Automating inventory predictions for a mid-sized retail chain.

About

RetailFlow is a mid-sized clothing retailer struggling with manual stock counting and frequent out-of-stock scenarios across their 15 physical locations. They relied on fragmented spreadsheets, leading to data silos and inefficient purchasing decisions. They needed a modern system to centralize their data and forecast demand.

Challenge

The primary challenge was migrating a decade's worth of messy, unstructured data into a new, cloud-based platform without disrupting daily store operations. Additionally, store managers were highly accustomed to their legacy methods and hesitant to adopt a complex new software tool.

Process / Approach

We started with generative field research, shadowing store managers to understand their daily physical constraints. Recognizing they are rarely at a desk, we designed a simplified, mobile-first dashboard for floor staff and a comprehensive desktop analytics view for warehouse managers. We used an agile, phased approach, releasing the mobile app to two pilot stores for feedback before refining and rolling it out company-wide.

Key decisions

• • Prioritized a mobile-first interface for store managers moving on the floor.
• • Implemented a phased rollout starting with two pilot stores to minimize operational risk.
• • Used a simplified traffic-light visual system (Red/Yellow/Green) for stock urgency rather than complex data tables.

Results / intended outcome

Reduced manual inventory counting time by 45% per week. Decreased stockout incidents by 30% within the first three months of the full rollout. User adoption reached 95% among floor staff within the first month due to the simplified mobile UI.

Gallery

Project images will be connected through the media library in the next production phase.