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Finance Operations

Forecast Cash Flow to the Liquidity Low Point

Hand Opulent statements and assumptions; get back an editable forecast workbook that pinpoints the liquidity low point, with every formula inspectable.

Skills
AuthorOpulent
CategoryFinance Operations
FeaturesSkills
start it with one message
Build me an editable cash-flow forecast workbook from our statements and assumptions. Pull actuals from Xero, project the next 13 weeks, and pinpoint the liquidity low point, with every formula inspectable so I can change an assumption and watch it recompute.
Run this in OpulentCopy it, swap the names for your own, and send it.
connected systems
XeroView financial data, generate reports, and gain personalized business insights
NumericAutomate accounting close workflows and financial reporting
Financial DatasetsAccess real-time stock prices, financials, SEC filings, and market data
FactSetAccess FactSet fundamentals, estimates, ownership, and deals
step 1

Hand over the actuals and the assumptions

Connect Xero for actuals and Numeric for close data; add Financial Datasets or FactSet if the forecast needs market inputs. Opulent pulls real numbers instead of asking you to paste them.

State the assumptions once as a skill spec, a reusable instruction set for how the workbook is built: the horizon, the collection and payment timing, and which drivers you want to flex. The workbook is built to that spec every time.

Build a 13-week cash-flow forecast workbook:

1. Pull the last 6 months of actuals from Xero as the base.
2. Project inflows: AR aging with collection timing by customer
   segment. Project outflows: AP, payroll, recurring, taxes.
3. Model the opening balance forward week by week.
4. Put every driver on an assumptions tab, referenced by formula
  , nothing hardcoded in the projection.
5. Flag the week with the lowest projected balance as the
   liquidity low point.
Tip

Ask for a scenario toggle on the assumptions tab, base, downside, upside. One workbook that flips between cases beats three separate files that drift out of sync.

step 2

Run it on demand and refresh it monthly

The first build is on-demand: send the kickoff message with your horizon and assumptions, and Opulent returns the workbook. This is a skill run, a packaged capability, so the same build is repeatable, not a one-off.

Keep it live with a schedule: a monthly run pulls fresh Xero actuals and rebuilds the forecast so the low point reflects reality. Set it under Settings, then Schedules, and route the workbook to your finance channel.

The sharp edge: a forecast with hardcoded numbers looks right and cannot be trusted, because you cannot see what drives it. Insist every projected cell trace to an assumption cell, so a reviewer can audit the logic.

step 3

Watch the workbook get built

Take a run building the forecast for a company with lumpy receivables:

Opulent builds the model with live formulas, then names the risk the numbers reveal.

Run: 13-week cash-flow forecast

Run actions:
- Pulled 6 months of actuals from Xero; classified inflows and
  outflows.
- Built AR collections from aging: 45% in week 1, 30% week 2,
  rest trailing.
- Laid opening balance forward 13 weeks with formulas referencing
  the assumptions tab.
- Found the low point: week 8 dips to $180k against a $250k
  covenant floor.
- Noted the driver: a $600k quarterly tax payment lands the same
  week AR runs thin.
step 4

What you can open and audit

When the run finishes, you have a working model, not a static PDF, and every number is verifiable:

An editable workbook with actuals, a projection, and a separate assumptions tab. The liquidity low point flagged, with the week and the shortfall named. Every projected cell driven by a formula that references an assumption, so changing one input recomputes the forecast.

The inspectable formulas are the proof-of-work: you can click any cell and see exactly how it was derived, then flex a driver and watch the low point move, instead of trusting a number you cannot trace.

step 5

Sharpen the forecast

When actuals keep diverging from the model, correct the assumptions (collection timing, seasonality) and write the better defaults into memory (the notes a run recalls next time), so the next monthly build starts closer to reality.

Add the scenarios your board asks about (a delayed raise, a slow quarter) as reusable toggles, so answering "what if" takes a click rather than a rebuild.

The natural chain: when the forecast raises a question the workbook cannot answer, hand it to Data Analysis as an Agent-Run Workflow for a deeper, sourced investigation.