eProcureAI / Platform / For FP and A
RoleCommitted spend is known weeks before it invoices. Building a forecast without it means rediscovering decisions that were already made and could have been planned around.
Written for the people building the model. Committed spend is the input you are missing.
Financial planning built on invoiced actuals is planning around decisions that were taken weeks ago, by people who did not think to mention them.
A department approves a purchase in March. The order goes out, the goods arrive in April, and the invoice posts in May. Your forecast learns about it in May, at which point it is not a forecast at all, it is a reconciliation.
The information existed in March. It simply was not carried anywhere you could see it, because the budget only moved when an invoice arrived to force it.
Approved orders that have not yet invoiced represent decisions the business has already made. Including them in a forecast converts a chunk of your model from estimate to fact.
It also changes the conversation with budget holders. Instead of explaining a variance after the event, you are discussing a position they can still influence.
When a line moves unexpectedly, the useful question is which transactions caused it and who approved them. Drilling from a variance to the underlying purchases with approver and reason attached turns a week of investigation into a few minutes.
Intent, not commitment. Reasonably invisible to a forecast at this stage.
The business has committed. This is the moment a forecast should know, and usually the moment it does not.
External commitment, difficult to unwind. Still absent from invoiced reporting.
Received but not invoiced. Relevant to both accruals and timing.
Where most forecasting inputs begin, which is several weeks too late to be useful.
Approved orders with expected timing, available at the moment of approval rather than when the invoice arrives.
Requests raised but not yet approved are the earliest signal you can get. Not commitment, but a genuine indication of where demand is building.
Drill from a moving line to the transactions behind it, each carrying who approved it and why, so the explanation is a lookup rather than an investigation.
Using all three gives you a picture that starts earlier and firms up as decisions are made.
| Signal | When it appears | Confidence | Best used for |
|---|---|---|---|
| Requests in flight | Before approval | Directional | Spotting pressure building on a budget |
| Committed spend | At approval | High | Forecasting the next few periods with facts |
| Goods received not invoiced | At delivery | Certain | Accruals and period cut off |
| Invoiced actuals | Weeks later | Certain but late | Reporting rather than forecasting |
Most planning functions only have the last of these, which is why forecasts feel like they are always catching up.
Drill from the summary rather than starting from a general ledger extract.
On every decision, with the reason they gave at the time.
Exceptions are recorded as exceptions, so the answer is on the record.
Category trend across periods rather than a single month in isolation.
The part that turns an explanation into a forecast adjustment.
Supplier and price adherence underneath the category number.
Better forecasting here is not a modelling improvement, it is an information timing improvement.
Build the model and explain the movement. Both get faster with better inputs.
Supplies the inputs at the moment they exist rather than when they invoice.
We will show what the committed position looked like at the time and what you would have seen.
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