Restaurant operators make dozens of decisions every day based on one big question: How busy are we going to be?
The answer affects nearly everything. How many employees should be scheduled? How much product should be ordered? How much prep needs to happen before the doors open? What should the restaurant expect to spend, and will projected sales support those costs?
Restaurant sales forecasting helps operators answer those questions with more than a gut feeling.
By using historical sales data, recent performance, seasonality, local events, promotions, and other factors that influence demand, restaurants can build more informed expectations for future sales. While no forecast will predict revenue perfectly, a consistent forecasting process can help operators make smarter purchasing, staffing, budgeting, and operational decisions.
What Is Restaurant Sales Forecasting?
Restaurant sales forecasting is the process of estimating how much revenue a restaurant is likely to generate during a future period. Forecasts can be created for a single shift, day, week, month, quarter, or even an entire year depending on how the information will be used.
At its simplest, forecasting may involve reviewing historical sales and using those results as a baseline. More advanced forecasts account for factors such as:
- Day of the week
- Daypart
- Seasonal demand
- Holidays
- Local events
- Weather
- Promotions and limited-time offers
- Menu changes
- Changes in operating hours
- Recent sales trends
The goal isn’t to predict sales down to the dollar. It’s to develop a realistic expectation for demand so the restaurant can prepare accordingly.
For multi-location operators, forecasting can also help identify differences between locations. A restaurant near a college campus may experience a very different September sales pattern than a suburban location, even when both operate under the same brand.
Why Sales Forecasting Matters
A reliable sales forecast gives restaurant operators a foundation for making better operational decisions before the shift begins.
- Labor planning: Scheduling too many employees against expected sales can push labor costs higher. Scheduling too few can leave employees overwhelmed and negatively affect speed of service and the guest experience.
- Purchasing and inventory: Forecasting anticipated demand helps operators determine how much product they are likely to need, reducing the risk of both shortages and unnecessary inventory.
- Food cost management: Better visibility into expected sales and product needs can make it easier to align purchasing with demand and reduce excess inventory that could eventually become waste.
- Cash flow and budgeting: Weekly and monthly sales forecasts provide a clearer picture of expected revenue, giving operators more information for upcoming expenses and financial planning.
- Operational preparation: Knowing that Friday dinner is expected to outperform a typical Friday gives managers time to adjust prep, inventory, and staffing instead of reacting once the rush has already started.
Forecasting becomes especially important when margins are tight. Small differences between expected and actual sales can affect labor percentages, purchasing needs, food costs, and profitability.
Restaurant Sales Forecast Formulas
There isn’t one restaurant sales forecast formula that works for every operation. The right calculation depends on the amount of historical data available and how detailed the forecast needs to be.
One straightforward approach is:
Forecasted Sales = Historical Sales × Expected Change
For example, if a restaurant generated $20,000 in sales during the same week last year and expects sales to increase 5%:
$20,000 × 1.05 = $21,000 in forecasted sales
Restaurants can also use average historical sales:
Average Sales = Total Sales During Comparable Periods ÷ Number of Periods
If the previous four comparable Tuesdays generated $4,800, $5,100, $4,900, and $5,200:
($4,800 + $5,100 + $4,900 + $5,200) ÷ 4 = $5,000
That gives the restaurant a $5,000 baseline before adjustments are made for factors such as weather, holidays, promotions, or local events.
Operators should also track forecast accuracy after the period ends:
Forecast Variance % = (Actual Sales − Forecasted Sales) ÷ Forecasted Sales × 100
If forecasted sales were $10,000 and actual sales were $10,500:
($10,500 − $10,000) ÷ $10,000 × 100 = 5%
Tracking variance over time is important because forecasting should be an ongoing process. When forecasts consistently miss in the same direction, operators can use that information to improve future assumptions.
Sales Forecasting Methods
Restaurants can approach forecasting in several ways depending on their available data, operating model, and forecasting needs.
- Historical sales forecasting uses previous sales results as the baseline for future projections. Operators might compare last week’s sales, the previous four comparable weekdays, or the same period from the prior year.
- Moving average forecasting calculates average sales across a defined number of recent periods. This can help smooth out unusually high or low sales days, although operators should be careful when moving from one season or demand pattern into another.
- Year-over-year forecasting compares upcoming periods with the same period from the previous year. This can be particularly useful when accounting for seasonal patterns, holidays, school schedules, and recurring events.
- Daypart forecasting breaks projected sales into breakfast, lunch, dinner, late night, or other relevant periods. This provides managers with more actionable information for scheduling and prep than a single daily sales number.
- Event-based forecasting adjusts expected sales based on factors such as sporting events, concerts, conventions, school schedules, festivals, or other local demand drivers.
Many restaurants will benefit from combining several methods rather than relying exclusively on one. Recent sales can show what is happening now, while year-over-year data can provide context for what typically happens next.
How to Build Your Sales Forecast, Step by Step
Start by deciding what you are forecasting and how the information will be used. A weekly financial forecast may require a different level of detail than a shift-level forecast used to build the employee schedule.
1. Gather your historical sales data.
Pull comparable sales by location, day, and, when possible, daypart. Look beyond the previous few weeks when seasonality could make recent performance less representative.
2. Establish a baseline.
Calculate average sales across comparable periods or use the same period from the previous year as your starting point.
