Six commercial metrics on top of TRL, made executable · then tested against its own record, which surfaced three misfires. Its honest use is routing capital, not screening deals.
John Francis, Partner · July 2026 · PDF · 26 pages · 11,610 words · 308 KB
Time to Market, Return on Investment, Capital Needs, Competitive Landscape, Process versus Platform, and the Market-to-Capital ratio · with the weighting scale defined, weights forced to sum to one, and raw sums out of thirty abandoned. Six technologies are scored under four investor weight vectors and four narrative cases are restored, surfacing three unfavorable findings the paper keeps in the summary: a metric that carries no information, a false negative on autonomous vehicles that weighting corrects, and a Competitive Landscape definition that scores differentiation but not cost leadership.
[ figures ]
The evidence, drawn.
fig. 01 · six technologies × five weightings
Darker prints higher. The VC column scores below the equal-weight, private-equity and corporate columns in all six rows · a framework published by a venture firm rates every technology in its own benchmark set as a worse fit for venture capital than for those classes of capital. Where the public/mission column falls lower still, as for smart contracts, it is because no public mandate supports the technology. Its honest use is routing, not screening.
fig. 02 · how much each metric actually discriminates
Spread of scores across the six retrospective cases. A metric that returns the same value for mRNA vaccines, smart contracts, batteries, language models, autonomous vehicles and drug discovery is contributing a constant, not a judgment. The fix: a 5 now requires realized third-party building, not an argument that a platform could emerge.
fig. 03 · the false negative, routed
Autonomous vehicles, rescored. Flat summation averaged away the routing information; the weighted vectors reveal the buyer · and a corporate parent with a strategic thesis is who actually carried the technology through its expensive decade. Scale: 0-5.00.
[ contents ]
Inside the paper.
Abstract
Introduction and the literature since 2024
Core problem
The refined framework · six metrics, re-anchored
Making the framework reproducible
Applying the framework to investor types
Strategic enhancements
Six technologies, scored
What the scoring reveals about the instrument
Four narrative cases, and two predictions checked
A prospective example: an AI assurance venture (with disclosure)