Demand Planning · Pharma

    Demand planning for pharma, where safety stock expires

    You can't cover uncertainty by holding more — it ages out. Likwid plans cover against the shelf life actually left on the batch, commits long-lead actives with the confidence shown, and forecasts tender demand separately from retail.

    Planning FMCG instead? See demand planning for FMCG.

    app.likwid.co.in/inventory/demand-forecasting
    Demand Forecasting
    3,242
    SKUs
    1,583
    Smooth
    785
    Intermittent
    408
    Erratic
    434
    Lumpy
    ItemPer Day
    Amoxicillin 500mgAntibioticssmooth44
    Surgical Gloves (M)Consumablesintermittent2
    Insulin Glargine PenCold Chainlumpy14
    Paracetamol 650mgAnalgesicssmooth180
    Cotton Roll 500gConsumablessmooth68
    The short answer

    What makes pharma demand planning different?

    In most industries you buy certainty with inventory. In pharma, inventory has a clock on it.

    Over-forecast and the cover you built expires as a write-off. Under-forecast and you're short of a product a patient is waiting on. The two errors pull in opposite directions, which is why a pharma plan has to weigh the confidence of a forecast as heavily as its value — and why expiry, batch size and API lead time belong inside the planning maths rather than beside it.

    Why it breaks

    Four constraints a generic forecast ignores

    None of these are about better maths. They're about what the number is allowed to assume.

    01

    Your safety stock has an expiry date

    Everywhere else, uncertainty is covered by holding more. In pharma, holding more is how you create a write-off — the buffer you built against a stockout quietly ages out on the rack. Forecast error costs you in both directions, and they pull opposite ways.

    02

    You commit to the API before you know the demand

    Imported actives run long lead times, so the purchase decision is taken months ahead of the month it serves. By the time the market tells you it was wrong, the material is already on a vessel — or already in your store.

    03

    Demand arrives in steps, not trends

    Retail demand trends. Institutional and tender demand jumps — a win is a step change that no moving average saw coming, and a loss removes a block of volume the same way. Averaging the two together forecasts neither.

    04

    Shelf life is consumed in your own warehouse

    A product with two years of shelf life that sat eight months with you isn't a two-year product any more. Distributors want remaining life, so stock that looks perfectly good on a stock report can already be hard to place.

    Inside the platform

    From a forecast to an API purchase order

    The same three screens every cycle — demand per SKU with the pattern named, what it nets to once batches and their expiry are counted, and the order that goes to the API vendor.

    ARIA · Forecast
    Signals → SKU-level demand
    3,242 SKUs
    ItemForecastConfPattern
    Amoxicillin 500mg CapsFG-AMX-5008,400 No88%Steady
    Paracetamol IP 650mgFG-PCM-65012,600 No85%Seasonal
    Cough Syrup 100mlFG-CGH-1009,300 No81%Seasonal
    Insulin Glargine PenFG-INS-PEN1,150 No64%Lumpy
    Oncology Vial · 100mgFG-ONC-100260 No51%Intermittent
    How Likwid plans it

    Plan to what can still be sold

    01

    Cover targets that respect remaining life

    Safety stock is planned against the shelf life actually left on the batch, not a flat days-of-cover number — so the buffer is sized to what can still be sold rather than to what fits in the rack.

    02

    Expiry-aware netting, batch by batch

    On-hand supply is counted with its expiry attached. A batch that will age out before the demand it was meant to cover isn't treated as supply, so the plan stops double-counting stock you can't actually ship.

    03

    Lead-time-aware commitment on actives

    Long-lead APIs are planned on their own horizon, with the forecast's confidence shown at the point of commitment — so a low-confidence number is visibly a low-confidence bet rather than a line in a spreadsheet.

    04

    Lumpy and intermittent patterns, handled honestly

    Tender, institutional and specialty items are classified as lumpy or intermittent and routed to methods that suit them, with wide confidence bands where the truth is genuinely uncertain instead of false precision.

    Built on Likwid's demand forecasting engine, feeding S&OP and procurement.

    0+
    SKUs forecast per cycle
    Batch · expiry
    counted as supply with a clock
    Lumpy · intermittent
    tender demand handled separately
    Long-lead
    actives planned on their own horizon

    Illustrative of how the platform is designed to behave — actual figures depend on your catalogue and data.

    Questions

    Pharma demand planning, answered

    Pharma demand planning is forecasting demand per SKU and market, then converting it into a production, inventory and API buying plan — under constraints that most industries don't face. Batch and expiry mean stock has a clock on it, active ingredients carry long lead times, and a share of demand arrives as lumpy institutional or tender volume rather than a smooth trend. The plan has to respect all three, not just predict a number.

    Because you cannot cover uncertainty by holding more stock. In most sectors extra inventory is an insurance premium; in pharma it expires, so an over-forecast becomes a write-off while an under-forecast becomes a stockout with patient impact. Planning has to find the level that survives both, which means the forecast's confidence matters as much as its value.

    By sizing cover against remaining shelf life rather than a flat number of days, and by counting existing batches as supply only for the period they can actually serve. A batch that expires before the demand it was bought for is not cover — treating it as cover is how expiry write-offs are planned in by accident.

    Separately from retail. Institutional volume is lumpy and event-driven, so blending it into a retail trend corrupts both. It is classified as a lumpy or intermittent pattern, forecast with honest confidence bands, and where a tender outcome is known it is treated as firm demand rather than something to be predicted.

    They push the commitment point months ahead of the demand it serves, which means you are buying against the least certain part of the forecast. Planning the long-lead actives on their own horizon — and showing the confidence at the moment of commitment — lets a planner decide deliberately how much risk to take rather than discovering it later.

    No. Likwid layers on top of the ERP you already run, reads the consumption, batch and stock history it needs, and writes back plans and orders you approve. Your system of record — and your validated processes around it — stay exactly where they are.

    Looking at the wider system? See ERP for pharmaceutical manufacturing · inventory · pricing.

    See it plan against your own shelf life

    A 30-minute walkthrough on your SKUs — cover sized to remaining life, batches counted with their expiry, and the API commitment that follows.

    Talk to us

    See Likwid on your own data

    Leave your details and we'll set up a 30-minute walkthrough on your numbers — no slides. We reply within a day.

    Prefer email? admin@likwid.co.in