Agent CatalogueSolutionsSupply Chain Planning

Supply Chain Planning

From demand signal to optimised supply

The Supply Chain Planning process connects demand sensing, inventory optimisation, production scheduling, and supplier collaboration into a single intelligent loop. MyWave agents translate real-time demand signals into optimised supply plans, reduce excess inventory, and ensure production lines are never starved of material.

10
Process Steps
50+
AI Agents
Up to 70%
Automation Rate
Planning cycle: days to hours
Cycle Time
Optimal inventory at lower cost
Key Benefit

Agent Flow

Each step shows the AI agent responsible, what it does, which systems it touches, and what it produces.

Phase 1

Demand Sensing

1
AI Agent

Demand Sensing & Signal Aggregation Agent

Aggregates demand signals from POS data, customer order history, market trends, and promotions calendars to generate a short-term demand forecast at SKU/location level.

SAP IBPPOS SystemsCRMMarket Data
Output: Short-term demand forecast with confidence intervals
Exception: Flags statistical outliers and new product introductions for planner review
Next Phase
Phase 2

Demand Planning

2
AI Agent

Statistical Forecasting Agent

Runs ensemble forecasting models (ARIMA, ML-based, causal) and selects the best-fit model per SKU, incorporating seasonality, promotions, and lifecycle adjustments.

SAP IBPAnalytics EnginePromotion Calendar
Output: Consensus demand plan with model selection rationale
Next Phase
Phase 3

Inventory Optimisation

3
AI Agent

Safety Stock Optimisation Agent

Calculates optimal safety stock levels per SKU and location based on demand variability, supplier lead time variability, and target service levels.

SAP IBPSAP MMSupplier Lead Time Data
Output: Updated safety stock parameters with service level impact analysis
Exception: Alerts planners to SKUs where safety stock cannot be achieved within budget constraints
Next Phase
Phase 4

Supply Planning

4
AI Agent

Constrained Supply Planning Agent

Generates a feasible supply plan that balances demand requirements against production capacity, material availability, and supplier constraints.

SAP IBPSAP PPCapacity Management
Output: Feasible supply plan with capacity utilisation view
Exception: Triggers capacity exception alerts and suggests overtime or subcontracting options
Next Phase
Phase 5

Production Scheduling

5
AI Agent

Production Scheduling Optimisation Agent

Converts the supply plan into a detailed production schedule, sequencing work orders to minimise changeover time, maximise throughput, and meet delivery commitments.

SAP PPMESCapacity Planning
Output: Optimised production schedule with sequencing rationale
Next Phase
Phase 6

Material Requirements

6
AI Agent

MRP Exception Management Agent

Processes MRP results and intelligently filters, prioritises, and resolves MRP exceptions — converting actionable exceptions into purchase orders or production orders automatically.

SAP MMSAP PPMRP Engine
Output: Actioned MRP exceptions with auto-generated orders
Exception: Escalates critical shortage situations with lead time analysis and alternative sourcing options
Next Phase
Phase 7

Supplier Collaboration

7
AI Agent

Supplier Capacity Confirmation Agent

Shares rolling forecasts with key suppliers via the supplier portal and collects capacity confirmations, flagging gaps against planned requirements.

SAP SRMSupplier PortalEDI Gateway
Output: Supplier capacity confirmation with gap analysis
Exception: Initiates alternative sourcing or expediting process for confirmed shortfalls
Next Phase
Phase 8

Inventory Management

8
AI Agent

Excess & Obsolescence Management Agent

Continuously identifies slow-moving and excess inventory, calculates E&O provisions, and recommends disposition actions — redistribution, markdown, or write-off.

SAP MMSAP FIInventory Analytics
Output: E&O report with disposition recommendations and financial impact
Next Phase
Phase 9

Logistics

9
AI Agent

Inbound Logistics Coordination Agent

Coordinates inbound shipments from suppliers, manages dock scheduling, and triggers early warning alerts for delayed deliveries that could impact production.

SAP TMCarrier APIsWarehouse Management
Output: Inbound shipment visibility dashboard with delay alerts
Exception: Automatically expedites critical components via premium freight when production risk is high
Next Phase
Phase 10

Performance

10
AI Agent

Supply Chain KPI Monitoring Agent

Tracks end-to-end supply chain KPIs — forecast accuracy, fill rate, inventory turns, OTIF — and generates automated performance reports with root cause analysis.

SAP IBPSAP Analytics CloudERP
Output: Supply chain performance dashboard with trend analysis and alerts

Expected Outcomes

Typical results from full deployment

+20–30%
Forecast Accuracy
Improvement in demand forecast accuracy through ensemble AI models
–15–25%
Inventory Reduction
Working capital release through optimised safety stock levels
+15%
OTIF Performance
On-time in-full delivery improvement
+50%
Planner Productivity
Reduction in time spent on exception management

Process Phases

1
Demand Sensing
2
Demand Planning
3
Inventory Optimisation
4
Supply Planning
5
Production Scheduling
6
Material Requirements
7
Supplier Collaboration
8
Inventory Management
9
Logistics
10
Performance