Dynamic Safety Stock & Reorder Point Optimization in Retail Distribution

A national retail chain operating 12 regional distribution centers (DCs) supplying 400 retail store locations with 30,000 SKUs.

working capital unlocked by reducing unnecessary safety stock: $18Mworking capital unlocked by reducing unnecessary safety stock
retail store stockout incidents reduced: 45%retail store stockout incidents reduced

How the work runs

The pressure that made this worth automating, the steps the system runs, and what came out the other side.

Pressure & Trigger Points

Planners used static safety stock rules (e.g., maintain 14 days of supply for all SKUs), resulting in $25M in working capital tied up in slow-moving inventory.
Simultaneously, high-demand promotional SKUs suffered frequent stockouts due to unpredicted regional demand surges and transit delays.
Manual reorder point adjustments across 30,000 SKUs overwhelmed planning teams.

The run · 5 operational steps

Click any step to inspect telemetry signals, model reasoning, and governance gates.

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Purti continuously analyzes local sales velocity, weather patterns, promotional calendars, and carrier lead-time variability.

Input Signal:

Real-time operational telemetry & queue

Reasoning Pattern:

MCP grounded vector inference

Governance Gate:

Policy constrained with audit write-back

Verified Business Outcomes

$18M in working capital unlocked by reducing unnecessary safety stock buffers on stable SKUs.
Retail store stockout incidents reduced by 45% on high-demand promotional items.
Automated reorder point management across 30,000 SKUs, cutting manual planner workload by 80%.

Capabilities this relies on

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