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Launch

What the data platform delivers, and when. Then everything it has to produce.

A launch data platform is judged on two things: whether it exists early enough to be trusted, and whether it can carry the 24 recurring reports a commercial team runs on. Below is the calendar, then the inventory.

Why the window is fixed

The first 6 to 12 months set the trajectory the brand rides for the rest of its life.

A solid early ramp puts a medicine on track to hit its numbers. A weak launch costs revenue nobody recovers. And you get one chance at the field's trust: one wrong territory number and the reps run on gut, after which the platform you paid for is furniture.

The calendar

Build. Run. Transfer.

Three phases, clear roles, nothing a black box. We hold the engineering lane, your analysts hold the business lane, and the platform transfers when you say.

Build

Month −18 to month −1

We build the commercial data platform your launch needs. Star schemas your analysts can query, the AI-ready context layer beside them, tests on every table, and observability across every pipeline. Field reporting goes live six months before launch day, so the field learns to trust the numbers before anything is at stake.

Delivers: A production platform six months before launch day.

Run

Launch day through year one

We are in your standup. We ship new datasets in days. We fix what breaks before the field sees it. Your analysts spend their week on analysis rather than reconciling the IQVIA refresh against claims, and your AI tools answer real questions because the data underneath them is real.

Delivers: Launch hit. Analyst queue under a week. Errors caught upstream of the field.

Transfer

Whenever you say

You own it from day one, so the handover is a normal day rather than an event. We transfer to whoever you name: your team, Accenture, or your offshore centre. Eisai moved one of our platforms to Accenture cleanly, because every line of code and every test already lived in their environment.

Delivers: A working platform in your hands, your team trained, our people gone.

Milestones

You are not waiting two quarters for a design document.

  1. Week 4

    First star schema

    A fast-start star in a data mart on your highest-priority feed, with tests on it from the first build. Analysts start giving feedback while it is still cheap to change.

  2. Week 6

    First AI context layer

    Schema and grain written down, business definitions for equalized prescriptions and payer hierarchy, and validated example queries, so your AI tool answers instead of guessing.

  3. Month −6

    Field reporting live

    The full launch report set in production and in front of the field six months before go-live, which is the only way the numbers are trusted on day one.

  4. Launch day

    The first year begins

    The first 6 to 12 months set the drug's lifetime revenue trajectory. A weak launch costs revenue that is never recovered, and you get one chance at the field's trust.

  5. Ongoing

    New datasets in days

    A new business question that needs a large new dataset gets a fast-start star, questions back to the supplier, tests, and analyst feedback across a few sprints rather than a quarter.

On the record

What these teams actually looked like.

1.5

engineers, two years

The entire Cobenfy launch data infrastructure at Karuna, covering 50 integrated datasets. Most pharma companies staff that work with 10 engineers.

7

engineers, $10B in sales

At Celgene, seven of our engineers supported US sales across every brand, with 10 to 12 analysts covering hundreds of datasets without missed SLAs.

18%

of time on data loading

The rest of that Celgene engineering time went to new analyst work rather than plumbing, which is the whole point of automating the loads.

The inventory

The 24 reports a launch analytics team is on the hook for.

A data team of one or two dozen people serves hundreds of sales and marketing users, and each of them has a territory or a campaign. This is what the requests resolve into. Every row needs data from the feeds on the data sources page.

Performance and forecast

The numbers leadership sees first, and the ones a silent vendor restatement quietly rewrites underneath you.

Report What it is Cadence Who reads it Key metrics
Forecast tracking National brand performance against the current forecast, built on national prescription audit and forecast metrics. Weekly Senior management, brand team TRx, NRx, units
Forecast creation Developing the forecast itself from analogs, historical trends, population facts, and projected events. Quarterly Senior management, brand team, finance TRx, NRx, units
Launch tracking The executive summary that pulls the key point out of every more detailed report below. Weekly Senior management, brand team, home office TRx, NRx, cohorts, geographic differences, deciles, specialties, targets, activity vs plan, payer performance, top prescribers
Claims reporting Claim counts per product over time, from syndicated claims data. Weekly Senior management, brand team, field Claim volume and mix

Brand, promotion, and ROI

Where sub-national detail matters and where attribution windows shift the answer when a channel feed lands late.

Report What it is Cadence Who reads it Key metrics
Brand team report Critical sub-national topics in depth, joining sub-national volume, prescriber reference, alignment, targeting, promotional and field activity. Monthly Brand team TRx, NRx, cohorts, deciles, specialties, targets, payer performance, promotional execution and results
Brand planning support Standing up the analysis behind annual brand planning, including drivers analysis. A few months, annually Senior management, brand team Multiple
Promotional mix and ROI Lift analysis and return calculation across the major promotional efforts. Monthly Brand team TRx, NRx, units, financial return
Direct-to-consumer DTC geographic coverage and the lift analysis on top of it, keyed to current alignment. Monthly Brand team TRx, NRx, units
Non-personal promotion Lift and ROI across digital channels, joining promotional data to sub-national volume and field activity. Weekly Brand team Clicks, views, reads, lift

Field execution and incentive comp

The reports reps and sales operations live in, and the ones where a territory realignment or a duplicated prescriber costs real money.

