Creating Sales Forecasts

Chapter 2Creating Sales ForecastsMain IdeasImportance of Forecasting SalesSales HistoriesMaintaining Sales HistoriesSales VariancesPredicting Future SalesTechnology ToolsImportance of Forecasting Sales “How many guests will I serve today?” – “This week?” – “This year?” Guests will provide the revenue from which the operator will pay basic operating expenses and create a profit.Forecasts of future sales are normally based on your sales history.A Sales Forecast predicts the number of guests you will serve and the revenues they will generate in a given future time period.Importance of Forecasting Sales Determine your actual sales for a current time period by using a point of sales (POS) system. Distinction between sales (revenue) and sales volume (covers)Sales may be a blend of cash and non- cash. With accurate sales records, a sales history can be developed.Advantages of Accurate Sales Forecasts Accurate revenue estimatesImproved ability to predict expensesGreater efficiency in scheduling needed workersGreater efficiency in scheduling menu item production schedulesBetter accuracy in purchasing the correct amount of food for immediate useAdvantages of Accurate Sales Forecasts Improved ability to maintain proper levels of food inventoriesImproved budgeting abilityLower selling prices for guests because of increased operational efficiencies Increased dollars available for current facility maintenance and future growth Increased profit levels and stockholder value Sales HistorySales history is the systematic recording of all sales achieved during a pre- determined reporting (accounting) period. Sales histories can be created to record revenue, guests served, or both.Sales to date is the cumulative total of sales reported in the unit.Sales HistoryAn average or mean is defined as the value arrived at by adding the quantities in a series and dividing the sum of the quantities by the number of items in the series.Fixed average is an average in which you determine a specific time period. Rolling average is the average amount of sales or volume over a defined but changing time period.Fixed averageRolling averageRolling averageSales HistoryGuest count is the term used in the hospitality industry to indicate the number of people you have served.Examples of operations that are often more interested in guest count than in daily revenue include schools, colleges, health care facilities, and those food service facilities found on military bases. Sales HistorySome operations record both revenue and guest counts.Compute average sales per guest, a term also known as check average.Sales HistoryModern POS systems record:The amount of revenue generated in a selected time periodThe number of guests servedThe average sales per guestSales HistoryA weighted average is an average that weights the number of guests with how much they spend in a given time period.The weighted average sales per guest for 2 days is as follows:Maintaining Sales HistoriesSales history may consist of:Revenue, number of guests served, and average sales per guestThe number of a particular menu item served, the number of guests served in a specific meal or time period, or the method of meal delivery (for example, drive-thru vs. counter sales.)In most cases sales histories should be kept for a period of at least two years.Sales Variances Sales variances are changes from previously experienced sales levelsThe variance is determined by subtracting sales last year from sales this yearSales VariancesPercentage variance indicates the percentage change in sales from one time period to the next.Predicting Future SalesManagers use sales histories to predict, or forecast, their future revenues, guest counts, or average sales per guest levels.Predicting Future SalesRevenue forecast is calculated using the following formula:Sales Last Year + (Sales Last Year x % Increase Estimate)=Revenue ForecastOrSales Last Year x (1+% Increase Estimate)=Revenue ForecastPredicting Future SalesBy using the same techniques employed in estimating increases in sales, managers can estimate increases or decreases in the number of guests served.Predicting Future SalesThe guest count forecast is determined as follows:Guest Count Last Year + (Guest Count Last Year x % Increase Estimate) = Guest Count ForecastOrGuests Count Last Year x (1.00 + % Increase Estimate) = Guest Count ForecastPredicting Future SalesAverage sales per guest (check average) is simply the average amount of money a guest spends during a visit.Using data taken from the sales history, the following formula is utilized to forecast future Sales per Guest:Predicting Future SalesAn average sales per guest forecast can also be obtained by dividing the revenue forecast by the guest count forecast.Predicting Future SalesWhen used alone, sales histories are not sufficient to accurately predict future sales.Managers must also consider potential price changes, new competitors, facility renovations, improved selling programs, and other factors.Undertaking green initiatives can help increase guest counts.Technology ToolsThe importance of accurate sales histories for use in forecasting future sales is unquestionable. A modern POS system can be invaluable in this effort. Technology ToolsMany systems today can be utilized to do the following: Track sales by guest count or by dateMonitor cash vs. credit salesMaintain products sold histories and check average dataCompare actual sales to prior-period salesTechnology ToolsMany systems today can be utilized to do the following: (cont.) Maintain rolling sales averagesForecast future sales in incrementsMaintain actual sales to forecasted sales variance reportsMaintain reservations systemsTechnology ToolsReservations software makes it possible for operators to reward repeat guests by developing their own “frequent dining” programs, similar to a hotel or airlines’ frequent-traveler programs.Customer complaints can be tracked and, if desired, coupons to compensate guests for difficulties can be printed and distributed.Technology ToolsFor those operations that rely on reservations to control bookings, software of this type is available to instantly identify repeat guests, giving the operator a display screen that can include such information as frequency of visit, purchase preferences, and total dollars spent in the operation.