Statistical safety stock calculation skill with service level targeting and variability analysis
Calculates optimal inventory buffers using statistical analysis of demand variability and service level targets.
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The Safety Stock Calculator provides statistical methods for determining optimal safety stock levels. It analyzes demand and lead time variability, converts service level requirements, and calculates appropriate buffer stocks to meet customer service targets while optimizing working capital.
safety_stock_request:
items: array
- sku_id: string
demand_history: array
lead_time: object
average: float
standard_deviation: float
review_period: integer
unit_cost: float
service_level_targets:
target_type: string # fill_rate, cycle_service_level
target_value: float # e.g., 0.95 for 95%
calculation_method: string # standard, periodic_review, simulation
simulation_iterations: integer # For Monte Carlo method
safety_stock_output:
calculations: array
- sku_id: string
demand_stats:
mean: float
std_dev: float
cov: float
lead_time_stats:
mean: float
std_dev: float
safety_stock_units: integer
safety_stock_days: float
service_level_achieved: float
investment_value: float
summary:
total_safety_stock_investment: float
average_days_coverage: float
service_level_distribution: object
recommendations: array
Input: Demand history, lead time, 95% service level target
Process: Calculate demand and LT variability, apply formula
Output: Safety stock in units and days of supply
Input: Complex demand patterns, variable lead times
Process: Simulate 10,000 demand-supply scenarios
Output: Simulation-based safety stock with confidence interval
Input: ABC/XYZ segmented portfolio
Process: Apply differentiated service levels by segment
Output: Tiered safety stock policy with investment optimization
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