Industries · Pharma & Healthcare · Powered by Planamind

Demand & Supply Chain Planning for Pharma

Plan thousands of SKUs across a distributed network while managing expiry, tenders, product transitions and ingredient supply. Planamind brings demand, supply and materials into one plan for pharma manufacturers and distributors.

The challenges

What makes pharma & healthcare planning hard.

Pharma supply chains combine long lead times, strict shelf lives and volatile demand from tenders and new launches.

01

Large SKU portfolios

Thousands of products, each with its own demand pattern.

02

Product expiry

Batches expire in the channel while other markets run short.

03

Product transitions

Launches, generics and substitutions shift demand between products.

04

Tender volatility

Wins and losses change demand overnight.

05

Distributed networks

Stock sits in the wrong depot or country.

06

API and material shortages

Ingredient supply problems stop production.

How Planamind helps

Built for how pharma & healthcare businesses plan.

Demand, supply, materials and finance in one workspace, with Ana on every screen.

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Batch & expiry

Expiry risk managed before it becomes a write-off

Stock on hand is tracked by batch and expiry and used earliest-expiry-first in the daily simulation. Shelf life caps order sizes, and batches expiring within 90 days are highlighted.

AI · Stock healthAna's Stock Health analysis prioritises the actions that protect availability and release working capital.
TrackingBatch · expiry
ConsumptionEarliest expiry first
Near-expiry window90 days
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Product transitions

Launches and substitutions without guesswork

Map the history of a predecessor product to its successor with a configurable share and overlap, so product transitions and new presentations start with a grounded forecast.

AI · Accuracy diagnosticsWhen a forecast misses, Ana explains why in plain English, and the analysis points to a better-suited model.
History fromPredecessor product
Share & overlapConfigurable
Models12, selected automatically
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Tenders & opportunities

Tenders in the plan before they land

Add tenders and new business as pipeline opportunities, weighted by win probability, and phase them as a one-off or a ramp. Supply and finance plan for them automatically.

Flows downstreamView the plan as weighted, best case or committed, and see the effect on stock and gross profit.
Pipeline stagesLead → Won
ViewsWeighted · Best case · Committed
PhasingOne-off or ramp
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Network & materials

The right stock in the right market, with ingredients to match

Transfers move stock from locations with excess to those running short, with proportional, fair-share or priority allocation when supply is tight. Multi-level BOMs plan ingredients and packaging from planned production.

AI · Ask AnaAsk Ana which products are heading for a stockout, or which ingredients limit supply, and she answers from the live plan.
TransfersWithin location groups
AllocationProportional · Fair share · Priority
BOM levelsUnlimited
Ana in action

The right intervention, at the right moment.

Planamind flags what needs a decision, and Ana explains the numbers behind it.

Near expiry

Excess cover in one market

A product carries excess cover with batches expiring within 90 days, while another depot is running short. A transfer is planned before a new order.

Budget gap

Revenue behind AOP

The revenue bridge shows the gap is mostly volume, and Ana lists the forecast and channel actions for review.

Illustrative examples

What planning teams gain
5–20%Forecast accuracy improvement
10–20%Inventory reduction
50–80%Order-loss prevention
5–20%Working capital freed
Client stories

Pharma & Healthcare planning with Anamind.

“We saw it as a fantastic collaborative planning tool that could not only forecast but also drive consensus from top to bottom cut across functions.”

Johnson & Johnson · Planning as a Service
Case study · Pharma

Pharmaceutical company optimises demand planning

Better efficiency, accuracy and inventory management, leading to cost savings and improved performance.

Read the case study →
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