In an increasingly complex industry, restaurants stop gut-based sales forecasting, partnering manager and machine for more accurate projections.

Sponsored by HotSchedules.

The restaurant business is experiencing rapid and exciting growth in many areas—design, cooking technology, consumer insights, delivery—yet there is one aspect of the industry that has room for drastic improvement. Sales forecasting is an oft-neglected part of successful restaurant operations.

While many restaurateurs strive to stay abreast of the latest advancements in ingredients and technology, forecasting often falls by the wayside. Managers typically rely on gut instinct and weekly monitoring of a store’s P&L to predict sales. For many years, that was enough—and may still be for operations that are immune to the complexities of consumer preferences, off-premise ordering, and rising wages—but those scenarios are few and far between. Because restaurant sales forecasting is a complex process, gut instinct simply doesn’t work when inexperienced managers are at the helm. In addition, an increase in turnover means the store-specific knowledge a manager accumulates over time leaves when they do.  

Even experienced managers can struggle with sales forecasting, which is inherently prone to error considering the numerous factors that influence predictions. Not only are sales volumes likely to change based on trends, but certain promotions, holidays, and even weather can throw these numbers off. When managers are in constant “reaction mode” due to a lack of predictability in the business, it takes time away from more important tasks like hiring, training, operational control, and guest satisfaction.

Given the challenges associated with restaurant sales forecasting, it’s no surprise that it’s often overlooked as a valuable tool that can actually make operations run smoother. Forecasting technology helps decrease forecast variance percentage as well as overall food, paper goods, waste, and labor costs. For example, Clarifi, a cloud-based software platform by HotSchedules, automatically generates a forecast for management to build a schedule and place orders, but it also allows the manager to use his or her contextual knowledge— inputting events and other personal knowledge into the forecast. “Different events have different impacts and they are difficult to track across months or years,” says HotSchedules’ Chief Technology Officer Brian Gaffney. “When regular forecasts are generated for the manager they are more likely to recognize the outliers and make small adjustments based on the nuances that may not be accounted for in the historical data.”

Sales forecasting can even help with retention: when managers make their numbers, they are more likely to stay with the company. Store-specific knowledge is retained and employees tend to have more predictability in their schedules and higher sales—which leads to increased tip averages and longer tenures.

Clarifi incorporates a set of pre-configured fields to bring more structure and control to manager inputs—a benefit for corporations and chains who need oversight and compliance from their stores. Using machine learning, the system continues to learn from these inputs to generate best-fit forecasts in the future.

“We’re not suggesting a restaurant is going to go out of business because they don’t forecast,” says HotSchedules Co-Founder and Chief Customer Officer David Cantu. “But it’s going to be a whole lot easier to meet financial goals, deliver on great experiences and run a consistent operation when managers trust a platform like Clarifi to generate a forecast for them. It’s a partnership between manager and machine.”

By Davina van Buren

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