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Forecast Override Log Worksheet

Manual overrides are sometimes the smartest part of a forecast and sometimes the biggest source of bias. This log records each override with its requester and reason, then compares the error of the adjusted forecast with the statistical baseline once actuals are in.

Download:

Override size	Statistical abs error	Adjusted abs error	Error reduction
300	280	20	260
300	100	200	-100
-400	50	450	-400
-80	85	5	80
150	10	140	-130

Total statistical error

525

Total adjusted error

815

Net error reduction

-290

Net override volume

270

Forecast value added

-55.2%

Share of statistical error removed by overrides. Negative means overrides made things worse.

Fill actuals after the period closes. Summarise by requester in Excel to see whose adjustments add value. Positive FVA means overrides help, negative means they hurt.

Automated override tracking

Ask for an optional review of capturing overrides and FVA directly from your planning data.

Optional. The tool and every export work without this. No spam.

How to use the worksheet

Record each override when it is agreed: SKU, who asked, why, the statistical forecast and the adjusted one. After the period closes, add the actuals. The worksheet computes absolute error for both versions, the error reduction per row, and the total forecast value added across the log. Export to Excel and pivot by requester or reason.

Reading forecast value added

Forecast value added is the share of statistical error removed by the adjustments. A positive result means that human input improved the forecast. A negative result means overrides, in total, increased error. Break it down by reason: promotions with evidence often add value, while optimistic sales uplifts with no evidence often subtract it.

Positive FVA: overrides helped
Negative FVA: overrides hurt
Slice by requester and by reason
Look at net override volume for bias

Using the findings

Share the results with each requester in the demand review in a neutral way. If one group consistently pushes volumes up without result, require evidence for their overrides, such as signed orders. If the planner correcting the model adds value, keep that route open. The aim is a fair process, not blame.

Common mistakes

Logging only large overrides hides the many small ones that add up to bias. Recording actuals against a version of the forecast that was changed after the fact makes the comparison meaningless. Freeze both versions at the time of the review and compare only against those.

Frequently Asked Questions

What is forecast value added?

Forecast value added measures whether a step in the forecast process, such as a manual override, improved accuracy compared with the previous step. It is calculated as the reduction in error versus the baseline.

Should I allow manual overrides at all?

Yes, when they carry information the model cannot see, such as signed orders or planned promotions. Track them, require a reason and review the results so poor overrides are discouraged.

Which error measure should I use?

Absolute error in units is simple and clear in this worksheet. Many teams also report percentage or weighted error. Whatever you choose, use it consistently for both versions.

How many cycles of data do I need?

At least three to six cycles before drawing conclusions about a group, because a few large items can dominate any single cycle.

Netray can capture overrides from your planning system and ERP automatically and report forecast value added by requester every cycle.

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