Forecasting Sales

This chapter provides an overview of sales forecasting and discusses how to:

• Generate seasonality values.

• Generate projected sales.

• Add and revise projected sales.

Understanding Sales Forecasting

Percentage rent, or sales overage, is a significant component of revenue for all retail real estate companies and a significant expense for retail tenants. Use the sales forecasting tools to forecast sales amounts for future periods. You can use these estimated amounts to generate billings for the tenants, analyze historical trends, and predict future revenue and expenses.

The system provides the following programs for using sales forecasting:

• Seasonality Generation (R1547)

  The R1547 program creates the values that populate the Sales Seasonality table (F1547) that are used to calculate estimates for noncomparable leases.

• Seasonality Models (P1549)

  The P1549 program displays the order in which the seasonality model for estimating sales is determined.

• Seasonality Information (P15470)

  The P15470 program is used to revise generated seasonality values.

• Projected Sales Generation (R1542)

  The R1542 program projects monthly and annual sales. You use processing options to specify whether the system projects annual sales. For noncomparable leases, sales are projected based on the seasonality values. For comparable leases, sales are projected based on comparisons with prior actual sales amounts.

• Sales History Inquiry (P1541B)

  The P1541B displays a rolling 24-month cycle for both actual and estimated sales amounts. Actual sales amounts are retrieved from the F1541B table. Estimated sales amounts are retrieved from the F1542 table.

The flowchart provides a high-level view of the programs and tables required for sales forecasting:

Sales forecasting programs and tables

Generating Seasonality Values

This section provides an overview of seasonality generation and discusses how to:

• Run the Seasonality Generation Program.

• Set processing options for Seasonality Generation (R1547).

• Set processing options for Seasonality Models (P1549).

• Add buildings to seasonality models.

• Set processing options for Seasonality Information (P15470).

• Revise seasonality information.

Understanding Seasonality Generation

If a lease does not meet the conditions for comparable leases or there is not sufficient sales data to generate future sales estimates, you can define seasonality values to enable the system to create a sales forecast.

A lease is considered comparable if the values for the following fields do not change:

• The Urban Land Industry (ULI) Code (for example, the Major Merchandise code).

• Building.

• Unit.

• Area. (square footage)

• DBA.

If any of these conditions change or if insufficient sales data are available to use any of the forecasting methods, the lease is considered noncomparable

To create seasonality values and a default seasonality model, run the Seasonality Generation program (R1547) or create the seasonality values manually in the Seasonality Models program (P1549) and the Seasonality Information program (P15470). You can also to review and revise seasonality values generated by the R1547 program in the P1549 and P15470 programs

The Projected Sales Generation program (R1542) uses a seasonality model to select seasonality values. When forecasting sales, the system uses the model with the lowest line number whose minimum number of tenants is fewer than the number of tenants for whom the sales forecast is run. If none of the seasonality models meet the criteria, the system uses the default model that includes sales for the entire project or building.

The system calculates seasonality values by building and ULI or project and ULI. The system uses this formula to calculate seasonality values: Seasonality (month X) = (Sales (month X this year) × 100) ÷ total sales for current year

The system stores seasonality values in the Sales Seasonality table (F1547).

Forms Used to Generate Seasonality Values

Running the Seasonality Generation Program

Select Sales Forecasting (G152211), Seasonality Generation.

Set Processing Options for Seasonality Generation (R1547)

Processing options enable you to specify the default processing for programs and reports.

Process

Print

Exclusions

Setting Processing Options for Seasonality Models (P1549)

Processing options enable you to specify the default processing for programs and reports.

Process

Adding Buildings to Seasonality Models

Access the Seasonality Model Revisions form.

ULI Code (urban land institute code)	Enter a ULI code from UDC table 15/UL to identify the nature of a business or enterprise. The ULI code is a real estate trade organization that publishes sales, expenses, and other statistical information by types of Buildings, Developments, and Tenants.
Minimum # of Tenants (minimum number of tenants)	Enter the minimum number of tenants that are required in order to use the seasonality model to estimate sales when you run the Projected Sales Generation Program (R1542).

