Forecast accuracy

One minus the absolute forecast error over the actual, at a stated horizon, per rep and for the team.

DefinitionOne minus the absolute forecast error over the actual, at a stated horizon, per rep and for the team.

Forecast accuracy is one minus absolute error divided by actual, measured from a saved snapshot at a stated horizon. The team figure is the sum of signed errors and hides offsetting reps; the mean of per-rep absolute errors is the honest spread. Accuracy is read beside bias, because a random ten percent miss and a consistent ten percent low are different problems. See the forecast accuracy benchmark.

How it is computed

One minus the absolute value of forecast minus actual, divided by actual, measured from a saved forecast at a stated horizon.

Example

A forecast of $2.3 million made eight weeks out against an actual of $2.1 million is an error of 10 percent: accuracy of 90 percent at that horizon.

Where it goes wrong

Measured on the final forecast, the day before the period closes. Accuracy is always excellent and tells nobody anything.

Articles that use this term

Forecast and pipeline · Supply chain

Demand forecast bias by SKU and site: the plan that is always high in one place

How a supply chain team measures demand forecast accuracy and bias per SKU per site from the forecast snapshots and the actual demand: error and signed bias, the SKU-site pairs that are consistently over-forecast and carry the excess stock, the ones consistently under-forecast and carry the stock-outs, why bias at one site is usually a planner's override, and the adjustment the team's own history supports.

16 Sept 20263 min read Forecast and pipeline

Forecast bias by rep: the direction of the miss matters more than its size

How a sales leader measures forecast accuracy per rep from the weekly forecast snapshots and the closed results: error, bias and the split between them, why a rep who is always 20 percent high is more useful than one who is randomly 10 percent out, the per-rep adjustment it produces, and the identity that ties the adjusted forecast to the raw one.

16 Sept 20263 min read Forecast and pipeline

Pipeline stage definitions: exit criteria that make a weighted forecast mean something

Why a stage-weighted forecast is only as good as the stage definitions, what an exit criterion is, five stages with criteria a rep can verify and a manager can audit, how to check from the CRM that deals in a stage actually meet its criteria, the stage probabilities derived from the team's own history rather than set in a workshop, and the versioning that keeps last year's pipeline comparable.

16 Sept 20262 min read Forecast and pipeline

Reading a forecast bridge deal by deal: from run rate to the number the CFO sees

How to build a sales forecast bridge from pipeline history: the components that explain the difference between run rate and forecast, the slip count per deal that predicts the next slip, and the follow-up questions that turn the forecast call into a conversation about evidence.

16 Sept 20263 min read Alternatives and comparisons · Finance and FP&A teams

How to choose analytics software for finance and FP&A teams: questions, data and traps

How finance teams should choose analytics software: start from the questions, check the data you hold, ask vendors ten questions, avoid the traps.

24 Sept 20263 min read Alternatives and comparisons · Supply chain

How to choose analytics software for supply chain: questions, data and traps

How supply chain teams should choose analytics software: start from the questions, check the data you hold, ask vendors ten questions, avoid the traps.

24 Sept 20264 min read