AI Agents for Dynamics
365 FP&A
Which combinations are reportable was decided at implementation. That is why so much Dynamics analysis ends up in a spreadsheet.
- Dynamics decides which dimension combinations are reportable at implementation. Anything outside a configured set needs a rebuild, which is why analysis ends up in spreadsheets.
- An agent reading at transaction grain does not need a dimension set to exist, and can answer a cut nobody configured while returning the filter.
- In a worked 208,000 variance, 25,000 came from a budget loaded against a dimension set whose definition later changed. Nobody would find that by investigating spending.
- Report the budget model, its dimension basis, its coverage and its lock date. Four fields, and they remove most review questions.
- A budget loaded at a coarser dimension than actuals produces a residual that reads as overspend.
AI agents for Dynamics 365 Finance FP&A read dimension values on the transaction rather than depending on a configured dimension set, answer cuts nobody set up, and name the budget model, its dimension basis, its coverage and its lock date on every variance. ChatFin returns the filter with every figure and posts nothing.
The structural constraint is that Dynamics decides which dimension combinations are reportable when the dimension sets are built, and that happens at implementation. A cut outside those sets needs a rebuild through a queue, so people export to a spreadsheet or reuse a set that nearly fits. The first loses the audit trail and the second quietly answers a different question.
Dimension sets are the model, and they were fixed at implementation
Dynamics encodes analysis in financial dimensions and the dimension sets built on them. Which combinations are reportable was decided at implementation. Anything outside those sets needs a rebuild, which is why so much Dynamics analysis ends up in a spreadsheet.
| What people do | Why | What it costs |
|---|---|---|
| Export to a spreadsheet | The cut they need is not in a set | No audit trail, no rerun |
| Ask IT for a new set | It is the correct route | A queue, so it does not happen |
| Reuse a set that nearly fits | It is available now | The number quietly answers a different question |
| Report from balances only | It is fast | No explanation available |
An agent reading at transaction grain does not need a dimension set to exist. It can answer a cut nobody configured, and return the filter so the answer is checkable.
ChatFin reads dimension values on the transaction rather than depending on a configured set, and returns the filter it applied with every figure.
A worked variance, 208,000 over budget
A cost centre is 208,000 over budget. Rebuilt from transactions it is four things and two are not the cost centre's.
| Component | Amount | Evidence |
|---|---|---|
| Genuine rate increases on three suppliers | 78,000 | Invoices at new rates from renewal |
| Invoices coded by vendor default dimension | 61,000 | 41 invoices, dimensions match the vendor default exactly |
| Allocation from a shared cost pool | 44,000 | One allocation journal |
| Budget loaded against a dimension set that changed | 25,000 | Set redefined in month two |
| Total | 208,000 |
The last line is the one nobody would find. The budget was loaded against a dimension set whose definition changed, so the comparison is between two different populations while looking like a normal variance.
Which budget, and against which dimensions
Three fields make a Dynamics variance reviewable and they are rarely present.
Allocations, which explain a large share of what gets queried
Allocation journals move cost after the fact. A cost centre manager investigating an overspend frequently finds an allocation rather than anything their team did, and ChatFin sees that pattern on most Dynamics implementations.
Separate primary from allocated cost, always
They answer different questions. A manager can act on primary cost and usually cannot act on an allocation. ChatFin splits them on every cost report.
Show the source of every allocated amount
Which journal, which sender, what basis. Without that an allocation is an unexplained number arriving monthly.
Report when the allocation basis changed
A change in the driver moves cost between centres with no business event behind it, and it looks exactly like one.
Reconcile allocations out before comparing to budget
If the budget was set on primary cost and actuals include allocations, the variance is structural rather than performance.
ChatFin reports the allocation source and basis alongside the amount, so a manager can see immediately whether a movement is theirs to explain.
Where this underperforms
Three.
ChatFin ties out to a report your team already signs before anything else. A rebuilt figure that does not tie is a finding worth having in week one.
Deeper in Dynamics 365 FP&A
Three use cases sit under this hub, in build and shown rather than linked.
Worked on this page
Natural language querying of finance data · Financial forecasting · Financial modeling
Covered as sections here
Variance analysis · Budget models · Dimension sets · Allocations · Management commentary
Questions Dynamics 365 FP&A teams ask first
Why does Dynamics analysis end up in spreadsheets?
Because the cut people need is not in a configured dimension set, and adding one is a request that queues. So they export, which loses the audit trail and cannot be rerun, or they reuse a set that nearly fits, which quietly answers a different question. An agent reading dimension values on the transaction does not need the set to exist, and ChatFin returns the filter it applied so the answer is checkable.
What should be reported alongside a Dynamics variance?
The budget model, the dimension basis it was loaded at, its coverage and its lock date. A budget loaded at a coarser dimension than actuals produces a residual that reads as overspend, a revision covering some cost centres makes part of the variance an artefact, and an editable model makes prior comparisons retrospectively wrong. Four fields, rarely present.
What is the hardest variance cause to find?
A dimension set that was redefined. In a worked 208,000 variance, 25,000 came from a budget loaded against a set whose definition changed in month two, so the comparison was between two different populations while looking like an ordinary variance. No amount of investigating departmental spending would have surfaced it.
Answer the cut nobody configured.
ChatFin reads dimension values on the transaction rather than depending on a configured set, so a cut that would need a rebuild can be answered directly with the filter returned.
Every variance names the budget model, its dimension basis, coverage and lock date, and every figure is rebuilt from transactions.
Bring one quarter of variance and the cut you cannot get. The comparison takes an hour.
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Bring the cut you cannot get today.
We will answer it from transactions through ChatFin and rebuild one variance into components that reconcile to the reported total.