Domains
Demand & Supply Planning
End-to-end planning from demand forecasting through supply plan generation, built on the AWS Supply Chain 3-step process and executed by agents under AIIO. Two of the six decision domains Autonomy covers.
"By 2026, 75% of large enterprises will have adopted AI-augmented planning... moving from deterministic to probabilistic planning."
"The biggest opportunity in supply chain planning isn't better algorithms, it's closing the gap between what the plan says and what actually happens on the ground."
The AWS SC 3-Step Planning Process
of enterprises adopting AI planning by 2026
Gartner
reduction in lost sales from better demand sensing
McKinsey
reduction in inventory carrying costs
BCG
global supply chain planning market by 2030
Grand View Research
Step 1: Demand Processing
Aggregate demand from statistical forecasts, customer orders, and consensus inputs. Net out committed and allocated inventory, then time-phase demand across the planning horizon with P10/P50/P90 percentiles for uncertainty quantification.
Step 2: Inventory Target Calculation
Calculate safety stock and target inventory levels using four policy types:
- Absolute Level - Fixed quantity targets (simplest)
- Days of Coverage (Demand) - Dynamic targets based on actual demand
- Days of Coverage (Forecast) - Dynamic targets based on forecast
- Service Level - Statistical safety stock with z-score calculation
Hierarchical overrides ensure the right policy applies at the right level: Product-Site overrides Product overrides Site overrides Config defaults.
Step 3: Net Requirements Calculation
Time-phased netting computes gross requirements minus on-hand minus scheduled receipts. Multi-level BOM explosion handles recursive component requirements. Sourcing rules with priorities determine whether to buy, transfer, or manufacture. Lead time offsetting ensures orders are placed when they need to be, not when they're reviewed.
Master Production Scheduling (MPS)
Strategic production planning with rough-cut capacity checks. MPS drives finished goods production at the aggregate level, balancing demand requirements against available capacity and material constraints.
"The shift from deterministic MPS to probabilistic planning is the most significant change in production planning in 30 years. Organizations that master this transition will have a fundamental competitive advantage."
"By interacting with planners, we get all of their knowledge and experience. The planner's implicit knowledge can be made into a standardized, explicit process."
Material Requirements Planning (MRP)
Detailed component requirements exploded from MPS. Multi-level BOM processing with scrap rates, yield adjustments, and configurable lot sizing rules (LFL, FOQ, POQ, EOQ, MIN/MAX).
Capacity Planning
Resource utilization analysis identifies bottlenecks before they become problems. Rough-cut capacity planning at the MPS level and detailed CRP at the MRP level ensure plans are feasible before release.
Industry Perspective
"AI in planning works best when it augments human judgment, not when it replaces it. The most successful implementations keep planners in the loop."
"Companies using AI-driven planning see 10-20% improvement in forecast accuracy and up to 65% reduction in manual planning effort."
"Only 7% of supply chains can sense and shape demand in real-time. Autonomous planning closes this gap."
reduction in manual planning effort
BCG, 2024
improvement in forecast accuracy with AI
BCG/MIT Sloan
of supply chains can sense demand in real-time
Supply Chain Insights
The S&OP Cycle
This plane intersects with
Supply Planning sits in the middle of the stack, it's where the most intersections live.
Portfolio × Supply Planning
Launch calendars need capacity and long-lead component feasibility.
Demand Shaping × Supply Planning
Promo surge commits drive pre-build and pre-position decisions.
Supply Planning × Production Scheduling
WO commitments + changeover cost as a Lagrangian dual price returned upward.
Supply Planning × Transport
Deployment plans become TMS loads; landed-cost and capacity feedback shape the next run.
See planning in action
Walk through the full planning cycle from demand signal to supply plan execution.