How value growth works — from a single startup to a full portfolio

Standard early-stage assessment asks "is this a good startup?" The Startup Mentor™ asks a different question: "where is enterprise value being created, where is it being constrained, and what specific action would unlock it?"

The answer is a decomposition into 16 pillars — the dimensions along which early-stage enterprise value accumulates. Each pillar is scored (0–100) and independently evidence-graded (E1–E5). The score tells you how strong the pillar is. The evidence level tells you how much you should trust that score.

These are not assessment criteria. They are the dimensions along which enterprise value accumulates. Moving a pillar is creating value. A founder who takes P3_NTH from 20 to 70 has not "improved their score." They have identified and captured a specific, estimable portion of enterprise value that was previously constrained.

The evidence level is what makes this system fundamentally different from any other startup evaluation. A high score at low evidence is a confident guess. A moderate score at high evidence is validated reality. The system weights evidence as a multiplier on value:

A note on E2: E2 covers two types of indirect evidence. Anecdotal: your network confirms your thesis — real signal, but biased. Secondary: a published study or industry report measuring the same problem — real data, but generic. A McKinsey report quantifying the exact pain is stronger E2 than five friends nodding. But neither passes Gate 1 alone, because neither is evidence about your specific customers with your specific solution.

Value accumulates in layers. You cannot build a viable business model on an unvalidated customer. You cannot scale a business that doesn't have product-market fit. The system enforces this through value thresholds — gates that require evidence-graded validation before progression:

Each pillar score, weighted by its evidence multiplier, contributes to an enterprise valuation estimate. The model produces a range — not a single number — that narrows as evidence improves. At E1 across the board, the band is wide: the startup could be worth almost anything. At E3–E4, the band narrows dramatically. The narrowing itself is valuable — certainty is worth something to investors.

A value gap is the difference between a pillar's current contribution and what it would contribute if improved. The system calculates the economic value of every gap. A founder doesn't just hear "work on your pricing." They see: "your P3_NTH gap at E1 is your highest-impact lever. Closing it to E3 would raise your valuation floor by €185K. Improving your logo would raise it by €2K."

Each session produces specific, actionable tasks — ranked by value impact, sequenced by dependency, with clear success criteria. Not "do customer research" but "talk to five potential customers who match your ICP, ask about their current spending on this problem, and report what price they would pay." The task is designed to produce evidence at a specific level for a specific pillar.

Across sessions, the system tracks value growth velocity — how fast pillar scores and evidence levels improve. A startup with high velocity and incomplete gates is a strong candidate for continued investment. A startup with zero velocity after three sessions has a structural problem the mentoring has not yet resolved.

The same architecture that tracks individual startup value growth scales to the portfolio level. This is not a separate product. It is the same analytical framework applied at a different aggregation level.

The framework is invariant. The parameters shift. Understanding these distributions is essential for calibrating expectations, benchmarks, and interventions.