Smart Ops
Smart Ops: AI-Based Inventory Cut Optimization
Client: Tier-1 Manufacturing & Retail Enterprise
Executive Summary
Challenge: Inaccurate demand forecasting led to $12M in tied-up capital and 15% lost-sales rate.
Solution: Predictive engine optimizes 'inventory cuts' by aligning procurement with real-time market signals.
Results: 20% reduction in carrying costs and 35% improvement in stock turnover.
The Challenge
The company was ordering inventory based on 30-day-old data, failing to account for seasonal spikes.
Dead Stock:Billions in capital locked in products that weren't moving.
Frequent Stockouts:High-demand items were out of stock due to slow cycles.
Wasteful Logistics:Inaccurate placement led to expensive expedited shipping.
The Solution
Replaces static rules with dynamic, predictive intelligence.
- Demand Forecasting 2.0: Analyzes external factors like weather and social trends.
- Dynamic Safety Stock: Adjusts levels for every SKU based on lead-time volatility.
- Automated Replenishment: Calculates exact order amounts to minimize travel distance.
- Anomaly Detection: Allows teams to pivot procurement within hours.