Field reporting was supposed to go live six months before launch day. That is the milestone in DataKitchen’s launch timeline, and it exists so reps can find the bad numbers while a bad number is still cheap. You are at three months. Half that window is gone.
So stop planning the whole platform. Plan launch week.
A year out, the 12-month launch checklist orders the work as feeds, systems, stars, then reports. At T-3, run it backward. Start from the reports someone opens on launch Monday, and build only what they read.
Sort the 24 reports by who opens them in week one
The launch page lists 24 reports a commercial launch analytics team owns, with cadence and audience for each. Cadence is the sorting key. A weekly report read by the field is a launch-day dependency. A monthly ROI report is not.
| Priority | Reports (cadence from the launch inventory) | Why |
|---|---|---|
| Launch week, must be right | Launch tracking, forecast tracking, field activity, field performance, incentive compensation (all weekly) | Leadership and every rep read these first, and comp pays out on them |
| Launch week, can be rough | Pre-call planning, claims reporting, stocking (weekly); target list development, plan of action and sales meetings, sales force logistics (periodic) | Reps need them before the first call; a scrappy version will do |
| Launch week if it applies | Specialty pharmacy dispense and status; REMS reporting | A specialty or limited-distribution brand lives here; a REMS program sets its own cadence |
| After launch | Brand team report, promotional mix and ROI, DTC, non-personal promotion lift, payer and plan, source of business | Monthly, except non-personal promotion (weekly); lift and adherence need post-launch history to measure |
| After launch | Brand planning support (annual), forecast creation (quarterly), demand-based P&L, finance reporting (monthly) | Slow cadence; schedule them, don’t build them now |
The cadences come from the launch inventory. The launch-week and after-launch split is DataKitchen’s recommendation, not a record of a specific launch. Move finance reporting up if your finance team closes on it in launch month.
The drug launch case study is a useful check on the top row. When that team’s field reporting went live six months early, the reports it names as ready are claims, Rx, payer plan, incentive compensation, and marketing automation. Field and money, before planning.
Test the feeds behind the top row, and only those, first
A report is ready when its inputs pass, not when it renders. Every feed behind a launch-week report gets the two reconciliation checks: extract to load against the vendor’s control record, and a diff of overlapping periods against the delivery you kept. The post on the commercial data most likely to be wrong walks through both, and the feed-by-feed test list adds the check each feed type needs.
Incentive compensation needs more than that before its first run. A duplicated prescriber splits credit, and a realignment moves a rep’s numbers with every value valid. Run the relationship tests in testing territory alignment and incentive comp data before the first payout, not after the first dispute.
If you’re a specialty brand, the specialty pharmacy feeds are the ones the access team watches, and their integration is almost always somebody’s afterthought. Settle the event date and the calendar first, as in why specialty pharmacy, 867, and sales numbers don’t match. Reconcile later.
Ship rough, on tested data
Celgene’s Otezla team built a scrappy star first and shipped production dashboards at 70 percent done, then hardened them over later sprints. That’s the trade you are making now, and it’s a good one if you make it on purpose. A dashboard with an ugly layout is recoverable. A territory number that’s wrong in launch week isn’t, because the first 6 to 12 months set a drug’s lifetime revenue trajectory and you get one chance at the field’s trust.
Things to cut without guilt: the AI context layer, the second visualization pass, and every report in the bottom two rows of the table.
Don’t staff your way out
The instinct at T-3 is to add ten people. The case study points the other way. One engineer carried the pre-launch work for 1¾ years, and a second joined nine months out. It also notes that communication channels grow as (N² minus N)/2 with team size. Two people share one channel. Twelve share 66.
Add one or two people who already know IQVIA, specialty pharmacy, and Veeva feeds, then protect them from every report whose first reader is a quarterly business review.