About Forecast Curves

A forecast curve allows you to divide anticipated revenue over a series of sequences of time in a larger time period (such as a quarter). You can define forecast curves on the following:

• The forecast setup
• A project
• An opportunity

The forecast curve is made up of a number of forecast curve details, or points on the curve, each covering a certain number of days (Period) and indicating the percentage of the total forecast amount to apply during that period (Percent Burndown).

A forecast curve is basically a delivery schedule you can build, based on how your business typically performs.

Warning:

It is important to specify default curves for projects and opportunities in your forecast setup. You can add forecast curves to an individual project or opportunity but if you haven't added any and there are no default curves defined in your forecast setup, the forecast calculation will fail.

For information on creating forecast curves, see Managing Curves for Forecast Calculations.

Forecast curve data is stored in the Forecast Curve and Forecast Curve Detail objects.  For more information, see:

• Forecast Curve Fields
• Forecast Curve Detail Fields

Examples

Applying a Forecast Curve to a Project

A forecast curve is set on a project that spans Quarter 2 (Q2). The forecast curve is configured as follows:

• Lag = 10 days (applies from the run date of the forecast calculation and delays the start of burndown)
• Curve Detail 1 = Sequence: 1; Period: 20 days; Percent Burndown: 20%
• Curve Detail 2 = Sequence: 2; Period: 30 days; Percent Burndown: 80%

The length of the curve is the sum of the Lag and the Periods set on the curve details = 60 days.

The Q2 forecast calculation is run four times: on January 1, February 15, April 1, and May 16.

Run 1: January 1

January 1 + 60 days = March 1

Unscheduled backlog forecast = 0%

As January 1 does not fall within the Q2 time period, no unscheduled backlog is included in the forecast calculation.

Run 2: February 15

Feb 15 + 60 days = April 16

Unscheduled backlog forecast = 42.67%

As 16 days of the curve fall within the Q2 time period, only part of the unscheduled backlog is included in the forecast calculation.

Run 3: April 1

April 1 + 60 days = May 30

Unscheduled backlog forecast = 100%

As both the forecast run date and the curve end date fall within the Q2 time period, all of the unscheduled backlog is included in the forecast calculation.

Run 4: May 16

May 16 + 60 days = July 15

Unscheduled backlog forecast = 40%

As 45 days of the curve fall within the Q2 time period, only part of the unscheduled backlog is included in the forecast calculation.

The following diagram shows what is included in each run: Click the image to expand it.

Applying a Forecast Curve to an Opportunity

We take the weighted opportunity value and then project the delivery based on a curve that you apply to one of the following:

• The total opportunity amount
• The products that you would use on the opportunity

Weighted value of opportunity (opportunity value * probability percentage) = $10,000

Projected close date = January 1.

The business typically delivers a project over the following duration:

• Month 1 after opportunity close date = 0% delivered
• Month 2 = 10% delivered
• Month 3 = 30% delivered
• Month 4 = 30% delivered
• Month 5 = 20% delivered
• Month 6 = 10% delivered

The forecast curve reflects this delivery pattern:

• January = $0
• February = $1,000
• March = $3,000
• April = $3,000
• May = $2,000
• June = $1,000