sop-scenario-modeler
S&OP scenario modeling skill for demand-supply-financial plan alignment with what-if analysis
Best use case
sop-scenario-modeler is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
S&OP scenario modeling skill for demand-supply-financial plan alignment with what-if analysis
Teams using sop-scenario-modeler should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/sop-scenario-modeler/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How sop-scenario-modeler Compares
| Feature / Agent | sop-scenario-modeler | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
S&OP scenario modeling skill for demand-supply-financial plan alignment with what-if analysis
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# S&OP Scenario Modeler
## 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
```yaml
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
```yaml
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
1. Define clear scenario naming conventions
2. Establish assumption documentation standards
3. Include sensitivity analysis on key drivers
4. Track scenario accuracy over time
5. Maintain version control on scenarios
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