S&OP Scenario Modeler
SkillCommerce & financeS&OP scenario modeling skill for demand-supply-financial plan alignment with what-if analysis
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
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Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the S&OP Scenario Modeler skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/business/supply-chain/skills/sop-scenario-modeler/SKILL.md and read by ahel’s review.
Overview
The S&OP Scenario Modeler enables comprehensive Sales and Operations Planning through multi-scenario modeling, demand-supply-financial plan alignment, and what-if analysis. It supports the monthly S&OP cycle by facilitating scenario comparison and consensus plan development.
Capabilities
- Multi-Scenario Demand Planning: Create and compare multiple demand scenarios
- Supply Constraint Modeling: Model capacity, material, and resource constraints
- Financial Impact Calculation: Revenue, margin, and cost impact analysis
- Capacity Utilization Optimization: Balance capacity across scenarios
- Inventory Investment Modeling: Working capital implications by scenario
- Gap Analysis and Reconciliation: Identify and resolve demand-supply gaps
- Executive Summary Generation: Automated scenario comparison reports
- Consensus Plan Tracking: Monitor adherence to agreed plans
Input Schema
sop_scenario_request:
base_scenario:
demand_plan: object
supply_plan: object
financial_targets: object
alternative_scenarios: array
- name: string
demand_adjustments: object
supply_adjustments: object
constraints:
capacity_limits: object
material_availability: object
financial_bounds: object
planning_horizon: integer
granularity: string
Output Schema
sop_scenario_output:
scenarios: array
- name: string
demand_plan: object
supply_plan: object
financial_projection: object
gaps: array
feasibility_score: float
comparison_matrix: object
recommendations: array
executive_summary: string
consensus_plan: object
Usage
Demand Scenario Comparison
Input: Optimistic, base, pessimistic demand scenarios
Process: Model supply response and financial impact for each
Output: Side-by-side comparison with recommendation
Capacity Constraint Analysis
Input: Demand plan exceeding capacity in Q3
Process: Model capacity addition, demand shaping, outsourcing options
Output: Feasible scenario with cost-service tradeoffs
Financial Plan Alignment
Input: Operations plan vs. financial budget targets
Process: Reconcile volume, price, cost assumptions
Output: Aligned operational-financial plan
Integration Points
- Planning Platforms: o9 Solutions, Kinaxis, SAP IBP connectors
- ERP Systems: SAP, Oracle for master data and constraints
- Financial Systems: Budget and forecast integration
- BI Tools: Visualization and reporting
Process Dependencies
- Sales and Operations Planning (S&OP)
- Demand Forecasting and Planning
- Capacity Planning and Constraint Management
Best Practices
- Define clear scenario naming conventions
- Establish assumption documentation standards
- Include sensitivity analysis on key drivers
- Track scenario accuracy over time
- Maintain version control on scenarios
- Ensure cross-functional alignment on assumptions
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
sop-scenario-modeler- Source
- github.com/a5c-ai/babysitter
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