Stock Intelligence System with Seasonal Awareness

2025-01-01

Warehouse vs. live store inventory: monitored, compared, and corrected automatically.

Built a stock intelligence system for a fashion ecommerce brand. Pulls warehouse quantities from the accounting system, compares them to live Shopify inventory, detects discrepancies, and applies corrections with seasonal logic built in.

The challenge

A fashion brand with a physical warehouse and a live Shopify store constantly faces inventory drift: the store shows stock that is no longer in the warehouse, or warehouse arrivals are not reflected in the store. For a fashion brand, the timing of when you show stock matters. Swimwear in December misleads customers, even if units exist. Manual stock management across both systems was creating errors and customer service issues.

Approach

• Automated warehouse stock pulls via accounting API: current quantities per SKU per warehouse location
• Compared accounting quantities against live Shopify inventory levels in real time
• Discrepancy detection built: flags products where store inventory does not match warehouse count
• Correction scripts built: dry-run first, then execute. Full log of every change applied.
• Seasonal intelligence layer added: system considers product type and time of year before suggesting corrections. Swimwear is not pushed to live inventory in off-season even if warehouse stock exists.
• Audit reports generated per run: what matched, what was corrected, what was flagged for manual review

Results

• Real-time — warehouse vs. store inventory comparison
• Seasonal — logic: product type and time of year inform decisions
• 0 — manual inventory cross-checks needed
• Full — audit log of every correction applied

Tools used

Python, Shopify API, Accounting API, Inventory Logic, Seasonal Rules Engine