Designed and implemented a decision-optimization system to improve staff scheduling and operational planning across retail store operations. The system uses mixed-integer programming to allocate staff across shifts, roles, and locations while respecting labor rules, demand patterns, and budget constraints. A complementary discrete-event simulation model was also built to optimize labor allocation, increasing average net earnings by 5.5%.