Venture capital is supposed to finance the improbable; spotting the outliers amongst a field of promising opportunities.

That makes valuation hard. When investors can’t easily recognise a novel company’s value, it does more than slow negotiation. It shapes which ventures get created and which get financed. Research shows that this friction nudges founders toward lower‑quality, copy‑cat projects that fit what investors already understand. This is bad for innovation and, ultimately, bad for LP returns.

Mastering valuation, especially for companies with no obvious peers to compare against, is therefore a core VC competency, not just a menial back‑office task.

To make this case we can synthesize evidence from three studies:

  • Li (2025) formalizes and documents a “catering” dynamic: when valuation is hard, founders pivot ideas toward what VCs already know how to evaluate, at a measurable cost to quality of company and speed of innovation.
  • Dittmann, Maug & Kemper (2002) show that German VCs who anchor on fundamental valuation and who triangulate across methods have meaningfully lower write‑off rates, while multiples alone are not useful.
  • Miloud, Aspelund & Cabrol (2012) demonstrate that investors already price strategic drivers (industry growth, founder/TMT quality, and external relationships) into early‑stage valuations, pointing to a useful “inputs‑based” complement when cash‑flow histories don’t exist.

Together, they imply a simple imperative: if VCs want to serve both LPs (returns) and founders (receptivity to new ideas), they must get better at understanding value without leaning on crude comparables.

When valuation frictions distort innovation

Li defines startup catering as founders selecting projects that “deviate from their own experience toward a VC’s expertise,” precisely to reduce information frictions in valuation. Using 62,088 first‑time patent applications by US startups (2007–2018), she shows that proximity to a VC’s expertise raises the odds of receiving investment and shortens the time to first check; a one‑standard‑deviation increase in this proximity predicts a 27% higher investment probability relative to the sample mean.

But this informational shortcut comes at a cost. Catering applications are 9.3 percentage points less likely to be granted within three years, which is about a 19.3% drop relative to a 48.2% mean approval rate—a clear quality penalty. The dynamic is strongest where alternative information is weaker (slower patent examination speeds) and when VCs double down on past‑data‑driven screening, making them especially “informative” when the new idea looks like something they already know.

The uncomfortable conclusion is that VCs shape the opportunity set before term sheets exist. If investors can’t see the value of novel projects, founders rationally steer toward imitative ones they can finance. Better valuation reduces that distortion.

Evidence that fundamentals (and multiple methods) improve VC outcomes

Dittmann, Maug and Kemper surveyed 53 German early‑stage VC funds about how they value deals and linked those practices to performance (write‑offs and IPOs). The pattern is striking: 58% said they use DCF, and respondents used ~3 methods on average (2.92), i.e., triangulating rather than relying on a single technique.

But implementation matters. Only 10 of the 31 DCF users tied their discount rate to an objectifiable cost of capital; most used subjective, ad‑hoc rates. That difference shows up in performance: using DCF with an objectifiable discount rate (DCF‑O) reduces write‑off rates by ~5.4 percentage points, while using DCF with subjective rates doesn’t help.

The study also finds that longer investment horizons (≥4 years) are associated with 7.5 percentage‑point lower write‑offs, consistent with a fundamentals‑first stance instead of short‑term momentum.

Two more takeaways for practice:

  • Multiples aren’t a silver bullet. Use of multiples is not significantly correlated with performance in this sample.
  • Breadth helps, if it’s disciplined. Funds that use several methods have lower failure rates, and DCF users tend to pair it with other “objectifiable” approaches rather than subjective heuristics.

The message isn’t “do DCF and ignore everything else.” It’s apply a disciplined fundamentals method and triangulate and avoid over‑reliance on comparables that price in the last cycle’s exuberance (or fear).

Pricing outliers without “comps”: use the inputs founders and markets actually care about

Miloud, Aspelund & Cabrol study 184 early‑stage financing rounds across 102 French startups and show that VCs already price strategic factors. Early‑stage valuations are significantly and positively related to industry attractiveness/growth, founder & top‑management experience, and external relationships (network size)—variables long known to drive performance in strategy research.

Why does that matter for valuation practice? Because novel ventures lack the accounting histories traditional methods demand; valuations computed mechanically can vary wildly. The authors note that, under such conditions, startup valuation often devolves into “guess” and “alchemy.” An inputs‑based approach, systematically incorporating strategic determinants, gives investors a way to price when cash‑flow outputs are hard to estimate.

This aligns perfectly with a first‑principles DCF mindset. A disciplined cash‑flow model is not a spreadsheet trick; it’s a conversation scaffold that forces investor and founder to surface assumptions about the very inputs Miloud et al. identify: market growth pathways, defensibility, team capacity, and how relationships accelerate commercialization. It’s the fastest way to align on expectations and to see the underlying value when no clean comps exist.

