Cash Shortage Probability Model
Estimates the probability of running out of cash within a given period based on revenue variability, expense commitments, and current reserves. Determines the buffer needed to reduce shortage risk to an acceptable threshold.
Risk - Cash Shortage Probability Model.xlsx
Excel (.xlsx) — No macros — Works in Excel, Google Sheets, LibreOffice
What This Spreadsheet Solves
- No quantified probability of cash running out
- Revenue variability is not factored into cash planning
- Fixed commitments create exposure during revenue dips
- Cash buffer sizing is based on intuition rather than data
- No early warning system for approaching cash shortfalls
Who This Is For
- CFOs and finance managers monitoring cash positions
- Startup founders managing burn rate against limited runway
- Small business owners with seasonal revenue patterns
- Financial analysts stress-testing cash flow scenarios
Inputs
- $Current Cash Balance
- $Average Monthly Revenue
- $Revenue Standard Deviation
- $Fixed Monthly Expenses
- #Projection Period (Months)
Outputs
- Probability of cash shortage within period
- Expected month of first potential shortage
- Minimum cash buffer for 95% confidence
- Monte Carlo simulation distribution
- Months of coverage at current burn rate
How Calculations Work
The model runs a Monte Carlo simulation generating thousands of revenue scenarios using the provided mean and standard deviation. For each scenario, monthly cash flow is computed as revenue minus fixed expenses, applied sequentially to the starting balance. A shortage occurs if the balance hits zero in any month. The probability is the percentage of scenarios resulting in a shortage. The buffer recommendation is the additional cash needed to reduce shortage probability below 5%.
Example Use Case
Scenario: Current cash: $120,000. Average monthly revenue: $45,000 with $12,000 standard deviation. Fixed expenses: $38,000/month. Projection: 12 months.
Result: Shortage probability: 23% over 12 months. First potential shortage month: month 8. Buffer needed for 95% confidence: $47,000 additional. Current coverage: 3.2 months at average net burn.
What You Get — 5 Sheets
Technical Details
Frequently Asked Questions
How do I estimate revenue standard deviation?
Calculate the standard deviation of your last 12-24 months of revenue. If you lack historical data, estimate the range between your worst and best months and divide by 4 as an approximation.
Does this assume expenses are fixed?
The base model uses fixed expenses. You can add variability to expenses in CONFIG by specifying an expense standard deviation, which produces more conservative results.
How many simulations does the model run?
Default is 10,000 iterations, configurable in CONFIG. More iterations increase accuracy but slow calculation. 10,000 is sufficient for most use cases.
What does 95% confidence buffer mean?
It means that with the recommended buffer, there is only a 5% chance of running out of cash during the projection period. Increase the confidence level in CONFIG for a more conservative buffer.
Can I model a revenue trend (growing or declining)?
Yes. Add a monthly growth rate in CONFIG. The simulation will apply the trend to each month's mean revenue while preserving the variability.
Download Cash Shortage Probability Model
Ready to use immediately. Enter your data in the INPUT sheet, see results in OUTPUT.