nPlan — Supply Chain Planning Platform
Next-generation Supply Chain Planning. A single integrated engine for S&OP, S&OE, APS, MRP and DRP. Powers up SAP, TOTVS, Oracle and Dynamics with AI-driven demand, inventory, supply, capacity and distribution planning.
Modules
- Demand — AI-driven demand forecasting, collaboration, and influence analysis
- Inventory — Automated inventory policy, ABC/XYZ segmentation, safety stock optimization
- Supply — Integrated replenishment, BOM explosion, production and purchase planning
- Capacity — Finite capacity constraint, labour/tool/storage constraints, calendar simulation
- Orders — Multi-level synchronization, pegging, and order generation
- Distribution — Logistics rules, transport constraints, and transfers management
Key Integrations
SAP, TOTVS, Oracle, Dynamics, Siemens Opcenter AS. Available on Siemens Xcelerator Marketplace.
Articles & Knowledge Base
- What is Supply Chain Planning (SCP) — Foundations of SCP, S&OP, S&OE, APS, MRP, DRP.
- NPLAN vs SAP IBP — Architecture, time-to-value, total cost, decision matrix.
- NPLAN vs Global Platforms — Comparison with o9, Kinaxis, Blue Yonder, OMP, Anaplan.
- NPLAN vs S&OP Platforms — Why a single planning engine outperforms S&OP-only platforms.
- NPLAN vs Gen-AI Solutions — Why AI without a planning engine produces suggestions, not viable plans.
- Plan and Schedule Adherence in Manufacturing — BTP, BTS, probabilistic execution model.
- AI Foundations for Supply Chain
- AI Use Cases in Supply Chain
- Scenario Simulation
- Planning vs Scheduling
- Forecast Accuracy
- Inventory Policy (ABC-XYZ)
- MRO Planning
- Demand Consolidation
- From Excel to Supply Chain Planning
- Supply Chain Planning Canvas
- nPlan + SAP Integration
- nPlan + Siemens Xcelerator
- nPlan + Opcenter AS Integration
Case Studies
Trusted by Stellantis, Grendene, Malwee, Polenghi, Premier Pet, Dana, Unipac, Mercur, Bartira, Peccin, Fey and more.
Plan and Schedule Adherence in Manufacturing
Adherence measures the degree to which execution matches the plan or schedule. It evaluates both execution quality and plan quality simultaneously. Every deviation is an error — but not always the operation's fault.
Build to Plan (BTP)
BTP = Volume × Mix. Volume = Total produced ÷ Total planned. Mix = Σ min(produced, planned) ÷ Σ planned per product. Excess production of one item never compensates for shortage of another.
Build to Schedule (BTS)
BTS = Volume × Mix × Sequence. Sequence is evaluated relatively — a single skipped order does not penalize the rest of the queue.
Probabilistic Execution Model
Execution depends on: Material, Machine, Tooling, Operator, Quality. Overall probability = product of individual probabilities. At 95% reliability each: 0.95⁵ = 77.4% overall adherence.
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NPLAN vs Gen-AI Solutions
Pure GenAI approaches (ERP copilots, in-house LLM solutions, GenAI startups) are useful for queries and productivity but do not solve planning. LLMs can suggest a plan but cannot guarantee viability: they do not recalculate material explosion, do not respect finite capacity, do not synchronize orders across BOM levels. Planning processes (MRP, production planning, supply optimization) are deterministic, auditable, reproducible calculations that belong to a planning engine, not to a conversational interface. NPLAN combines a planning engine with AI agents as interface, delivering enterprise-grade security: dedicated corporate model contracts, controlled data access, prompt protection layer, clear separation of data/engine/interface layers, full traceability.
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Unipac
Peccin
Premier Pet