chapter 18 determining sales forecasts. importance of forecasting sales “how many guests will i...

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?