Setting Processing Options for Seasonality Information (P15470)

Processing options enable you to specify the default processing for programs and reports.

Process

Setting Up Seasonality Information

Access the Seasonality Revisions form.

Even though the system calculates seasonality values to four decimal places when you enter values manually, the program rounds only to the nearest hundredth. For example, even though the values might actually total 100.0001 percent, the program rounds the value to 100.00 percent.

Generating Projected Sales

This section provides overviews of projected sales and forecasting methods and forecasting sales for noncomparable leases, lists a prerequisite, and discusses how to:

• Run the Projected Sales Generation program.

• Set processing options for Projected Sales Generation (R1542).

Understanding Projected Sales

The Projected Sales Generation program (R1542) provides reliable data that supports sales forecasting for overage rents. The R1542 program estimates future sales based on a variety of calculation methods.

The JD Edwards EnterpriseOne Real Estate Management system provides seven forecasting methods for comparable and noncomparable leases. Regardless of the method you use, you must meet certain conditions. If a lease is considered noncomparable, you have to run the Seasonality Generation program (R1547) to generate the values required by the forecasting methods. Typically, sales data has to be available for a certain number of months.

The annual projection for a lease is the same as the amount for 12 months if the lease has 12 months of actual sales data. If the lease does not, it is considered noncomparable, in which case the system uses seasonality values to calculate the annual projection. The system uses the following calculation to determine seasonality values: (Monthly Sales ÷ Seasonality) ÷ Number of Months.

You can generate either a month-by-month detail report or a summary report. The detail report includes the calculations for each month of the year and indicates estimates with an asterisk (*). The summary report includes the rolling sales, year-to-date sales, and annualized sales. The summary report also includes sales per square foot and percent changes and indicates estimates with an asterisk (*).

Understanding Forecasting Methods and Forecasting Sales for Noncomparable Leases

This section provides an example of each of the seven forecasting methods, as well as forecasting for noncomparable leases.

Forecasting Method 1: Percent Increase of Rolling 12 Months Over Prior Rolling Months

The system calculates the percentage increase by comparing the rolling 12 months up to 2 months prior to the month for which sales are estimated, to the prior rolling 12 months.

This forecasting method uses this calculation:

Monthly Estimate = (Previous Year's Sales for Same Month × Current Rolling 12 months) ÷ Prior Rolling 12 Months.

Example

This table lists the results of the forecast calculation based on reported sales from October 2006 to September 2007:

By applying the forecast calculation from the previous table, determine at the sales estimate for November and December based on the sales figures for the same month in the previous year. The table also shows the percent increase in sales between the two time periods.

Note. For a lease to be comparable, 24 rolling months of sales must exist.

Forecasting Method 2: Lease Year-To-Date Increase Over Prior Year

The system calculates the percentage for all months based on a year-to-date increase over the previous year. The same percentage is applied to the remaining months. Leases must have at least 13 months of actual sales for the system to estimate sales. For example, if you want to estimate sales for November 2008, compare the time period from January through October 2007 with the time period from January through October 2008. The same percentage is then applied to the remaining months if you are estimating sales to the end of the reporting period.

This forecasting method uses this calculation:

Monthly Estimate = (Last Year's Sales for Same Month × Year-To-Date Sales for Current Year) ÷ Year-To-Date Sales Last Year

Example

This table lists the results of the forecast calculation based on reported sales for 2007 and 2008:

By applying the forecast calculation from the previous table, determine the sales estimate for November and December 2008 based on the sales figures for the same month in the previous year. The table also shows the percent increase in sales between the two time periods.

Note. For a lease to be comparable, 13 months of sales must exist. In addition, you cannot use this method to forecast January sales.

Forecasting Method 3: Fixed Percent Increase

The system estimates sales using a fixed flat percentage increase entered in the appropriate processing option.

This forecasting method uses this calculation:

Monthly Estimate = (Sales This Month Last Year) × (Fixed Flat Percent Increase)

Example

This table illustrates calculating a sales estimate by using a flat percentage:

Determine the sales estimate for November 2008 by multiplying the sales figure for November 2007 with the flat percentage entered into the processing option.

