Big Data’s Day in the Life of a Restaurant

Big Data brings together large amounts of siloed information in one place to make it more meaningful and useful. But it has a different impact on each hospitality worker. Mike Shipley explains how work life gets easier and more efficient for each restaurant persona after data is harnessed.

Inside a restaurant, “mise-en-place” rules operations. French for “everything in its place,” it’s the philosophy employed to keep kitchens and dining rooms organised and running efficiently.

But what happens when restaurant data gets the mise-en-place treatment?

“Big Data” might sound ominous and perhaps technologically overwhelming. In reality, it’s a vital tool to run a successful hospitality enterprise. The average restaurant sits upon heaps of data, often siloed and therefore also meaningless. But put together those data streams in context, unsiloed and all in one place, and now the information has meaning. The analytics become an advantage, as the restaurant owner can use data to gain a more complete picture of the business, how its customers and staff behave and ultimately how that drives sales and profit. On a dashboard, they can see one version of the truth. That impacts every restaurant employee differently every day.


Owners/managers have three primary responsibilities: the staff, the customers and the finances. They need a balanced performance scorecard to keep track of the daily burning questions: Is the right team in place to give the customers the best possible experience and service? Is the schedule set correctly to ensure the best of the staff are deployed and at the right time of day to maximise revenue? Using Big Data, it’s easy to answer those questions and more.

The first things owners/managers would do with Big Data every workday is look at a dashboard to see how staff is deployed, calculate what percentage of sales that represents, project the hourly revenue and optimise the staff schedule based on customer demand and staff performance.

Next, they’d investigate the restaurant’s inventory to make sure food production costs are in line with the restaurant’s budget. For example, the owner/manager might expect a restaurant’s food production costs to total 25% to 30% of forecast revenue with labour costs running at 25 percent of revenue. Most would be content with that, and Big Data would help them maintain the correct amount of inventory and deploy the right staff at the right time.

In the longer term, they can use sentiment analysis to mine customer feedback and use it to predict the restaurant’s health and how often customers will return. Customers give free, unsolicited feedback on a variety of social channels, such as Facebook, Twitter, Google, Yelp and TripAdvisor. To forecast accurately, owners/managers must know what customers truly think of their establishments and staff. Generally, positive sentiments tend to predict sales growth and negative sentiments portend weaker sales.

Or, for example, they could see the number of negative mentions about a certain menu item. Armed with that knowledge, the owner/manager can get the chefs to adapt the menus or menu items accordingly.

And within the restaurant, the register is a treasure trove of useful customer and staff information because it reveals what customers buy and what the staff sells. For example, the data might show a certain steak on the menu sells well. But how often does a server sell a really good bottle of wine along with it? If not often, there’s room to maximise opportunities for upsells.

Big Data works in service to the ultimate restaurant owner/manager goals – a happy and engaged staff optimised to serve customers well, hitting sales forecasts and labour targets and delivering margins.


The modern kitchen bustles with activity, stress and data. Chefs too can apply analytics to make menu development, menu engineering and reducing waste easier to handle.

Big Data can show chefs which menu items sell the most on certain days and certain times. Armed with that knowledge, chefs can buy and inventory products accordingly for better efficiency. On the other hand, they can also see which menu items don’t sell well, remove those dishes and reduce stocks of the ingredients in those items if necessary.

It can also help them weather seasonality of certain goods more effectively. Take salmon, for example. Its price can change on seasonality and supply-and-demand issues. Big Data can show cost-price inflation and help a chef predict when to buy salmon at lower prices or decide to not buy at all. The data might show mackerel is a better option because it’s more cost-stable at certain times. That’s important information for chefs, who have a set budget on cost of sale. It helps them control one of the biggest costs in the hospitality industry – kitchen waste.

18% of all food purchased by UK restaurants is wasted, with an average cost of £10,000 per outlet each year. Chefs must know which of their ingredients cause the most waste during food prep and be able to adapt. If a chef buys a whole fish at £15 a pound but gets only a 70% yield, it might be better to pay £20 for just the fish fillets. Big Data compiles the data in one place to show chefs waste over time and calculates a better alternative so they can make better purchasing decisions.

The chef is also responsible for having the right people in the kitchen when the house is particularly busy. They can see demand looms and at what times it peaks, so they can predict accurately how much food to prepare. They can ensure the optimum amount of product prepared is ready for service to meet customer demand, but ideally not have to throw anything away at the end of service.


By having staff data in one place, managers can compare every server on the floor in terms of how much they sell and how much they generate in tips. And they can see that data for the slowest or busiest shifts. Managers can also track who the best staff performers are and share their best practices or observe them in action to improve their craft. Motivated by earning potential, they perform better for customers and managers.

Big Data also empowers staff. They can use their mobile devices to request holidays, see pay slips, learn when they’ll get paid, find out their shifts in advance and swap shifts seamlessly without having to contact colleagues or managers directly. Yet, managers still retain control. They can set parameters so, for example, only the most productive employees can swap shifts at certain times.

But by offering options such as mobile shift swapping, Big Data helps keeps staff happy by giving them some control over their work lives. In an industry where high turnover is common and the cost to recruit and train new employees eats away at the bottom line, it pays for owners/managers to use analytics to keep their staff engaged, happier and more productive.

Find out more about data and analytics for the hospitality sector in our white paper.

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