Problem

Our restaurant client was struggling to predict how many guests they would have on any given day, leading to overstaffing or understaffing and ultimately affecting their bottom line. They were relying on manual methods of forecasting, which were often inaccurate and time-consuming.

We needed a solution that would provide accurate and timely predictions of guest numbers, allowing the restaurant to staff appropriately and improve their overall efficiency.

Learn more about our solution here.

Solution

We developed an algorithm that used historical data on guest numbers, weather patterns, local events, and other factors to predict future guest numbers with a high degree of accuracy. The algorithm was integrated into the restaurant's existing POS system, allowing for real-time updates and adjustments based on actual guest numbers throughout the day.

The algorithm also provided insights into which factors had the greatest impact on guest numbers, allowing the restaurant to make data-driven decisions about staffing levels and marketing efforts.

Impact

Improved accuracy of guest number predictions by X%
Reduced labor costs by X%
Increased revenue by X%

"This algorithm has completely transformed our business. We're now able to staff appropriately and make data-driven decisions that have had a significant impact on our bottom line."

Team

John Smith - Data Scientist
- Developed the algorithm and integrated it into the POS system
- Analyzed data to identify key factors impacting guest numbers
Jane Doe - Project Manager
- Oversaw the project from start to finish, ensuring timely delivery and effective communication with the client
- Liaised with the restaurant's management team to ensure successful implementation of the algorithm

Algorithm Improves Restaurant Guest Predictions