Note. For a lease to be comparable, sales for the estimated month in the prior year must exist. That is, at least 13 months of sales data must be available.

Forecasting Method 4: Specific Percent Increase for Each Month

The system estimates sales using a percentage increase for the particular month as entered in the appropriate processing option.

This forecasting method uses this calculation:

Monthly Estimate = (Sales This Month Last Year) × (This Month's Percent Increase)

Example

To calculate sales estimates for January, February and March of 2008, enter these percentage values in the appropriate processing options:

• January: 10 percent

• February: 20 percent

• March: 30 percent

  Month	2007 Reported	2008 Estimated	Forecast Calculation
  JANUARY	10,000	11,000	10,000 × 1.1
  FEBRUARY	12,500	15,000	12,500 × 1.2
  MARCH	15,000	19,500	15,000 × 1.3

Determine the sales estimates for January, February, and March 2008 by multiplying the sales figures for the corresponding months of 2007 with the percentage from the processing options.

Note. For a lease to be comparable, sales for the estimated month in the prior year must exist, that is, at least 13 months of sales data must be available.

Forecasting Method 5: Specific Percent Increase over Prior Month's Sales

The system estimates sales using a percentage increase over the prior month's sales in the prior year. Enter this percentage increase in the appropriate processing options.

This forecasting method uses this calculation:

Monthly Estimate = (Sales Last Month Last Year) × (This Month's Percent Increase)

Example

To calculate sales estimates for July, August and September 2008, enter these percentage values in the appropriate processing option:

• July: 25 percent

• August: 30 percent

• September: -15 percent

  Month	2007 Reported	2008 Estimated	Forecast Calculation
  JUNE	20,000
  JULY	22,500	25,000	20,000 × 1.25
  AUGUST	25,000	29,250	22,500 × 1.3
  SEPTEMBER	27,500	21,250	25,000 × .85

Determine the sales estimates for July, August, and September, 2008 by multiplying each previous month's sales in 2007 with the percentage that you entered in the processing option.

Note. For a lease to comparable, sales must exist for the month prior to the estimated month in the prior year.

Forecasting Method 6: Flat Percent Derived From Comparing the 13th to the 1st Month

The system estimates sales by comparing sales for the 13^thto the 1^stmonth when 13 months of sales figures are available. To calculate this month's estimated sales, use the percentage increase or decrease multiplied by this month's sales for the year.

This forecasting method uses this calculation:

Monthly Estimate = (Sales This Month Last Year × Sales for 13^thmonth) ÷ Sales for 1^stmonth

Example

This table lists the reported sales figures for 13 months and illustrates how the sales estimates for February through December, 2008 are calculated:

Determine the percentage used to calculated the sales estimates from this calculation:

Increase in 13^th month over 1^st month = Sales (January 2008) ÷ Sales (January 2007)

40,000 ÷ 30,000 = 1.3333 or 33.33 percent

Note. For a lease to be comparable, sales for the estimated month in the prior year must exist. That is, at least 13 months of sales data must be available.

Forecasting Method 7: Project/Building Year-To-Date Increase Over Prior Year

The system estimates sales based on a year-to-date increase for the mall (either building or project number as defined in the processing options) over the prior year. Because this method includes more than just the lease for which sales are being estimated, the reporting months sales for all comparable leases within the building or project are included in the calculation of year-to-date sales. For example, if estimating sales for December 2008, you compare year-to-date sales for January to December 2008 with the year-to-date sales for January to December 2007 for all comparable leases with the same building or project number. When forecasting the first three months of the year, (January, February, and March), year-to-date sales include the prior 4 months through the reporting month.

This forecasting method uses this calculation:

Monthly estimate = (Lease Sales This Month Last Year × Mall Year To Date Sales This Year) ÷ Mall Year To Date Sales Last Year

Where Month is the current reporting period.

Example

In this example, leases 1, 2, and 3 are all in Building ULSTER.

