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Archived noindex page. Kefiw's public focus is Property decision help.

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This older Kefiw page is kept for reference, marked noindex, and removed from the primary sitemap. The current Kefiw experience is focused on property decisions: cost, quotes, damage, buying, selling, owning, and packets.

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Six Runway Calculation Mistakes

The common errors that make runway look longer than it actually is.

Runway errors almost always run in one direction — more optimistic than reality. Here are the six to fix first.

Runway math seems simple — cash ÷ net burn — until you're wrong by 3 months and a quarterly tax bill lands. The mistakes below all push the Zero Date later than reality. Fixing them costs nothing and surfaces time you didn't know you were losing.

Quick answer

Runway errors almost always run in one direction — more optimistic than reality. Here are the six to fix first.

What you are trying to do
The common errors that make runway look longer than it actually is.
Best next step
Runway Zero
Limit to remember
Treat this as a practical aid for the task, not a replacement for professional judgment.

Key points

  • Counting booked revenue as cash. Signed contracts and sent invoices are not money in the bank. Use collected revenue only — or model the aging gap explicitly.
  • Forgetting quarterly and annual lumps. Estimated taxes, annual SaaS renewals, insurance premiums, and audit fees don't appear in monthly averages. Amortize them into burn.
  • Using gross instead of net revenue. Payment processor fees (2-3%), chargebacks, refunds, and platform cuts reduce the number. For SaaS, especially, NET is what funds the runway.
  • Ignoring customer concentration. If one customer is 40% of revenue, the "normal" runway calculation is a lie — your real runway is the Crisis-mode number, weighted by their renewal probability.
  • Assuming flat burn. Burn grows silently: tool upgrades, seat additions, cost-of-living raises, AWS bills. Last quarter's burn is usually 5-10% below this quarter's.
  • Not modeling payroll timing. If payroll lands on the 15th and rent on the 1st, mid-month cash can be dangerously low even if month-end looks fine. The Zero Date might be earlier than the monthly model shows.

Examples

  • The invoice gap
    $40k "revenue" in month 3 → $40k collected in month 5. If runway planning assumes month-3 cash, you're 60 days off.
  • The quarterly tax
    Monthly burn looks like $50k. Q4 estimated tax adds $30k in December. Runway at December looks fine; January might not.
  • The flat-burn lie
    Baseline set in January: $45k burn. By July: $52k burn (silent tool adds, raises, AWS creep). Runway projected from January is already 2 months too long.

When to use which tool

Related

Frequently asked questions

Should I include founder salary in burn? Trust & accuracy

Yes, at market rate. Deferred-salary math distorts runway — it looks longer than it is, and the deferred liability compounds when you raise.

Can I use projected revenue growth? Trust & accuracy

Not for runway math. Projections are a separate model; runway uses current reality. If you want to show projected runway, label it clearly — never confuse the two.

How should I use a decision framework in real life? How-to

Use a decision framework to expose the tradeoff, not to outsource the decision. Write down the inputs, compare the output with your constraints, then ask what would change the answer. The strongest use is scenario testing: base case, conservative case, and failure case.

Is this financial, legal, or tax advice? Trust & accuracy

No, this is not legal, financial, tax, medical, or professional advice unless the page explicitly says that use case is supported. It organizes assumptions so you can inspect them. Verify high-stakes choices with qualified people who can review facts, contracts, regulations, and downside risk.

What assumption matters most in a decision model? Edge case

The most important assumption is usually the one you are least certain about and most emotionally attached to. Change that input first. If the recommendation flips after a small change, the decision is fragile and needs more evidence before you treat the model as useful.