Smart Inventory Management System for Restaurants

Team context

Completed by Amrutha, Jaswant, Sindhuja and Swarup. This case study presents the team's shared research and design process without assigning unverified individual contributions.

What needed to change?

Restaurant staff repeatedly check stock levels, expiry dates, quality and deliveries by hand. The team's fieldwork found that inventory checks can take roughly 30 to 90 minutes and remain partly manual even where restaurants use digital operating systems.

How assumptions were reduced

1. Approached 15 restaurants across two days and recorded 12 interviews with owners, managers and staff.
2. Observed restaurant work during busy and semi-busy periods, including inventory and restocking walkthroughs.
3. Synthesised evidence using coding, affinity mapping, empathy mapping and an ecosystem map.
4. Identified recurring needs around low-stock visibility, expiry urgency, quality checks, delivery tracking and reduced duplicate recording.

From evidence to direction

1. Framed the opportunity: make day-to-day inventory management more efficient while reducing staff effort.
2. Generated concepts using SCAMPER and Crazy 8s, including automatic tracking, stock prediction and attention-based alerts.
3. Selected an automatic inventory-management concept for restaurant managers and owners.
4. Built a medium-fidelity Figma prototype covering inventory, reordering, deliveries, quality checks, expiry and billing updates.
5. Tested key tasks with five participants and iterated the prototype from their feedback.

What the work achieved

The final concept helps staff identify low-stock and expiring products, reorder items, accept deliveries after quality checks, add inventory and understand automatic stock changes after sales. Testing led to clearer expiry indicators, a dedicated Add Item action, reorder confirmation, delivery feedback and improved issue visibility.