How Big Data Works For Hospitality

By Sasha Poljak, CEO, Nimble Software Systems

Predictive analytics eliminate the guesswork from staff scheduling.

How do you, as a Detroit sports bar manager, staff for the evening shift when the #1 ranked Ohio State Football team is playing #4 ranked Michigan State on an unusually warm and sunny Saturday afternoon in December, following the previous Friday’s DJIA drop of 700 points which came as a result of the consumer confidence report reflecting the worst sentiment in five years, predicting a long recession and corporate layoffs?

While there are so many moving parts in a dining establishment, labor is the second largest concern. Up until very recently, any effort to optimize labor was a dangerous guessing game. Management was left alone with semi adequate tools and no visibility to real data to create shifts, manage exceptions, and react to unexpected changes. 

Not any more; enter Big Data!  Today, management is able to take the guess work out of staff scheduling by taking the historical sales data, future business forecasts, as well as various environmental factors such as weather, financial news, and special events, and put that data through computing engine parameters in order to create the most optimized staff schedule. Apps that leverage machine learning also consider local labor rules, staff availability, preferences, performance indicators, and staff ranking.  The result is the most optimal, suggested staff schedule based on true data, rather than “tribal” guess work.  Subsequently, management is left to only deal with the exceptions.

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