Why comps alone are procyclical, and how triangulation counters it

Comparables import the market’s current mood. In hot categories, they overstate value; in neglected categories, they understate it. For outliers (the ideas with no real peers) comps can hallucinate precision, benchmarking to the wrong reference class. Dittmann et al. show that multiples add little explanatory power to performance.

Triangulation counters procyclicality. If you:

  • Anchor on fundamentals,
  • Cross‑check with objectifiable ratios (e.g., EV/EBITDA), and
  • Explicitly price strategic drivers (industry growth, team quality, network reach),

…you’re less likely to let the last bull or bear market do your thinking for you, and more likely to see the value of a novel, non‑obvious company before it becomes consensus.

A practical, founder‑friendly valuation posture for VCs

You don’t need exotic models to do this well. You need a repeatable way to understand value that founders recognize as fair and that LPs recognize as disciplined.

  1. Start with the business physics. Map the handful of drivers that actually move cash flows: adoption curve, gross margin path, selling motion, capex/working‑capital needs. Use them to build scenarios and make each assumption testable in the first 12–18 months post‑investment.
  2. Use DCF as the backbone, not a black box. The point isn’t the 10‑year tab. It’s the clarity it produces on why the path creates value and where risk concentrates. Importantly, tie discount rates to opportunity cost of capital.
  3. Triangulate across methods. Add objectifiable cross‑checks (qualitative and quantitative methods) and avoid methods that hide valuation inside negotiation mechanics. The study documents how prevalent such implicit methods still are.
  4. Be sparing and thoughtful with comps. When you must use them, normalize for growth, profitability, quality of revenue, and capital intensity, and de‑bias the peer set away from hot adjacent categories. This maintains discipline without letting public multiples dictate early‑stage truth. (Note again: multiples use did not significantly correlate with lower write‑offs in the German sample.
  5. Take a longer view. The same survey links ≥4‑year horizons with meaningfully fewer write‑offs. That posture resists trend‑chasing and supports staged, evidence‑seeking investments, the exact antidote to catering.
  6. Price the “inputs” explicitly. Miloud et al. show that industry growth, founder/TMT experience, and external relationships already inform valuations in practice; bring those drivers into the model explicitly and test them in diligence instead of relying on narrative.

Payoff: better returns and more originality

A recurrent worry is that fundamentals‑based valuation will slow deals or scare off founders. The opposite is more likely:

  • For LPs: Investors that have a stronger understanding of valuation will be able to recognise good opportunities more readily, avoid the capital-incinerating pursuit of consensus ideas, and they’ll be able to more accurately and proactively provide updates on the NAV of the fund.
  • For founders: When investors can see value without forcing sameness, founders don’t have to cater. Li’s evidence suggests we lose quality when entrepreneurs feel compelled to pitch what investors already understand; reducing valuation frictions helps the truly novel survive.

There’s also a portfolio‑construction angle: VC informativeness—the ability to assess projects near your expertise—predicts faster financing and higher investment probability. That’s good. But if every firm optimizes solely for that, the market starves exploration. The right response is not to abandon expertise, but to complement it with valuation capability that can parse opportunities outside the firm’s pattern library.

The bottom line

Venture outcomes are driven by outliers. Outliers, by definition, won’t fit the last cohort’s comps. If you rely on them, you’ll buy high when the market is euphoric, miss the weird, and pressure founders to look like what you already own.

The alternative is both older and more robust:

  1. Think in first principles about how this business will create cash flows and why the risk is worth it;
  2. Anchor your valuation in disciplined, objectifiable methods and triangulate with other rigorous tools; and
  3. Make strategy variables—market growth, team quality, networks—explicit in your assumptions.

The studies reviewed here converge on the same conclusion: VCs who value fundamentally and triangulate methodically do better, and they create space for originality. That is the job.

 

References used

Dittmann, I., Maug, E., & Kemper, J. (2002). How Fundamental are Fundamental Values? Valuation Methods and Their Impact on the Performance of German Venture Capitalists. Key findings cited: method prevalence; DCF‑O vs. subjective DCF; write‑off reductions; horizon effects; limited impact of multiples; benefits of triangulation.

Li, X. (2025). Startup Catering to Venture Capitalists. Key findings cited: 62,088‑application sample; 27% higher investment probability for high VC‑informativeness; 9.3‑pp lower grant rates (~19.3% relative drop) for catering; catering more common when patent information is delayed and when VCs adopt data‑driven screening.

Miloud, T., Aspelund, A., & Cabrol, M. (2012). Startup Valuation by Venture Capitalists: An Empirical Study. Key findings cited: 184 rounds/102 ventures; positive valuation effects of industry growth, founder/TMT quality, and external ties; motivation for inputs‑based valuation when financials are sparse.