Pharmaceutical forecasting

Pharmaceutical forecasting software with accuracy you can see

The statistical forecast, the commercial plan and the tender usually live in three files that someone merges by hand. PLAIO puts them in one forecast, scores it against actual sales, and supply plans on the result.

See a few of your SKUs forecast in PLAIO

30 minutes with PLAIO. Bring a few SKUs and the forecast file you work from today.

Goes straight to our team. Never shared or sold.

Demand lines for Amoxicillin Suspension 100ml, hospital channel, Iberia: Client Forecast, an 8% scale, a Q4 Tender, and the ML Forecast next to a moving average
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Azurity
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Navamedic
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Adalvo
Frostpharma
CNX Therapeutics
Arcera
Sun Wave Pharma

Your forecast is three files and a merge

In most pharma planning teams the statistical forecast sits in one file and the commercial plan in another. The tender arrives by email. Someone combines them by hand every cycle.

When that merge goes wrong, you find out later, as a stockout or a write-off.

One portfolio number also hides a lot. A bias of −0.7% looks like a team doing its job. Cut by channel, it can be +2.9% on hospital and −1.7% on tender: errors cancelling out, and none of them gets fixed.

Then S&OP asks what changed since last month, and why. The answer is in someone’s sent folder, if it was written down at all.

Why it matters:

A cleverer model on its own won’t solve this. Every input needs to land in one place where it is combined, saved as a version and checked against what sold. Supply should plan on that number and nothing else.

Forecast accuracy at a three-month lag: overall bias of −0.7%, and by channel Hospital at +2.9% bias while Tender and Retail Pharmacy sit at −1.7%

What your forecast gets in PLAIO

Demand Builder for Amoxicillin Suspension 100ml in the hospital channel: Client Forecast base, Cutback 8% scale, and a Q4 Tender overlay from Nov 2026 to Feb 2027 switched on

Tenders and launches as overlays

A tender gets its own line on top of the base, for the months it covers. Lose it and you switch the line off. The baseline was never touched.

Exceptions for Cough Syrup 200ml in Iberia: four months flagged as Prev. Cycle Deviation, from −24% in November 2026 to −28% in January and March 2027

See what moved before the review

PLAIO compares the live plan with the last saved one. Anything past your threshold (20% unless you change it) is flagged, so the review starts on those rows.

Forecast accuracy grouped by therapy area: Anti-Infectives 91.5%, Respiratory 93.0% at −4.4% bias, Cardiovascular 93.9%, Dermatology 94.5% at +4.4% bias

Accuracy per segment

Accuracy, error and bias are reported by the dimensions your plan uses, such as channel or therapy area. A good portfolio number can’t hide a weak segment.

How pharmaceutical forecasting works in PLAIO

Two steps in PLAIO: choosing the base for one product from ML Forecast, Moving Average, Open Orders, Client Forecast or Commercial Plan, then reading forecast accuracy at a chosen lag from 1 to 12 months

A forecast trained on your own sales

The machine learning forecast learns from your monthly sales, item by item and location by location. It picks up seasonality and trend and starts from an item’s first month of sales. A moving average runs beside it, so you can compare the two.

Pick the base, then adjust it

For each part of the horizon you choose the base: the ML forecast, a moving average, open orders or the commercial plan your team uploads. Scale it up or down and add overlays. Set it once for the whole plan, or per item and location.

Save versions and measure at your lag

Save a forecast with a label and a note before S&OP. PLAIO also snapshots the plan every month, and scores accuracy, error and bias against actual sales at any lag from 1 to 12 months.

Supply plans on the same number

Supply planning reads the forecast directly. When a launch slips you edit one line, and the supply plan picks it up without anyone re-cutting a spreadsheet.

See my SKUs forecast

Pharmaceutical forecasting FAQ

No. It is one demand line among several. It only reaches the plan where you make it the base, for the whole plan or per item and location, and planners keep the final say. Where another source does better, use that one.

One month to start. The model forecasts an item and location from its first month of sales and learns more as history builds up. It looks back to the same month last year for seasonality, so two years of monthly sales gives it the most to work with. Until then you can keep a moving average or your own plan as the base.

Our customers run SAP (ECC and S/4HANA), NetSuite and Microsoft Dynamics 365 Business Central. PLAIO also works with Oracle. We build the connection for you. You don’t have to wait for it: start on the spreadsheet exports you already have, map their columns once, and each upload is checked before the plan changes.

Most teams are planning in PLAIO within weeks. Starting on exports means the first forecast doesn’t depend on the integration. When the connection is ready, each dataset moves to the live feed and the plan carries on.

Yes. Saved forecasts keep their date, author, label and notes, and PLAIO takes its own snapshot of the plan every month. For each product and location, the change history lists who edited which demand line and month, with the old and new values. Your ERP stays as it was validated. PLAIO plans, and approved orders go back to the ERP.

We build a forecast from a market baseline, a tender and a commercial plan, look at what moved since the last cycle, and show what supply planning does with it. Bring a few SKUs if you want to see your own. Book a time.

SAP, Oracle, NetSuite and Microsoft Dynamics 365 Business Central are trademarks or registered trademarks of their respective owners. PLAIO is not affiliated with or endorsed by them.

Bring a few SKUs. See them forecast in PLAIO

30 minutes on your own products: the base forecast, the tenders on top, and the accuracy you would report.

Book my 30-minute demo Prefer to read first? 3-step framework for stable pharma forecasting

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