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=

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$ Tues½$974.37$ Wed1/3$1,004.22$2, Thurs¼$976.01$3, Fri1/5$856.54$4, 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: ( =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

Average Sales per guest Tues Total Sales: $1, Total Guests = 79 Avg. Sales per Guest= $23.12 Formula Total 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.

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 Popularity Index =Total Number of a Specific Menu Item Sold Total Number of All Menu Items Sold

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 Roast Pork Roast Beef Total X

Forecasting Item Sales Menu ItemGuest Forecast Popularity Index % Predicted # to be sold Roast Chicken Roast Pork Roast Beef 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

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.

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?