DETERMINING SALES FORECASTS 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 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

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.

Managing the Cost of Food 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 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 95 121 106 562 280 320 300 315 285 1500 X

Forecasting Item Sales Menu Item Guest Forecast Popularity Index Predicted # to be sold Roast Chicken 300 Roast Pork Roast Beef 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. 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 consistency These & 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: Menu item name Total yield (number of servings) Portion size Ingredient list Preparation/method section Cooking time and temperature Special instructions, if necessary Recipe cost (optional)

Arguments Against Standardized Recipes They take too long to use. My people don't need recipes; they know how we do things here. My chef refuses to reveal his or her secrets. They take too long to write up. We tried them but lost some, so we stopped using them. They are too hard to read, or many of my people cannot read English.

Reasons for incorporating Standardized Recipes Accurate purchasing Dietary concerns are addressed – ingredients identified Accuracy in menu laws – ingredients identified Matching food used to cash sales Accurate recipe costing and menu pricing New employees can be better trained Computerization of a foodservice operation depends on them

Adjusting Recipes Factor Method 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 C 1 ½ T

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: 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 C 1 lb D 2 lb 4 oz Total 10 lb 8 oz Factor % Formula: Step 1: Ingredient Weight / Total Recipe Weight = % of Total Step 2: % of Total × Total Amount Required = New Recipe Amount

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?