Pull the same data two different ways and you get two different answers. There's no shared list of data or business rules to settle which one is right. Five naming systems run side by side and don't mean the same thing.
Data Foundation Governed ThresholdsDashboards and data access are built per brand. There's no way to see across brands, which is exactly what portfolio decisions need.
Data Foundation Governed ThresholdsA brand can push through a change without knowing the cost to other brands or to comp and IC. What looks fine for one brand can cost three others their reps.
Scenario Simulation Governed ThresholdsThere's no tiered process for change. Every change gets the same manual negotiation, with no agreed threshold for what needs approval.
Versioned Record Governed ThresholdsWork is saved all over the place with no structure, and time gets wasted searching for documentation and answers. When a framework changed last quarter, only 55% of the target list was retained (47% for PCP), and nothing recorded what changed or why.
Versioned Record Data FoundationA data feed can arrive once a month as a manual file, already several days old, with no fixed schedule to plan around. For example: PA data.
Data Foundation Governed ThresholdsWhen the market definition changes, nobody can tell if a different result is an expected change or a mistake.
Versioned Record Data Foundation Scenario SimulationPatient data is incomplete by design. Field reps fill the gaps with knowledge that never gets written down.
Knowledge Captured Data Foundation Governed ThresholdsHCP records don't track changes over time. It's unclear if a doctor has more than one main affiliation, which changes how territories get rolled up.
Versioned RecordReps call on doctors well beyond their assigned list. About a quarter of all calls fall outside the formal target list, and none of that feeds back into the system.
Knowledge CapturedA framework change can shake up the target list, and nobody records what changed or why.
Versioned RecordBrands run their own segmentation and map it into the shared framework, but the field force design team can't see what's actually happening underneath.
Versioned RecordMarket access data shows up in only one system and nowhere else. A new access flag is in progress, but only for one brand so far.
Access-WeightedReps call more on doctors with worse insurance coverage than on the ones with the best. Pay structures make this worse, not better.
Access-WeightedRADs win formulary access, but there's no set way for that win to reach the reps who could act on it.
Access-WeightedMarket access, RADs, MSLs, reimbursement, nurse educators, and contracting all sit outside today's sizing methods, which are based only on call activity.
Real Sizing MethodA ZIP belongs to one territory per brand, but that's never written down. Valuation weights differ by brand, and some brands skip the calculation entirely. Resizing cycles range from yearly to once every few years, with no shared standard for any of it.
Data FoundationAbout half of escalated prior authorizations never get resolved. An unsubmitted authorization behind a written script is the single biggest missed opportunity.
Access-WeightedArea leaders propose new field roles. They own the P&L but aren't sizing experts. A role can get approved with almost no data behind it, and the sizing team finds out after the fact.
Knowledge CapturedThere's no way to see how much value comes from one more call, and no cost view at the territory level.
Real Sizing MethodStaffing follows prior-authorization volume, not a real sizing method, and the work is fully outsourced. Since the role is non-promotional, it can't be tied to prescription volume either, so there's no lever to manage it by.
Real Sizing MethodTwo people manually review every territory using local, institutional knowledge that doesn't get recorded or tracked.
Knowledge CapturedTerritory value is built from doctor-level data alone. It ignores hospital systems, so two similar-looking territories can have very different value, and nobody sees that until it's too late. Worst in oncology and cardiovascular.
Data Foundation Governed Thresholds Knowledge CapturedDefinitions, methods, and history are saved with version tracking. A rerun after a change reads as an update, not a defect. A brand's own approach stays visible to the whole team, and anything can be looked up on demand instead of searched for.
The knowledge that today only lives in people's heads gets written down and made searchable, instead of disappearing.
Payer access and reimbursement data feed directly into targeting, reaching every brand and every part of the workflow. Access wins get a clear path into field action.
Every role, sales and non-sales, gets sized with a real method. Response curves and workload logic replace guesswork.
Every proposed change runs as a simulation first, showing impact and disruption across brands before anything gets executed.
One shared set of definitions replaces five naming systems and brand-by-brand rules. One valuation method, one refresh schedule, and cross-brand data access replace answers that used to differ by brand. Every input, including feeds like PA data, arrives on a defined, automated schedule instead of a manual file with no set cadence. MDM and HCP affiliation are mastered upstream.
Changes get checked against clear thresholds. Routine changes pass automatically. Critical or flagged changes go to a named approver, and named owners are responsible for committing each recommendation to execution.