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Restaurant sales forecasting can be an incredibly complex and error-prone process, especially with the number of other duties on a manager’s list. Let’s face it — restaurant managers are busy people, and many often lack the time or experience to fully understand the intricacies of forecasting, let alone tweak the statistical models to fit their stores.
That’s a problem, because poor forecasting ultimately results in poor business performance. Have you ever been to a restaurant and had to wait for service even though there were a bunch of open tables? Or have you ever been disappointed to learn that an item on the menu was sold out?
These issues are often due to flawed labor and sales forecasts, and they can hurt your business in the long run. From product ordering to waste management and staffing within compliance, precision forecasting is the key to profitability.
Intelligent Solutions Automate the Forecasting Process
This deep need for better forecasts has driven remarkable innovations in intelligent restaurant technology. Thanks to developments in back-office platforms, operators now have centralized forecasting capabilities, and can generate forecasts for multiple stores in order to optimize profitability.
These forecasting solutions are statistical in nature and based on mathematical models and historical data points about the restaurant. They can learn the seasonal rhythm of the store and spot changes in trends by analyzing new data.
Managers now have the ability to automatically generate forecasts based on mathematical algorithms instead of problematic “gut-instinct” notions. And through machine learning, these solutions track the forecast’s alignment with actual performance and draw the manager’s attention to areas of significant variance.
Unique Manager Insight will Always be Needed
But operators can never truly remove the restaurant manager from the forecasting process. Managers are the people who know the unique nooks and crannies of the business. And if they’re inexperienced, then operators need to get them up to speed — and fast.
If your restaurant’s finance department is running the forecasting for the business, they won’t know that there’s construction outside one of the stores, so that expected decrease in foot traffic won’t be factored into the forecast.
Inflexible statistical models may work on an average day at your restaurant, but they’re less reliable on the outlier days — the days that really matter. Without the feedback into the model from a human with boots on the ground, you’ll still have an inaccurate forecast.
For example, managers know the calendar of local business events and other relevant local situations that are likely to impact your store operations or product demand. Restaurant managers have the ability to adapt to dynamic change often times quicker than a machine. Forecasting today is no different. Managers are the ones who can adjust the the events that contributed to the significant variance to train the algorithm for the future
That’s why it is crucial to partner the manager and the machine. Both bring something important to the forecasting process. The machine brings raw number-crunching power. The manager brings contextual awareness and human intuition. And both of them need to play their roles to efficiently produce the forecasts that effectively predict the future for your business.
So, what’s the perfect equilibrium? What’s the secret sauce? Operators need to minimize human error through machine learning while preserving the field knowledge of managers. You do that through a structured ability to add events to the forecast based on predetermined fields configured with corporate guidance.
This isn’t to say that a business will fail without proper forecasting methods. But if your restaurant is achieving $5,500 in sales on an average lunch shift but you’re only staffing for $4,000, eventually your restaurant will do a $4,000 lunch.
The partnership between manager and intelligent forecasting platform will make it easier for your business to meet financial goals, deliver great customer experiences and run a consistent operation.