This table lists the reported sales for leases 1, 2, and 3 for 2007 and 2008:

The system does not use lease 3 for calculating the building growth rate because it does not have sales for December. Without a full set of year-to-date sales, the growth rate calculation would be skewed and, therefore, incorrect. In this example, only leases 1 and 2 are used to calculate the building growth rate.

This calculation yields this result:

Building Growth Rate = Year-To-Date Sales 2008 ÷ Year-To-Date Sales 2007

392,000 + 394,000 ÷ 365,000 + 334,000

786,000 ÷ 699,000 = 1.1245 or 12.45 percent

Determine the sales estimate for December 2008 for Lease 3 by multiplying the sales figure for November 2007 with the percentage increase calculated for the building growth rate:

Estimated Sales (Lease 3, December 2008) = 22,000 × 1.1245 = 24,739.00

Note. For a lease to be comparable, sales must exist for at least a calendar year, from January to December.

Sales Forecasting for Noncomparable Leases

For noncomparable leases, run the Seasonality Generation program (R1547) to obtain the seasonality values necessary for generating monthly estimates.

Example: Sales Forecasting for Building Quincy and ULI Code B05 for the 2007

This table lists the actual sales for 2007, as well as the seasonality values for each month:

To generate a monthly estimate, retrieve the previous three months of actual sales. The program requires at least one month of sales to generate the monthly estimate. If no sales exist for the previous 3-month period, the program cannot calculate a monthly estimate.

For the months following the first month for which estimates are generated, the Projected Sales Generation (R1542) program uses the estimated sales to generate subsequent estimated amounts.

The monthly estimate is calculated using this formula:

Monthly Estimate (n, ×) = ((Sales_{n-3, ×} ÷ Seasonality_{n-3, ×-1}+ Sales_{n-2, ×}÷ Seasonality_{n-2, ×-1}+ Sales_{n-1, ×}÷ Seasonality_{n-1, ×-1}) ÷ Number of months) × Seasonality_n,×-1

Wherenis the current period/month and × is the current year.

In the processing options for the R1542 program, specify whether to run the program for the reporting period only or for a period of time through the end of the reporting period.

Forecast Through the Reporting Period

In this example, assume that you want to generate estimates for the months of April, May and June:

The projected sales for April, May and June are calculated as:

Forecast for the Reporting Period Only

In this example, assume that you want to generate an estimate for only the month of June:

The projected sales for June are calculated as follows:

Sales Estimate (June) = 0.095890 × (25,000 ÷ .054795 + 0 + 0) ÷ 1

0.095890 × 456,246.01 = 43,749.43

Prerequisite

Before you complete the tasks in this section, you must run the Seasonality Generation program (R1547) to ensure that all included leases meet the conditions for comparable leases.

See Generating Seasonality Values.

Running the Projected Sales Generation Program

Select Sales Forecasting (G152211), Projected Sales Generation.

Setting Processing Options for Projected Sales Generation (R1542)

Processing options enable you to specify the default processing for programs and reports.

Process

Forecast

Print

Revising Projected Sales

This section provides an overview of projected sales revisions and discusses how to:

• Set processing options for Projected Sales Revisions (P15423).

• Revise projected sales.

Understanding Projected Sales Revisions

Use the Projected Sales Revision program (P15423) to revise or delete projected sales records that the system generates when you run the Projected Sales Generation program (R1542), or to manually add projected sales records. The system updates the F1542 table with the revisions.

Forms Used to Revise Projected Sales

Setting Processing Options for Projected Sales Revisions (P15423)

Processing options enable you to specify the default processing for programs and reports.

Process

Revising Projected Sales

Access the Projected Sales Revisions form.

Product Code	Enter the product code from UDC table 15/PC to categorize tenants' sales. The codes are used for Sales Reporting in the Sales Overage module of the Property Management system. Example product codes are: FOOD: Food TOYS: Toys OFCF: Office Furniture BOOK: Books
Store Number	Enter the alphanumeric code that identifies a particular store number.
Year	Enter the four-digit calendar year.
January through December	Enter the forecasted sales amount for periods 1 through 12.