3. Review recent trends.
Determine whether sales have been consistently increasing or decreasing. A year-old number shouldn’t automatically become this year’s forecast without considering what has changed.
4. Identify upcoming demand drivers.
Review holidays, school schedules, sporting events, local events, weather expectations, promotions, limited-time offers, and changes to operating hours.
5. Adjust your baseline.
Use what you know about upcoming conditions to increase or decrease expected sales. Document significant adjustments so managers understand why the forecast changed.
6. Build operational plans around the forecast.
Use projected demand to inform scheduling, purchasing, inventory, production, and prep decisions.
7. Compare forecasted sales with actual results.
Once the period is over, calculate the variance. Determine what the forecast got right, where it missed, and what may have caused the difference.
8. Apply what you learned to the next forecast.
Forecasting becomes more useful when restaurants consistently measure and refine it. Over time, managers can identify recurring patterns and improve the assumptions behind future projections.
Seasonal Forecasting: 5 Traps to Avoid
As summer comes to an end and school comes back in session, adjustments to your sales forecast needs to happen in order to ensure your teams are operating at their optimum levels. Poor forecasting can lead to poor customer service, running out of product, and a higher stress work environment. Below are five traps that your management team should avoid as the Fall season begins and you build your sales forecast template.
You can’t get out of your summer sales mind-set.
As the summer time ends, continuing to use four to six-week sale averages for daily and weekly sales isn’t really relevant. Routines change for most people when the calendar changes from August to September which could cause shifts in daypart sales compared to the summer months. Shift from using just sales history from the past four/six weeks and reference the location’s actual history during the month of September. Track your daily/weekly actual sales to forecasted sales variances, target 5% to 7%. Any variance outside of this range generally starts to affect your operation’s performance.
You don’t have the appropriate calendars.
While the summer months may have been more open and free or jam packed with evening events, happy-hour shows, and more, the change of season also welcomes back a new routine. File a separate calendar that is tracking local events that will affect daily sales forecasts. Consider including events that like school events, school closures, sporting events, and Holidays that affect each of your locations. Another thing to add to your calendar? Time each week for you and your team to collect the tools needed to properly forecast.
Poor assumptions on holiday/special day events.
Manager and employee time off requests should be limited to ensure that the customer’s experience and speed of service is not impacted. Prepare for employee call-outs, have a backup plan in case of short staffing and reference your seasonal calendar so your scheduling is in line with possible increase in visitors during sporting events or holidays.
You don’t know your history.
Trying to forecast for the fall can be impossible without an archive or history of sales and daily averages for past years. Research your sales history for each day part and adjust your forecasts appropriately. For example, the dinner day part generally begins earlier and ends earlier than in the summer. Your own sales history is your best asset to adjust your sales forecasts. Trust your history and numbers, seasonality has a level of predictability that can be used to your advantage.
Value messages/LTO’s.
Fall is a popular time for limited time offers and promotions. Know and plan for your promotions in order to ensure your staff is prepared in a product and a labor standpoint. Additionally, talk to your team, and get their thoughts and suggestions as menus change and you work towards keeping your customers happy.
Set yourself up for success as the seasons shift. Use your history and your tracking tools to adjust your sales forecasts to keep your operations running at optimum levels! Plus, explore these free financial templates from TouchBistro.
Final Thoughts
Restaurant sales forecasting doesn’t eliminate uncertainty. It gives operators a better way to prepare for it.
The strongest forecasts combine historical performance with what is happening in the business right now. Sales history provides the baseline, while seasonality, events, promotions, weather, and changing customer routines provide the context.
Most importantly, don’t create a forecast and forget about it. Compare projections with actual sales, investigate meaningful variances, and use what you learn to make the next forecast better.
For independent restaurant operators, better forecasting can ultimately mean better control over labor, purchasing, inventory, and food costs. And when you’re working to protect already-tight margins, having a clearer idea of what’s coming can make a meaningful difference.
Frequently Asked Questions
How do you forecast restaurant sales?
Start with historical sales from comparable periods, such as the same weekday, week, month, or season. Establish a baseline and adjust it based on recent sales trends, seasonality, holidays, local events, promotions, weather, operating changes, and other factors that could influence demand. Afterward, compare actual sales with the forecast and use the variance to improve future projections.
What is the restaurant sales forecast formula?
A simple restaurant sales forecast formula is Forecasted Sales = Historical Sales × Expected Change. For example, if comparable historical sales were $10,000 and you expect a 5% increase, forecasted sales would be $10,500. Restaurants can also use averages across multiple comparable periods to establish a baseline before making adjustments.
Why is sales forecasting important for restaurants?
Sales forecasting helps restaurants anticipate demand and make more informed decisions about labor scheduling, purchasing, inventory, food preparation, budgeting, and cash flow. More accurate forecasts can help reduce the operational problems associated with being significantly over- or under-prepared for actual demand.
What is a good forecast accuracy for a restaurant?
There isn’t one forecast accuracy percentage that is appropriate for every restaurant. Accuracy can vary based on the restaurant concept, sales volatility, forecast period, seasonality, and unexpected factors such as weather or local events. Instead of focusing only on a universal benchmark, restaurants should consistently measure forecast variance and work to improve their own accuracy over time. A forecast that repeatedly misses in the same direction can be especially useful because it signals that the forecasting assumptions may need to be adjusted.