Report What it is Cadence Who reads it Key metrics
Field activity Rep activity against planned activity, joining prescriber reference, alignment, targeting and activity data. Weekly Field Calls, samples
Field performance Brand performance by geographic alignment, which is the report a realignment breaks while every underlying value stays valid. Weekly Field TRx, NRx, calls, samples
Pre-call planning Physician-level views that integrate several datasets into one page a rep reads before a call. Weekly Field Multiple metrics by physician
Incentive compensation Ranking each rep on performance and business logic. A duplicated prescriber splits credit here and the comp run pays the wrong people. Weekly Field, sales operations IC metrics, rank
Plan of action and sales meetings The analysis behind national sales meeting presentations, sessions, and materials. At meetings Field Field activity and performance
Target list development Identifying the most promising existing and potential prescribers from prescriber reference, alignment, and sub-national data. Periodically Sales operations Scores by physician, zip-to-territory
Sales force logistics The periodic data work that keeps the field functioning between the headline reports. Periodically Sales operations Multiple

Access, payer, and patient

Where a specialty brand actually lives, and where a half-loaded dispense feed hides real patients during the weeks that matter most.

Report What it is Cadence Who reads it Key metrics
Payer and plan Performance across major model groups, minor model groups, and individual payers, which usually needs a bridge file to join. Monthly Brand team TRx, NRx, units, formulary status impact
Stocking Which pharmacies carry the brand, from syndicated stocking data. Weekly Brand team Pharmacies stocked
Specialty pharmacy Stocking and sales across the specialty network, stitched from a dozen or more pharmacy feeds that disagree on what a date means. Periodically Senior management, brand team Dispense, referrals, time to fill
Source of business, patient level Adherence, refills, and switching from longitudinal patient and source-of-business data. Monthly Senior management, brand team Adherence, persistence, discontinuation

Finance and compliance

The reports that have to tie out, where "roughly right" is not an available answer.

Report What it is Cadence Who reads it Key metrics
Finance reporting Accrued financial metrics from finance data. Monthly Senior management, brand team, finance Multiple financial metrics
Demand-based P&L TRx, SKU, pricing, and contracting data combined into a demand view of profitability. Monthly Senior management, brand team, finance Multiple financial metrics
REMS Use within the certified components of the delivery chain, from REMS-specific datasets. Daily, weekly, or monthly by program Brand team REMS programme metrics

The queue nobody schedules

The work that decides whether your analytics team is trusted, and the first thing to collapse when the engineering layer underneath is weak.

Report What it is Cadence Who reads it Key metrics
Analytic questions Answering questions about the launch and sub-national market dynamics quickly enough to still matter, across whatever data the question touches. On tap Extended sales and brand team Multiple

Questions

About the launch calendar.

How far before launch should we start?

For a launch, 12 to 24 months out is cheapest and calmest: the first 6 to 12 months set the drug's lifetime revenue trajectory and you get one chance at the field's trust. If a product is already selling, timing works differently. We take the existing operation over feed by feed, so there is no window you can miss.

How soon do we see something working?

First star schema in four weeks. First AI context layer in six. Full launch report set six months before go-live. Field reporting has been live six months ahead of launch day on every engagement we have run. You are not waiting two quarters for a design document.

How does an engagement actually run?

Three phases. Build runs from roughly 18 months out to launch minus one, and ends with a production platform six months before launch day. Run covers launch day through year one, shipping new datasets in days and fixing breakage before the field sees it. Transfer happens whenever you say, to whoever you name.

How do you keep us in the loop?

Daily scrum and ticket triage, all tracked in Jira. A weekly status meeting with your analytics lead covering work completed, in progress, and planned. A quarterly business review with leadership covering timelines and metrics on bugs, tests, and datasets. Documentation lives in a shared wiki. Time is tracked and reported.

What happens if our launch slips?

The rate scales down with you on 30 days' notice, with no penalty for an FDA delay you did not choose. That matters when roughly 3,500 staff left the FDA after the 2025 cuts and biotechs are missing meetings and pushing trials. A fixed multi-year commitment is the wrong shape for a date you do not control.

What does the handover look like?

A normal day rather than an event. We transfer to whoever you name: your team, Accenture, or your offshore center. No lock-in, no exit fees. Eisai transferred one of our platforms to Accenture cleanly when they were ready. Because every line of code and every test already lived in their environment, there was nothing to extract.
All questions

When is your launch?

Thirty minutes. Bring the date, the team, and the data sources, and we will tell you what the first four weeks would produce and whether we are a fit at all.