What it means
The forecast begins with the receivables ledger, which already contains real invoices with real due dates. Ageing that ledger and applying a realistic collection pattern to each band produces the near term receipts with a high degree of confidence.
Beyond the existing ledger, the forecast depends on the sales plan converted through a collection profile. If experience shows 30% of a month's sales are collected within the same month and 70% in the following month, that profile turns a revenue forecast into a dated receipts forecast.
Two adjustments separate a good forecast from an optimistic one. Bad debts need a small percentage haircut, and habitually late payers should be forecast on their actual behaviour rather than their agreed terms, even when the credit controller finds that uncomfortable.
Receipts are not only from customers. Grants, tax refunds, interest, insurance settlements, asset sales and loan drawdowns all arrive as cash, and leaving them out of the forecast produces surprises in both directions.
The forecast improves fastest through feedback. Comparing forecast receipts with actual receipts each week, and recording the reason for each material difference, quickly narrows the error range and gives the credit control team a clear list of accounts to chase.
In practice
Real-world examples.
Example
A specialist food supplier finds that its supermarket customer pays on day 68 despite 45 day terms. Rebuilding the receipts forecast around 68 days moves $410,000 of expected cash out by three weeks and reveals a genuine funding gap that had been hidden.
Example
A membership body forecasts renewal receipts by cohort, using the historical pattern that 55% of renewals are paid in the first two weeks after the reminder. That lets it fund its annual conference deposit from renewal cash rather than reserves.
Example
A civil engineering firm includes retention releases in its receipts forecast as a separate line, since these sums fall due long after the work is invoiced. Tracking them separately recovers $180,000 of retentions that had been quietly forgotten.
Think of it
“Cash receipts forecast predicts when you'll collect money-forecasting your cash coming in.
Formula
Calculation
Forecast receipts = collections from opening receivables + (forecast sales x same period collection percentage) + other cash inflows
A commercial cleaning company enters May with $600,000 of receivables, all within terms and expected to be collected during the month. Forecast May sales are $900,000, and history shows 30% is collected in the month of sale and 70% in the following month.
Forecast May receipts = $600,000 + ($900,000 x 0.30) = $600,000 + $270,000 = $870,000. Adding a $20,000 insurance refund due in May gives total forecast receipts of $890,000.
The remaining $900,000 x 0.70 = $630,000 falls into June. Applying a 2% allowance for invoices that will never be collected reduces that to $630,000 - $12,600 = $617,400, which is the figure carried into the June forecast.Case study
Seen in the real world.
The following is an illustrative and fictional case. Lantern Bay Marine, an invented boatyard and chandlery, forecast receipts by taking each month's sales plan and assuming payment on the stated 30 day terms. Every month the forecast was too high, and the finance manager blamed the sales team.
An analysis of the fictional company's last two years of collections told a different story. Chandlery sales were cash on the day, servicing work averaged 41 days, and winter storage invoices were routinely settled in March regardless of when they were raised, giving three quite different collection profiles blended into one meaningless average.
Lantern Bay rebuilt the receipts forecast with a separate profile for each revenue stream. Forecast accuracy for the following six months improved from being 18% out on average to within 4%, and the illustrative boatyard stopped drawing its overdraft in the two months it had previously assumed would be comfortable.
Watch out
Common mistakes.
- Forecasting collections on contractual payment terms rather than on how quickly each customer actually pays, which builds optimism into the model from the first cell.
- Blending several revenue streams with very different payment behaviour into one average collection period, which hides both the early cash and the late cash.
- Leaving out non trading inflows such as tax refunds, grant instalments and loan drawdowns, which can be large enough to change a funding decision.
Questions
People also ask.
How do I set a collection profile?
Take twelve months of paid invoices, measure the actual days between invoice date and payment date, and group the results by customer type or revenue stream.
Should the forecast include invoices in dispute?
Only at the value and date you genuinely expect to collect, since a disputed invoice sitting in the forecast at full value on its original due date is one of the most common sources of error.
How far ahead is a receipts forecast reliable?
Usually four to six weeks with high confidence because it is driven by existing invoices, with accuracy falling steadily beyond that as it relies more on the sales plan.
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