Skip to content
Zero Employee Startup
Menu

Portfolio metric · methodology v0.1

Founder Attention ROI

The return on the scarcest resource in a founder-run portfolio: an hour of the founder's attention.
Updated 16 Oct 2026

Definition

Founder Attention ROI is the incremental portfolio value created per founder hour invested, measured at the margin, for the next hour rather than the average hour.

This is a proposed metric, not an industry standard. We publish the definition so it can be criticised and improved.

01Formula

Founder Attention ROI

Incremental portfolio value created per founder hour invested.

v0.1
Attention ROI = Δ portfolio value ÷ founder hours invested
Δ portfolio value
Change in value attributable to the work (e.g. Δ MRR × an explicit multiple, or Δ cash flow)
founder hours
Hours invested in the product or initiative over the same window

Allocate the next hour to the product with the highest marginal, not average, attention ROI.

  • — Attribution lags: value often arrives weeks after the hours.
  • — Average ROI flatters mature products; use marginal estimates for allocation.
Full definition →

02Worked example

Illustrative · hypothetical products · not real data

A founder gives two products an extra six hours a week for four weeks. Value is defined explicitly as ΔMRR × 12 (one year of the added recurring revenue); any consistent definition works if it is stated.

Illustrative founder attention ROI calculation
ProductHours investedΔ MRRΔ value (× 12)Attention ROI
Product A24h+$1,200$14,400$600 / h
Product D24h+$50$600$25 / h

The same 24 hours returned 24× more on Product A. Unless Product D's hours are buying something not in the metric, such as preparing it for sale, they belong on Product A.

03How to measure it

  1. Log founder hours per product and per initiative. Use weekly logs, not recollection.
  2. Choose one value definition (ΔMRR × a stated multiple, Δ monthly cash flow, or a sale-price proxy) and keep it fixed.
  3. Attribute value to the initiative that produced it, with a stated lag window (for example, 30–60 days for pricing changes).
  4. Estimate the marginal return of the next block of hours from recent experiments, not lifetime averages.

04Pitfalls

  • Average vs marginal. A mature product with a great track record can have a poor next hour.
  • Lag. SEO, content and distribution pay back slowly; short windows undervalue them.
  • Unpriced value. Hours spent preparing a product for sale, or protecting reputation, may not appear as revenue.
  • Noise. Small products have noisy revenue; prefer reversible experiments with stated thresholds.