CHAPTER 18

1. CHAPTER 18 DETERMINING SALES FORECASTS

2. 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

3. What is FORECASTING? • Forecasts of future sales are normally based on your sales history. • A sales forecastpredicts the # of guests you will serve and the revenues they will generate in a given future time period.

4. SALES VS VOLUME • SALES = • SALES VOLUME= COVERS REVENUE

5. 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 dateis the cumulative total of sales reported in the unit.

6. 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

7. Sales History • Record both revenue and guest counts • Compute averagesales per guest, a term also known as check average Total Sales Number of Guests Served = Average Sales per Guest

8. Average Sales per guest Tues Total Sales: $1,826.27 Total Guests = 79 Avg. Sales per Guest= $23.12 Formula Total Sales #of Guests Served = AvgSales per Guest

9. 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.

10. Chapter 19 Managing the Cost of Food

11. 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?”

12. 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

13. Chpt 19: Fig 19.1Menu Item 5 day Sales History

14. Forecasting Item Sales 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.

15. 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.

16. 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.

17. 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)

18. Arguments AgainstStandardized 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.

19. Reasons for incorporatingStandardized 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

20. Adjusting Recipes • Factor Method • Percentage Technique

21. 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.

22. 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? _____________

23. Percentage Method Factor % Formula: Step 1: Ingredient Weight / Total Recipe Weight = % of Total Step 2: % of Total × Total Amount Required = New Recipe Amount

24. 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?