Download presentation
Presentation is loading. Please wait.
Published byRafe Morris Miles Modified over 8 years ago
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 forecast predicts 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=
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 date is the cumulative total of sales reported in the unit. RAE’S RESTUARANT Sales Period DateDaily Sales Sales to Date Mon1/1$851.90 Tues½$974.37$1896.27 Wed1/3$1,004.22$2,830.49 Thurs¼$976.01$3,806.50 Fri1/5$856.54$4,663.04 5 day Total $4,663.04
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 average sales 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 = Avg Sales 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 Popularity Index =Total Number of a Specific Menu Item Sold Total Number of All Menu Items Sold
13
Chpt 19: Fig 19.1 Menu Item 5 day Sales History Date: 7/27/11 Menu Items Sold Menu Item MonTuesWedThursFriTotalWeek’s Average Roast Chicken 7072618577365 Roast Pork 110108144109102573 Roast Beef 10014095121106562 Total2803203003152851500X
14
Forecasting Item Sales Menu ItemGuest Forecast Popularity Index % Predicted # to be sold Roast Chicken400.24397.2 Roast Pork400.382152.8 Roast Beef400.375150 Total100%400 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. Popularity Index % Predicted # to be Sold 400
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
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?
Similar presentations
© 2024 SlidePlayer.com. Inc.
All rights reserved.