Demand-Driven MRP buffer positioning and management skill with dynamic adjustment
Scanned 9/2/2026
Install to Claude Code
npx -y skills add a5c-ai/babysitter --skill ddmrp-buffer-manager --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: ddmrp-buffer-manager
description: Demand-Driven MRP buffer positioning and management skill with dynamic adjustment
allowed-tools:
- Read
- Write
- Glob
- Grep
- Bash
metadata:
specialization: supply-chain
domain: business
category: inventory
priority: future
graph:
domains: [domain:supply-chain]
specializations: [specialization:supply-chain-optimization]
skillAreas: [skill-area:procurement-management, skill-area:capacity-planning-ops, skill-area:quantitative-modeling]
workflows: [workflow:vendor-onboarding, workflow:vendor-evaluation]
roles: [role:supply-chain-analyst, role:procurement-manager, role:operations-analyst]
---
# DDMRP Buffer Manager
## Overview
The DDMRP Buffer Manager implements Demand-Driven Material Requirements Planning methodology for inventory management. It handles strategic buffer positioning, zone calculations, dynamic adjustments, and execution prioritization to create flow-based material planning.
## Capabilities
- **Strategic Decoupling Point Identification**: Optimal buffer location selection
- **Buffer Profile Assignment**: Categorize items by lead time and variability
- **Buffer Level Calculation**: Green, yellow, red zone determination
- **Dynamic Adjustment Factors**: Planned and recalculated adjustments
- **Net Flow Position Calculation**: Real-time inventory position
- **Execution Visibility and Prioritization**: Color-coded supply priorities
- **Buffer Health Monitoring**: On-target percentage tracking
- **Lead Time Compression Analysis**: Identify lead time reduction opportunities
## Input Schema
```yaml
ddmrp_request:
items: array
- sku_id: string
average_daily_usage: float
decoupled_lead_time: integer
minimum_order_quantity: integer
variability_factor: string # low, medium, high
lead_time_factor: string # short, medium, long
bom_structure: object
planned_adjustments: array # Promotions, seasonality
current_positions: array
calculation_scope: string # positioning, sizing, execution
```
## Output Schema
```yaml
ddmrp_output:
buffer_positions: array
- sku_id: string
is_decoupling_point: boolean
rationale: string
buffer_levels: array
- sku_id: string
buffer_profile: string
zones:
green: integer
yellow: integer
red: integer
red_safety: integer
total_buffer: integer
execution_priorities: array
- sku_id: string
net_flow_position: integer
net_flow_equation: string
priority_color: string
on_hand: integer
on_order: integer
qualified_demand: integer
buffer_health: object
```
## Usage
### Buffer Positioning Analysis
```
Input: BOM structure, lead times, demand variability
Process: Identify strategic inventory positioning points
Output: Recommended decoupling points with rationale
```
### Buffer Sizing Calculation
```
Input: ADU, lead time factors, variability factors
Process: Calculate zone sizes using DDMRP formulas
Output: Green, yellow, red zone levels by buffer
```
### Execution Priority Management
```
Input: Current inventory, orders, qualified demand
Process: Calculate net flow position, assign priority color
Output: Prioritized replenishment recommendations
```
## Integration Points
- **DDMRP Platforms**: Demand Driven Technologies, Replenishment+
- **ERP Systems**: BOM, inventory, demand data
- **Planning Systems**: Qualified demand, supply orders
- **Tools/Libraries**: DDMRP algorithms, flow optimization
## Process Dependencies
- Demand-Driven Material Requirements Planning (DDMRP)
- Inventory Optimization and Segmentation
- Safety Stock Calculation and Optimization
## Best Practices
1. Start with pilot categories before full rollout
2. Validate decoupling point selection with operations
3. Monitor buffer health daily during transition
4. Train planners on net flow execution
5. Review dynamic adjustment factors seasonally
6. Track lead time compression progress
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