Challenges: Restaurants, grocery stores, and other food service businesses face significant challenges in managing food waste. Traditional methods of tracking inventory and predicting demand are often inaccurate, leading to spoilage, overstocking, and unnecessary costs. This not only impacts profitability but also contributes to environmental problems. Simultaneously, optimizing HR deployment, particularly scheduling and resource allocation, can be a complex task. Manual scheduling processes are often inefficient and fail to consider factors like predicted customer traffic, employee skill sets, and real-time changes in demand, resulting in overstaffing or understaffing, impacting both labor costs and customer service. Developing this solution involved challenges in accurately predicting food demand and spoilage using data analytics, integrating with existing POS and inventory systems, and creating an intuitive interface for staff to manage schedules and resources. Data privacy concerns related to employee scheduling, ensuring the accuracy and reliability of the predictive models, and the initial cost of implementing the system was another challenge.