The restaurant business is a notoriously relentless one, with rising labor and food costs, perishable merchandise, ever-changing consumer tastes, and a wide range of other variables squeezing profit margins. The chains and individual restaurants that understand their customers, supply networks, and operations best stand to get a leg up on their competitors.
For that reason, it’s an industry ripe for the insights delivered by advanced data analytics. But most operators aren’t able to take on the considerable expense of finding and hiring scarce data experts or investing in a data processing infrastructure.
Enter Oracle Hospitality Data Science Cloud Services, a suite of subscription services that food and beverage providers can use to analyze sales, guest, inventory, staff, marketing, and other data to boost their top and bottom lines. The first two services in the cloud software suite—Data Science for Menu Recommendations and Data Science for Adaptive Forecasts—will be available worldwide to customers of Oracle Hospitality’s Simphony Cloud Service point-of-sale platform as well as its on-premises RES 3700 POS software.
The Menu Recommendations service mines guest transaction data contained in Simphony or RES systems to deliver upsell recommendations to terminals used by cashiers and wait staff at quick-service and table-service restaurants. Those food and beverage recommendations, which update dynamically during the ordering process, are tailored to each restaurant’s location, the time of day, and past guest behaviors, says Saras Yagnavajhala, Oracle Hospitality director of cloud strategy and solution management. Restaurants can also feed those recommendations into a central data warehouse or third-party systems to inform promotions and special offers, Yagnavajhala says.
The data analysis will suggest up to five recommendations—wine pairings, complementary appetizers, special sauces, and so on—based on each guest’s specific order. “It's very prescriptive,” she says. “It's taking the guesswork out from the server.”
Most franchisees are stuck in order-taking mode, the mechanics of moving from one customer to the next. “This is where the science comes in, where we learn from locations that do well and apply those learnings to other underperforming locations to enhance the order value and customer satisfaction,” Yagnavajhala says “This service is self-learning all the time—as updated data flows in, it's learning and adjusting its recommendations.”
Adaptive Forecasts
Oracle Hospitality’s other new data science service, Adaptive Forecasts, is designed to help food and beverage providers predict their stock and labor needs. The service creates granular forecasts by item, location, time of day, and day of the week, factoring in the weather, local events, seasonality, and customer demographics. It even takes into account how a restaurant’s Net Promoter score (a measure of how likely customers are to recommend the establishment to others) is trending. The service uses machine learning to quickly understand the impact of various external factors on demand.
Such forecasting, conducted centrally but implemented location by location, helps restaurant managers maintain appropriate inventory and staffing levels, minimizing waste, lowering labor costs, and improving guest experiences. Labor and inventory costs alone already gobble up more than 50% of restaurant revenues, according to a survey last year of more than 200 independent operators and chains conducted by Oracle and food industry consultancy Technomic.
Yagnavajhala estimates that customers can realize a short-term 3% to 5% increase in revenue by using Menu Recommendations while improving customer satisfaction. Adaptive Forecasts, she says, can reduce labor and food costs by as much as 10% to 15%.
Data Science Dream Team
One key attribute of the Data Science services is that they give customers access to leading analytics experts and capabilities at a small fraction of the cost required to hire data scientists and build that competency internally.
The way a typical customer engagement will work, data and hospitality-industry experts on Oracle’s professional services team will initially work with a restaurant company’s operations or marketing team to discuss business process and change management to maximize the benefits from the Data Science results. They then will work with the customer’s IT teams to define data inputs and outputs to operationalize the insights.
If the results are being hooked into one of Oracle’s POS systems, the professional services team will work within the application’s extensibility framework to personalize the interface workflow and guide the customer on best practices. The Oracle team also works with the customer on how to roll out the system to different locations.
Once data is loaded into the application’s “science engine,” thresholds and configuration parameters are tuned based on a customer’s unique data characteristics, and results are quickly made available via reports and recommendations, Yagnavajhala says.
Customers also get access to some of the most accomplished data scientists in the world, and those scientists draw on the expertise of a separate Oracle Labs team that specializes in machine learning and data mining.
“Every hospitality professional I meet loves data—they love their KPIs and being able to check their phones to see how sales are doing,” says Laura Calin, Oracle Hospitality vice president of product strategy. “What they don’t necessarily want to do is commit people, time, and money to data mining and analysis, which then needs to be interpreted and fed into the POS before it can deliver any return. Oracle has the expert analysts and the data processing power our customers need, without them having to invest in the latest machine learning technologies themselves.”
Some restaurants already are mining data on social media and reviews sites to gauge customer sentiment, but they stand to gain many more insights by analyzing their own transaction data, Yagnavajhala says.
“With servers who are doing a great job, earning good tips, is it the location itself that has a good culture around service or is it the individual server?” she says. “This kind of data analysis will allow our customers to get more proactive rather than have to wait for the customer reviews to show up online. With prescriptive recommendations, Data Science can drive service consistency across locations.”
Rob Preston is editorial director in Oracle’s Content Central organization.
The preceding is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle's products remains at the sole discretion of Oracle.
