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Retail • Guadalajara

From Gut-Feel Purchasing to Predictive Restocking.

Store managers called the warehouse to check stock. Purchasing decisions came from Excel pivots and experience. We connected their 42 locations, centralized the data, and layered in a prediction engine that tells them what to reorder 3 days before they run out.

Location Guadalajara, MX
Retail store shelves

What We Found

  • warning Purchasing decisions based on Excel pivot tables and "how it felt last year" — no live demand data
  • warning Store managers calling the warehouse to ask "do we have this in stock?" — no shared inventory view
  • warning Stockouts discovered only when a customer complains. Restock orders always 2-3 days late
Capital Freed -22% overstock costs

The Journey

Phase 1 • Weeks 1-2

Connect the Locations

Connected all 42 point-of-sale systems to a central dashboard. For the first time, the purchasing team could see real-time stock levels across every location — no more phone calls to the warehouse, no more surprises. Every sale, every return, every transfer visible in one place.

Phase 2 • Weeks 3-4

Automate the Reorders

Set up automated reorder triggers: when a product drops below a calculated threshold at any location, the system generates a restock request and routes it to the right supplier. No human needs to notice the low stock. The purchasing team reviews and approves — one click instead of a morning of spreadsheets.

Phase 3 • Month 2+

Add the Prediction Layer

With 8 weeks of clean data, we layered in a demand prediction engine. It analyzes sales velocity, seasonal patterns, local events, and weather to forecast what each store will need 72 hours from now. Managers get a daily restock recommendation — not a 50-page report, just "order these 12 SKUs for Store #7 by Thursday."

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Results

Stockouts dropped 60% in the first quarter — mostly from just having visibility and automated triggers (Phase 1 & 2). The prediction layer added another level: instead of reacting to empty shelves, they now restock before it happens. Overstock costs fell 22%, freeing up capital that was sitting in slow-moving inventory.

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"I used to spend every Monday morning staring at Excel trying to figure out what to order. Now the system tells me 'Store 14 will need these products by Thursday' and I just approve it. I got my Mondays back."

Purchasing Director
Purchasing Director Multi-location retail chain, Guadalajara

60%

Fewer Stockouts

-22%

Overstock Costs

42

Locations Connected

72h

Advance Demand Visibility

Guadalajara metro area
Project Reach

42 retail locations across the Guadalajara Metro Area. From Excel pivots and phone calls to centralized inventory with predictive restocking.

Still Ordering Inventory from a Spreadsheet?

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