Creating Sales Forecasts

Perhaps the most important business quote….

"You lose profits one penny at a time" 

Importance of Forecasting Sales

  • Forecasts of future sales are typically based on an operation’s sales history

  • A Sales Forecast predicts the number of guests that will be served and the revenues that will be generated in a given future time period.

 

Forecasting future sales addresses the

important operational questions like:

"How many guests will I serve?"

“What will they order?”

 

Advantages of Accurate Sales Forecasts

  • Accurate revenue estimates

  • Improved ability to predict expenses

  • Greater efficiency in scheduling needed workers

  • Greater efficiency in scheduling menu item production schedules

  • Better accuracy in purchasing the correct amount of food for immediate use

  • Improved ability to maintain proper levels of food inventories

  • Improved budgeting ability

  • Lower selling prices for guests because of increased operational efficiencies

  • Increased dollars available for current facility maintenance and future growth

  • Increased profit levels and  shareholder value

 

Sales Histories

  • A sales 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

  • An 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.

  • A fixed average is an average for a specific (fixed) time period.

  • A rolling average is the average amount of sales or volume over a changing time period.

 

  • Some operations record both revenue and guest counts to then compute the “average sales per guest,” or “check average.”

 

Total Sales/Number of Guests Served=Average Sales per Guest

 

  • A weighted average weighs the number of guests served in different time periods with how much they spend in those same time periods.

 

The weighted average sales per guest for 2 days is as:

 

(Day 1 Sales + Day 2 Sales)/(Day 1 Guests + Day 2 Guests)

 

Maintaining Sales Histories

  • Sales histories may consist of:

    • Revenue

    • Number of guests served

    • Average sales per guest

    • Specific menu items served

    • Guests served in a specific meal- or time-period

    • Method of meal delivery

 

Sales Variances

  • Sales variances are changes from previously experienced sales levels

    • Absolute Variance

      • Unit difference between periods

      • Actual (number) difference (E.g., $, covers, etc.)

 

Sales this period- Sales last period= Variance

 

  • Percentage variance indicates the percentage change in sales from one time period to the next.

(Sales this period- Sales last period)/Sales last period = Percentage Variance

 

Predicting Future Sales

  • A revenue forecast is calculated using the following formula:

 

Sales last year x (1 + % increase estimate) = Revenue Forecast

 

  • The guest count forecast is determined as follows:

Guest Count Last Year x (1.00 +% Increase Estimate)

 

When calculating a YTD or multiple period average,

DO NOT take an average of individual averages!!

 

When 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,

    • Upcoming events, etc.

 

Important Formulas

  • Total Sales/Number of Guests Served = Average Sales Per Guest

  • Sales This Year - Sales Last Year = Variance

  • (Sales This Year - Sales Last Year)/Sales Last Year = Percent Variance

  • Variance/Sales Last Year = Percent Variance

  • (Sales This Year/Sales Last Year) - 1 = Percent Variance

  • Sales Last Year + (Sales Last Year x % Increase Estimate) = Revenue Forecast

  • Sales Last Year x (1 + % Increase Estimate) = Revenue Forecast

  • Guest Count Last Year + (Guest Count Last Year x % Increase Estimate) = Guest Count Forecast

  • Guest Count Last Year x (1 + % Increase Estimate) = Guest Count Forecast

  • Last Year's Average Sales Per Guest + Estimated Increase in Average Sales Per Guest = Average Sales Per Guest Forecast

  • Revenue Forecast/Guest Count Forecast = Average Sales Per Guest Forecast

  • Sales Last Year x (1 + % Increase Estimate) = Revenue Forecast

  • Guest Count Last Year + (Guest Count Last Year x % Increase Estimate) = Guest Count Forecast

  • Guest Count Last Year x (1 + % Increase Estimate) = Guest Count Forecast

  • Last Year's Average Sales Per Guest + Estimated Increase in Average Sales Per Guest = Average Sales Per Guest Forecast

  • Revenue Forecast/Guest Count Forecast = Average Sales Per Guest Forecast

 

 

Inflation decreases the purchasing power of the dollar