Demand Planning Platform

Part of the worlds-biggest-software-project initiative.

An AI-native, open-source demand planning platform combining statistical forecasting, real-time demand sensing, and consensus planning for supply chain teams.

Demand Planning Platform is a candidate open-source alternative to enterprise demand planning suites such as SAP IBP, Kinaxis Maestro, Blue Yonder Luminate, and o9 Solutions. It targets supply chain, demand planning, and S&OP teams who need modern AI-driven forecasting without seven-figure licence commitments or 12–18 month implementations.

Why Demand Planning Platform?

Enterprise platforms are prohibitively priced. SAP IBP starts at ~$100,000/year; Kinaxis, Blue Yonder, and o9 are custom-quoted at similar enterprise tiers, locking out mid-market and smaller buyers.
Implementations take 12–18 months. SAP IBP and Kinaxis projects routinely run more than a year and require certified consulting partners, while Logility ships in 3–6 months for the mid-market.
APIs are gated behind contracts. Only Anaplan and Prediko publish developer documentation; every other incumbent hides API specs behind enterprise customer portals, blocking evaluation and integration.
AI depth is uneven. Statistical-only methods underperform in volatile markets, yet most platforms still require manual model selection, manual bias correction, and meeting-driven consensus reconciliation.
No open standards exposure. No incumbent natively exposes data in SCOR-DS or GS1-compliant formats, limiting interoperability across the planning stack.

Key Features

Forecasting Core

Multi-model statistical and ML demand forecasting with automated model selection per SKU/location
Demand hierarchy management across product, location, channel, customer, and time dimensions
Historical data cleansing: outlier detection, event isolation, and zero-demand handling
Seasonality, trend, and promotional uplift decomposition
Forecast accuracy dashboard covering MAPE, bias, and WAPE with actuals overlay and drill-down

Demand Sensing & Signals

Short-horizon forecast refresh from near-real-time order or POS signals
Probabilistic forecast output with configurable confidence intervals
External signal ingestion for weather, economic indicators, social sentiment, and web traffic
Bias detection and correction layer monitoring forecast bias by product, channel, and region

Collaborative & Consensus Planning

Multi-user concurrent editing with change attribution
S&OP process support with structured monthly consensus workflow and approval states
Forecast Value Added (FVA) analysis tracking the contribution of each planning step
New product forecasting using similar-item analogues
Promotion and event management with manual uplift entry and historical promotion modelling

AI Co-pilot

Natural language scenario co-pilot translating free-text "what-if" assumptions into quantitative scenarios
Consensus reconciliation agent aggregating commercial, marketing, and finance inputs and flagging disagreements
Automated bias detection and correction with explainable audit trail
Automated statistical model selection and ensemble management evaluating 20+ models per SKU

Integration & Extensibility

REST API with public OpenAPI documentation for all core planning data objects
ERP data ingestion via REST API, CSV, JSON, and webhook
Exception-driven planner alerts for stock-out risk, forecast deviation, and bias threshold breach
Export of demand plan to downstream supply and inventory planning processes

AI-Native Advantage

Unlike incumbents whose AI features are bolted onto legacy planning engines, this platform treats multi-signal demand sensing, automated ensemble selection, and bias auto-correction as first-class capabilities. A natural-language scenario co-pilot lets planners express assumptions in prose rather than configuring model parameters, and a consensus reconciliation agent collapses meeting-driven S&OP cycles into continuous, auditable planning. Forecast explainability and FVA scoring are built into every model so AI-generated forecasts can be defended in S&OP reviews.

Tech Stack & Deployment

The platform targets cloud-native deployment with a publicly documented REST API as the primary integration surface — directly addressing the gap that enterprise incumbents leave by gating API documentation behind contracts. Planned alignment with industry standards includes SCOR (ASCM), CPFR (GS1/VICS), IBF forecasting metrics (MAPE, bias, FVA), and S&OP/IBP process cadences. An MCP server implementation is on the backlog for AI agent integration with downstream supply planning tools.

Market Context

The supply chain planning market is valued in the tens of billions globally, with demand planning the largest segment and the AI-native segment growing fastest. Incumbent pricing ranges from $100,000+/year (SAP IBP) to custom enterprise quotes (Kinaxis, Blue Yonder, o9), with mid-market alternatives (Logility, Flowlity) more accessible and AWS Forecast pay-per-use. Primary buyers are VPs of Supply Chain or Demand Planning, demand and supply planners, commercial finance teams, and procurement leaders driving S&OP processes; an IBM survey cited in the research found 90% of executives expect supply chain workflows to include AI assistance by 2026.

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.