Restaurant Labor Forecasting Tool Development

The project aims to develop an analytic tool using Looker Studio to forecast labor needs for specific roles within a Lone Star Texas Grill restaurant. By leveraging historical sales and labor data, the tool will enable restaurant managers to optimize staffing levels, ensuring efficient operations and cost management. The project will involve analyzing existing datasets to identify patterns and trends that influence labor requirements. Learners will apply their knowledge of data analytics and visualization to create a user-friendly interface that provides actionable insights. The goal is to enhance decision-making processes and improve operational efficiency by accurately predicting labor needs based on historical data. - Analyze historical sales and labor data to identify key trends. - Develop a forecasting model to predict labor needs for select roles. - Create a user-friendly interface in Looker Studio for data visualization. - Provide actionable insights to optimize staffing levels and improve efficiency.

Weekly Sales and Traffic Forecasting System

Lone Star Texas Grill seeks to enhance its operational efficiency by developing a robust forecasting system for its restaurants. The goal is to create a weekly forecast model that leverages historical sales and traffic data to predict future trends. This project will involve analyzing past sales and customer traffic patterns to generate accurate forecasts in 15-minute increments. The forecasts will be integrated into Business Intelligence (BI) tools, allowing restaurant managers to make data-driven decisions. By applying statistical analysis and data visualization techniques, learners will bridge classroom knowledge with real-world applications, enhancing their understanding of data analytics in the hospitality industry. The project will focus on creating a user-friendly interface for easy access and interpretation of the forecasts.

What is the right level of service for Lone Star

The objective is to complete a service audit of at least 2 locations, with one being our Milton location. Milton has recently launched an augmented service model using technology to entertain our guests and enhance their experience by allowing them to order, reorder and request service. The intent would be to get an unbiased comparison of service with and without this technology. This comparison would include (but not be limited to) speed of service, atmosphere, level of interaction from staff and managers, premises review and overall impression. The project would also include using the locations guest WiFi and engaging in "The Sizzle" Loyalty Program.

Unbiased Hospitality Forecasting

Using Cheque level historical data from 20 locations for a 3 year period, the objective is to build a weekly forecast that can be viewed at 15 minute increments across a variety of on premise and off premise channels. Influencing factors such as (but not limited to) weather, local demographics, and marketing initiatives need to be considered. The project is divided into 2 key areas: 1) Understanding what the influential factors are and what degree each impacts the overall results 2) Building a model that can project sales based on the variable factors and test using historical results.