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Prepared fictional example

Forecast and scenarios sample pack

An editable 12-month XLSX with drivers, three volume cases, cash roll-forward formulas, and exclusions.

Change a driver and trace the formula chain before using your own forecast.

Read the prepared sample

# Cedar Cycle — scenario model

Prepared fictional Kona example. Not a live AI run, customer story, verified demand, or approved financial/legal advice.

## Prepared inputs
Cedar Cycle is a fictional mobile bicycle-service concept. Unit price USD 100; variable cost USD 40/visit; monthly fixed cost USD 2,000; opening cash USD 10,000. Downside/base/upside volume: 30/40/50 visits per month. All figures are prepared assumptions. The simplified model excludes tax, debt, capex, payment timing, and changing capacity costs.

## Formulas
Revenue = monthly visits × price. Variable cost = monthly visits × variable cost per visit. Gross contribution = revenue − variable cost. Simplified operating cash = gross contribution − monthly fixed cost. Ending cash = prior cash + operating cash.

## Expected results
Downside monthly result: USD −200; month-12 cash: USD 7,600. Base monthly result: USD 400; month-12 cash: USD 14,800. Upside monthly result: USD 1,000; month-12 cash: USD 22,000.

## Review
These are constant-month scenarios. They are not tax, debt, capex, payment-timing, or probability-weighted forecasts. Do not read opening cash as an observed real account balance.

## How to revise
Edit the Inputs sheet, open the XLSX in compatible spreadsheet software, and inspect formula recalculation. Add supported lines explicitly if your business needs them.

Check before adapting it

  • Formula caches match independently calculated values.
  • Inputs are editable and referenced by formulas.
  • Opening/closing cash reconciles across months.
  • Excluded cash items are visible.

Prepared 2026-10-11 through Kona’s existing deterministic export code. Replace fictional assumptions, open the file, and check calculations and formatting before using it.

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AI financial forecast

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