Compass Coffee Uses Legion Workforce Management to Increase Employee Productivity by 50 Percent Through Labor Forecasting and Scheduling Automation

Share Article

Data-driven D.C. coffee roaster and cafe chain selects Legion Technologies for workforce management

By using data to accurately forecast busy times in our cafés, Legion helps us be efficient with our scheduling while maintaining the legendary service that our customers expect.

Legion Technologies, the Demand-Ready Labor Platform for today’s workforce, announced that Compass Coffee has deployed Legion Technologies for end-to-end scheduling and forecasting capabilities across their eleven locations in Washington D.C.

Founded in 2014 by Michael Haft and Harrison Suarez,​ ​former Marines who served in Afghanistan, Compass Coffee started in the Shaw neighborhood of Washington D.C. and has expanded to eleven locations including a roasting facility.

Compass Coffee decided to use the Legion AI-powered labor platform to accurately forecast demand across their locations, factoring in both historic traffic patterns and variables such as weather and events. The company uses this forecast to automate scheduling based on customer demand, the demands of their business and the preferences of their team.

“Legion takes into account the needs of our customers as well as the schedule preferences of our team,” says Haft, co-founder of Compass Coffee. “By using data to accurately forecast busy times in our cafés, Legion helps us be efficient with our scheduling while maintaining the legendary service that our customers expect.”

“Previously, I could go in and fix the schedule every week, but it was like playing whack a mole ...every single week, you have to go in and tweak the schedule; in some cases, the manager doesn’t know why they are doing a bad job...or why they didn’t follow rules. Legion has helped us get the productivity numbers we are looking for, with a 50 percent improvement, through scheduling automation.”

Legion forecasting is powered by machine learning algorithms that create highly accurate forecasts. Internal research by the company has shown 98 percent accuracy in labor demand forecasts. Legion customized the machine learning model for Compass and each of its locations so every café’s specific patterns and nuances are factored into a continuous learning model. Legion also integrates labor compliance laws to automatically create fully-compliant schedules that factor in state and city regulations while providing detailed analytics for workforce managers.                                                        

“Almost 60 percent of the U.S. workforce is comprised of hourly employees and it’s clear there’s a need for data-driven solutions,” said Sanish Mondkar, CEO of Legion Technologies. "Legion marries data science and machine learning with modern, intuitive interfaces so processes that used to take hours are now solved quickly and efficiently."

“Compass Coffee has always been highly data-driven,” says Suarez. “Each batch of coffee we roast undergoes a rigorous and detailed collections process. We routinely analyze water quality at our cafés. Now, with Legion, we can take that same focus on precision and apply it to make people’s days better. Our customers appreciate that we’re properly staffed, and our team appreciates that they get the hours they want. Legion helps us work smarter, and it gives us the data we need to more effectively manage our team.”

About Legion Technologies
Legion’s labor platform modernizes the hourly workforce management experience for both employers and employees. Legion enables companies to provide superb customer experiences by accurately forecasting demand and staffing the right employees at the right times. Results include labor efficiency, higher employee engagement, reduced compliance penalties, and time savings —all delivered via a smart, easy-to-use platform. Legion is used by a wide swath of companies including retailers, restaurants and fitness clubs with locations across the United States. Legion is headquartered in Redwood City, California.

Share article on social media or email:

View article via:

Pdf Print

Contact Author

Nancy Boas
Visit website