Forecast bridge

The decomposition of the difference between a run rate, or the prior forecast, and the current forecast into named components: new deals, expansion, slipped, pushed, lost.

DefinitionThe decomposition of the difference between a run rate, or the prior forecast, and the current forecast into named components: new deals, expansion, slipped, pushed, lost.

How it is built

Take every deal in the pipeline history with its stage, close date and value at two points in time. Classify the change: new since the prior snapshot, moved in from a later period, moved out to a later period, closed, lost, resized. Sum each class. The classes bridge the two totals exactly.

Why it matters

"Q4 is $1.4m above run rate" is a claim. "Three deals explain $1.1m of it, all pushed from Q3, all having slipped twice already" is a bridge, and it tells the CFO what to believe.

Needs history

A bridge needs stage history, not a snapshot. Two quarters of history gives a bridge; two years gives slip patterns by rep.

How it is computed

Starting from the prior forecast or the run rate, named lines add and subtract to reach the current forecast: deals won, lost, slipped out, pulled in, resized, and new. The lines sum exactly to the difference.

Example

Last month's forecast was $13.3 million. Won early plus $0.2 million, slipped out minus $0.7 million, lost minus $0.3 million, new deals plus $0.4 million. This month's forecast: $12.9 million.

Where it goes wrong

A forecast that changes with no explanation of which deals moved. Trust in the number goes with it.

Articles that use this term

Board and management reporting · Finance and FP&A teams

Automating the sales report: from a manual monthly pack to computed tables

A practical path for a sales operations or finance team that assembles the monthly sales report by hand: what to automate first, the definitions that have to be written down before anything can be computed, the four exports the whole pack comes from, the identity checks that replace the reconciliation week, what stays manual, and the order in which the pack's sections move from spreadsheet to computed table.

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 AI and self-service analytics

How to ask an analytics assistant a question it can answer reliably

What separates a question an AI analytics assistant answers correctly from one it answers plausibly: naming the measure, the level, the period and the comparison, asking for the table before the sentence, and checking the citation. Six rewrites of common questions, and the four kinds of question an assistant should refuse.

16 Sept 20263 min read Forecast and pipeline · Finance and FP&A teams

How to read a forecast bridge: the lines that sum, and the deal behind each one

A reading guide for a forecast bridge from last period's number to this one: the check that the lines sum before anything is read, the order to read them in, closed, slipped, lost, new, resized, the deal list behind each line as the thing to open, the line with no deals behind it as the one to distrust, the repeat slippers across bridges, and the two lines that set next period's calibration.

16 Sept 20263 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 Board and management reporting

Ten questions a CFO asks about sales data, and the table that answers each

The ten questions a chief financial officer puts to the commercial team, does the sales number reconcile, how concentrated are we, what is the base worth, is the forecast believable, where is revenue leaking, what does it cost to serve the top accounts, are credits under control, is the pipeline real, what did the discounting cost, and what changed, each with the computed table that answers it, the identity that makes the answer trustworthy, and the answer a CFO should refuse.

16 Sept 20263 min read