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?
Forecasts of future sales
are normally based on
your sales history.
A sales forecast
predicts the # of guests
you will serve and the
revenues they will
generate in a given
future time period.
SALES VS VOLUME

SALES =

SALES VOLUME=
SALES HISTORY


Sales history is the
systematic recording of
all sales achieved
during a predetermined time
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.
RAE’S RESTUARANT
Sales
Period
Date Daily
Sales
Sales to Date
Mon
1/1
$851.90
$851.90
Tues
½
$974.37
$1896.27
Wed
1/3
$1,004.22 $2,830.49
Thurs
¼
$976.01
$3,806.50
Fri
1/5
$856.54
$4,663.04
5 day
Total
$4,663.04
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 History


Record both revenue
and guest counts
Compute average
sales per guest, a
term also known as
check average
Total Sales
Number of Guests Served = Average Sales per Guest
Average Sales per guest
Formula
Total Sales
# of Guests Served
= Avg Sales per Guest
Tues Total Sales:
$1,826.27
Total Guests = 79
Avg. Sales per Guest=
$23.12
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
Managing the Cost of Food
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 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
Date:
7/27/11
Menu Items Sold
Menu
Item
Mon
Tues
Wed
Thurs
Fri
Total
Roast
Chicken
70
72
61
85
77
365
Roast
Pork
110
108
144
109
102
573
Roast
Beef
100
140
95
121
106
562
Total
280
320
300
315
285
1500
Week’s
Average
X
Forecasting Item Sales
Menu Item
Guest
Forecast
Popularity
Index %
Predicted # to
be Sold
sold
Roast Chicken
400
.243
97.2
Roast Pork
400
.382
152.8
Roast Beef
400
.375
150
100%
400
Total
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







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
Empower

Develop
Record
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?