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CHAPTER 18. DETERMINING SALES FORECASTS. Importance 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. What is FORECASTING ?.

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Chapter 18



Importance of forecasting sales
Importance 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

What is forecasting

  • Forecasts of future sales are normally based on your sales history.

  • A sales forecastpredicts the # of guests you will serve and the revenues they will generate in a given future time period.

Sales vs volume

  • SALES =




Sales history

  • Sales history is the systematic recording of all sales achieved during a pre-determined time period. Sales histories can be created to record revenue, guests served, or both.

  • Sales to dateis the cumulative total of sales reported in the unit.

Sales history1
Sales History

  • 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. Ex: (6+9+18 =33/3)

  • Fixed average is an average in which you determine a specific time period. Ex: 14 days in a month

  • Rolling average is the average amount of sales or volume over a changing time period. Ex: examining only 7 days prior for a bar

Sales history2
Sales History

  • Record both revenue and guest counts

  • Compute averagesales per guest, a term also known as check average

Total Sales

Number of Guests Served = Average Sales per Guest

Average sales per guest
Average Sales per guest

Tues Total Sales: $1,826.27

Total Guests = 79

Avg. Sales per Guest=



Total Sales

# of Guests Served

= AvgSales per Guest

Maintaining sales histories
Maintaining Sales Histories

  • Sales history may consist of :

    • revenue, number of guests served, and average sales per guest.

    • the 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-through vs. counter sales).

  • In most cases, your sales histories should be kept for a period of at least two years.

Chapter 19

Chapter 19

Managing the Cost of Food

Menu item forecasting
Menu item Forecasting

  • How many servings of each item should we produce?

  • You don’t want to run out

  • You don’t want to make too much.

  • Menu item forecasting addresses the questions:

    • “How many people will I serve today?”

    • “What will they order?”

Menu item forecasting1
Menu Item Forecasting

  • Popularity index is defined as the percentage of total guests choosing a given menu item from a list of alternatives.

Popularity Index =Total Number of a Specific Menu Item Sold

Total Number of All Menu Items Sold

Chpt 19 fig 19 1 menu item 5 day sales history
Chpt 19: Fig 19.1Menu Item 5 day Sales History

Forecasting item sales
Forecasting Item Sales

Use the previous table to follow the formula:

Step 1:

Popularity Index = Total # of a specific menu item sold

(= %) Total # of all menu items sold

Step 2:

Take the Popularity index in decimal form and x by the guest forecast to come up with the predicted # to be sold.

400 x popularity index = predicted # to be sold.

Factors that influence predicted to be sold
Factors that influence Predicted # to be sold

  • Competition

  • Weather

  • Special Events in your area

  • Facility Occupancy (hospitals, dorms, hotels, etc.)

  • Your own promotions

  • Quality of service

  • Operational consistency

    These & factors affect sales volume, make guest count prediction very difficult.

Forecasting summary
Forecasting Summary




Failure Potential

Answer Questions

  • Knowledge of potential price changes, new competitors, facility renovations and improved selling programs = factors to predicting future sales.

  • Must develop, monitor, daily, a sales history report appropriate for your operation.

  • With out accurate data, control systems, are very likely to fail.

  • Help you answer: “How many people are coming tomorrow?, “How much is each person likely to spend?