A Case Study: A Popular New York Restaurant Chain Expands

A forecast for business: Helping retailers plan adequate staffing

Executive Summary:

Brothers Leo and Oliver Kremer have come a long way since opening their first restaurant eight years ago. With a strong desire to bring Bay Area-style burritos to the east coast, they launched the fast-casual chain Dos Toros Taqueria in New York City in 2009. Since then, they have developed 13 locations across New York and they will expand outside of the state for the first time with their newest location in Chicago at the end of this year.

"We are proud of Dos Toros' success in the busy New York City restaurant market and expanding to Chicago is one of the most exciting things we've done", said Oliver Kremer. "We now have about 475-500 people working for Dos Toros and we're committed to providing them with a good work environment and culture because they're the most important part of what makes us successful."

When Oliver and Leo started Dos Toros, they were starting from scratch. With absolutely no experience in the restaurant world (Leo was formerly a bassist for the rock band Third Eye Blind), they knew they had to act quickly when determining how to manage their new business venture - including how to staff appropriately, stock inventory, and plan revenues.

"It's always nerve-racking starting something new, and of course the restaurant industry is no exception," said Oliver. "But now that we've been doing this for almost a decade, we have found some extremely valuable tools that we rely heavily on."


Weather's Impact on Sales

"We're in a very weather-driven business," said Oliver. "Predictability is key in the restaurant industry and with Sales Temperature, we get essentially a smart algorithm that provides us with total clarity into future sales."

Because LaTulippe is focused on serving customers and making great-tasting, healthy food, he doesn't have time to manually forecast, so for the past year, DIRT has been relying on the simple-to-use and automated forecasting of Sales Temperature to predict customer rushes or slow times, and to help control labor and staffing.

The software application adds external factors, such as weather forecasts, to a restaurant's sales projections. It incorporates and interprets this data to make it easier for restaurant owners and managers to be able to calculate how many team members they'll need each week and how much inventory they'll need.

"While historical data is great for forecasting, it's time consuming to go over old numbers and try to determine what to do with that information," said Oliver.


Machine Learning Means Better Results

"There's a lot of software out there that tries to help you with forecasts and sales predictions, but they always fall short because they're not intelligent, so they keep making the same mistakes," said Oliver. "I don't claim to be an expert in machine learning, whatsoever, but I do know that it's one of the things that sets Sales Temperature apart from the competition."

Sales Temperature's cloud-based technology leverages machine learning to make it more efficient at making predictions over time, giving businesses a growing return on their investment.

Oliver says each of their locations has its own nuances and certain locations are impacted by the weather or other external factors more than others - for instance, some restaurants are really affected by Summer Fridays, and others tend to have smaller Sunday crowds. Sales Temperature helps them manage their 13 locations by looking at each one individually and being smart about understanding their individual patterns.

"We're able to more precisely forecast our week because we have a comprehensive forecast that constantly adapts to the specific characteristics of each location," said Oliver.


Forecasting for Normal Days, when you need it the most...

Oliver said he and his brother found, oftentimes, the regular weekday and weekend schedules are the hardest to plan for.

"Sales Temperature has been weirdly good during our normal weeks," said Kremer. "On a day-to-day basis, when nothing special is going on, we really need to have a reliable predicting tool and Sales Temperature regularly surprises us with its accuracy."

There have been times when Oliver and Leo are completely convinced that there's no way Sales Temperature's predictions are right - whether it's they need more inventory for a particularly busy Saturday or fewer staff on an upcoming slower-than-usual Friday - but then the software proves them wrong.

"We'll think - there's no way we're going to be that busy - we've never had a Saturday like that," said Kremer. "But then, low and behold, it'll happen."

Overall, Oliver said they appreciate Sales Temperature's detailed but uncomplicated approach to delivering forecasts. In fact, they have been so pleased with Sales Temperature that the company is currently in the process of establishing the software as the center of all of their sales projections.


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