CHAPTER 18
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Transcript of CHAPTER 18
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 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 RESTUARANTSales Period
Date
Daily Sales
Sales to Date
Mon 1/1 $851.90 $851.90Tues ½ $974.37 $1896.27Wed 1/3 $1,004.
22$2,830.49
Thurs ¼ $976.01 $3,806.50Fri 1/5 $856.54 $4,663.045 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 SalesNumber of Guests Served = Average Sales per Guest
Average Sales per guestTues Total Sales:
$1,826.27Total Guests = 79Avg. Sales per
Guest=$23.12
FormulaTotal Sales
# of Guests Served = Avg 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.
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 5 day 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 SalesMenu Item
Guest Forecast
Popularity Index %
Predicted # to be sold
Roast Chicken
400 .243 97.2
Roast Pork 400 .382 152.8Roast Beef 400 .375 150Total 100% 400Use 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.
Popularity Index %
Predicted # to be Sold
400
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 recipesThe 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
Factor MethodRecipe conversion factor: Yield Desired = Conversion Factor
Current YieldEx: 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
oz300 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?