If/Then: Forecasted Inventory Optimization Engine
If/Then reduces holding costs by 40% with AI-driven forecasting and automated reorder logic for $2M+ footwear inventory.
The Challenge
If/Then managed more than $2M in footwear inventory using spreadsheets and an 8-person team. Manual forecasting created frequent overstocking, missed opportunities, and delays in ordering due to 120-day supplier lead times.
Without intelligent demand forecasting, the company struggled to balance stock availability against holding costs. The manual process couldn't scale with business growth or respond quickly to changing consumer preferences.
Our Approach
An AI-driven forecasting engine was built that analyzes Shopify sales velocity, seasonal patterns, customer behavior, and supplier timelines. The system automates reorder suggestions and provides a live dashboard for operational planning.
Implementation Phases
Connected Shopify API, imported 18 months of historical order data, standardized SKU catalog.
Built predictive models using sales velocity, seasonality, and supplier lead times.
Configured reorder triggers, automated alerts, implemented anomaly detection.
Launched live dashboard, trained operations team, refined forecasting parameters.
System Architecture
Live Shopify data, historical sales, supplier lead times
Python ML models, forecasting, anomaly detection
Optimized inventory recommendations, dashboards
Results & Impact
Reduction in manual forecasting and ordering hours
Decrease in excess inventory and storage expenses
No out-of-stock incidents in Q3–Q4 2024