricing wall, no commitment — we come back with what we'd actually recommend, including anything you don't need.
Approach, modules, delivery.
Move through the tabs to see how the work runs, what it's made of and what lands at the end.
Inputs
- Engagement plan, KOL 1:1s, advisory boards, congress satellites, investigator webinars, MSL field visits, standing payer-clinical committees
- Objective, format and owning function (Medical · MSL · Clinical · HEOR · Access) for every interaction
- Interaction log, attendees, materials version, consent state, MLR clearance, notes
- Insights captured per interaction with theme (Evidence · Operational · Strategy · Compliance) and a downstream route
- Coverage cohorts (Tier-A KOLs, EU5 investigators, US community oncologists, payer clinical leads, advocacy chairs) with cadence and meaningful-engagement definition
Method
Engagement OS is the single place where every scientific interaction is planned, logged and measured. Plans are built per cohort with cadence and objective; interactions are logged at the moment they happen with attendees, materials and consent state; insights are captured against a theme and routed to the surface that consumes them; coverage is measured as meaningful-engagement, not as activity. Scenarios over cadence, format, reallocation and compliance can be tested before they are shipped. The OS writes back into Stakeholder Graph, Narrative Workbench, Evidence Gap Console and the Reimbursement Strategy Console, and the compliance log is the source of truth, the engagement plan and the insight engine both read from it.
Assumptions
- MLR pre-clearance and disclosure obligations are part of the workflow, not a separate spreadsheet.
- Meaningful-engagement is defined per cohort and agreed with the medical leadership team; coverage is measured against that definition.
- Insights are captured at the interaction, not reconstructed from memory a week later.
Limitations
- Some insight tagging is human-judgement; the OS captures provenance but does not replace medical interpretation.
- Cross-team adoption requires standing operating rhythm; the OS surfaces drift but cannot enforce discipline.
Think this belongs in your scope?
Add it alongside anything else that fits, then send the shortlist over. We'll reply with the shape we'd recommend — sequence included, and the parts we think you can skip.
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