chapter 18 determining sales forecasts. importance of forecasting sales “how many guests will i...
TRANSCRIPT
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=COVERS
REVENUE
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 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
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 19.1Menu Item Sales History
Date: 7/27/11
Menu Items Sold
Menu Item
Mon Tues Wed Thurs Fri Total Week’s Average
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 X
Forecasting Item Sales
Menu Item
Guest Forecast
Popularity Index
Predicted # to be sold
Roast Chicken
300
Roast Pork 300
Roast Beef 300
TotalUse 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.
300 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 consistencyThese & factors affect sales volume, make guest count
prediction very difficult.
Standardized recipes
The standardized recipe controls both the quantity and quality of what the kitchen will produce.
It consists of the procedures to be used in preparing and serving each of your menu items.
Standardized Recipes
Good standardized recipes contain the following:
1. Menu item name
2. Total yield (number of servings)
3. Portion size
4. Ingredient list
5. Preparation/method section
6. Cooking time and temperature
7. Special instructions, if necessary
8. Recipe cost (optional)
Arguments AgainstStandardized Recipes
1. They take too long to use.
2. My people don't need recipes; they know how we do things here.
3. My chef refuses to reveal his or her secrets.
4. They take too long to write up.
5. We tried them but lost some, so we stopped using them.
6. They are too hard to read, or many of my people cannot read English.
Reasons for incorporatingStandardized Recipes
1. Accurate purchasing
2. Dietary concerns are addressed – ingredients identified
3. Accuracy in menu laws – ingredients identified
4. Matching food used to cash sales
5. Accurate recipe costing and menu pricing
6. New employees can be better trained
7. Computerization of a foodservice operation depends on them
Adjusting Recipes
1. Factor Method
2. Percentage Technique
Factor Method
Recipe conversion factor: Yield Desired = Conversion Factor
Current Yield
Ex: If you our current recipe makes 50 portions, and the # of portions we wish to make is 125, the formula is
______ =
Determine the conversion factors.
Determine the new amount by x the factor by the original amount.
Ingredient
Original Amount
Conversion Factor
New Amount
A 4 lb x =
B 1 qt x =
C 1 ½ T x =
The % method
Deals with recipe weight, rather than with a conversion factor.
If you have a recipe that weighs 10 lbs 8 oz = ______ oz
If the portion size is 4 oz what is the recipe yeild? ______
If you want your kitchen to prepare 75 servings how much total weight will you need? _____________
Percentage Method
Factor % Formula:
Step 1: Ingredient Weight / Total Recipe Weight = % of Total
Step 2: % of Total × Total Amount Required = New Recipe Amount
Ingredient
Original Amount
Oz. % of Total
Total Amount Required
%o of Total
New Recipe Amount
A 6 lb 8 oz 300 oz
B 12 oz 300 oz
C 1 lb 300 oz
D 2 lb 4 oz 300 oz
Total 10 lb 8 oz
300 oz
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?