DEMAND

Demand planning software built for pharmaceutical complexity

Forecast more accurately. Plan collaboratively. 
Replace spreadsheets with AI-powered precision

Demand Hero V2
AI-Powered Demand Forecasting

Improve your forecast accuracy with an AI engine that learns from your historical data

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    Forecasts that learn from actual demand patterns across different products.
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    Automatic detection of seasonality and trend shifts.
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    Gives pharma planning teams confidence in their forecast — even with volatile demand and new product launches.

Why it matters:

Better forecasts mean less excess inventory, fewer stockouts, and more confident planning decisions.

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Full Visibility & Forecast Comparison

Compare multiple forecast methods side-by-side to find the best approach for each product

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    Run side-by-side comparisons of forecast accuracy and bias between methods.
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    Flexibly assign different forecast approaches to different product segments.
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    Systematically track forecast accuracy against actual sales, allowing planners to report on materially improved forecast reliability and reduced manual rework.

Why it matters:

With centralized demand planning, you kill the spreadsheet chaos and finally align teams.

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Demand Segmentation

Segment demand by channel, customer, or market to see what is actually driving your business

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    Segment demand by channel, customer, or market.
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    Integrate customer orders to provide a clear view of firm commitments versus projections.
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    Use an intuitive interface that allows you to freely aggregate and disaggregate your data.

Why it matters:

Better visibility into demand drivers helps you make smarter and more confident supply decisions.

Demand 2 V2

Demand Planning FAQ

Demand planning software helps businesses predict future demand by analyzing historical data and market inputs. Tools like PLAIO consolidate forecasts and purchase orders, apply statistical models and machine learning, and offer manual overrides, dashboards, and simulations to support accurate, data-driven planning.

No. PLAIO’s Demand Planning combines machine learning with full planner transparency. Forecast accuracy, bias, and error are continuously measured against actual sales, and planners can always review, adjust, and override forecasts. AI supports decision-making but never removes human control.

Yes. PLAIO is designed for consensus demand planning. Sales, marketing, and finance can all contribute through dedicated forecast lines, comments, and reviews. Market intelligence such as promotions, tenders, and launches is treated as first-class inputs.

No. PLAIO works seamlessly with spreadsheets. You can import and export forecasts at any time, or continue collecting inputs in spreadsheets while centralizing and consolidating them in PLAIO. This allows teams to transition at their own pace without losing flexibility.

PLAIO has an integration layer that works with most ERP systems, including SAP, using standard interfaces and APIs. The ERP remains the system of record, while PLAIO acts as an advanced planning layer that enhances forecasting, visibility, and decision support without disrupting execution processes.

Yes. PLAIO keeps a full history of forecast versions and changes. This allows teams to trace what was forecasted, when it changed, and how accuracy evolved over time - supporting audits, compliance requirements, and continuous improvement.

Absolutely. PLAIO is purpose-built for pharmaceutical supply chains. It supports multi-market aggregation, long planning horizons, expiry awareness, and demand signals from multiple sources; ensuring forecasts reflect real-world pharma complexity.

Upgrade to Demand planning software made for pharma

Start planning smarter with PLAIO.

Speak to an expert in Demand planning

Connect the Dots Across Your Planning Process

Optimize supply 
with precision.

Turn your forecast into feasible, constraint-ready plans with our

Supply Planning Software

Keep production on schedule.

Align supply with optimized, line-level schedules using

Production Scheduling Software

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