Every guide hands you a menu of methods and tells you to pick two or three. Whoever picks the methods picks the answer, which is the problem.
There are five startup valuation methods to run on an early-stage company, and the useful move is to run all of them every time. Equidam’s methodology uses two qualitative methods, the Scorecard Method and the Checklist Method, and three quantitative ones, DCF with Long-Term Growth, DCF with Multiples and the Venture Capital method, grouped into three lenses: Qualitative Assessment (Scorecard, Checklist), Future Cash Flows (the two DCFs) and Investor Returns (the VC method). The five outputs are combined into one number through a weighted average set by the company’s development stage: the qualitative pair carries the most signal before there is revenue, the cash-flow methods take over as traction accumulates. That combination is the unit of analysis, not any single method. It is the engine behind 160,000+ companies valued, every parameter published on the Data Sources page (Equidam internal data).
The standard advice is the opposite. Ask most advisors, or most AI assistants, “what valuation method should I use?” and you get a menu: Berkus for pre-revenue, Scorecard for angels, VC method for Series A, DCF once you have revenue. Then pick two or three and triangulate. It sounds rigorous, but nobody says who chooses, on what basis, or how much each method counts once chosen.
What investors actually do today
In a survey of 885 institutional venture capitalists at 681 firms, Gompers, Gornall, Kaplan and Strebulaev found 63% use a cash-on-cash multiple and only 22% use NPV methods. Seventeen percent of early-stage VCs use no financial metric at all, 31% of them don’t forecast cash flows, and the mean number of metrics used is 2.1: triangulation in the wild is two metrics, not five methods.
Forty-nine percent set valuation by dividing the amount they want to invest by the ownership stake they want, rising to 63% of early-stage investors against 29% at late stage. That is round-size arithmetic with a valuation-shaped output. The authors are blunt: “VC firms as a class appear to make decisions in a way that is inconsistent with predictions and recommendations of finance theory.” (Gompers et al.; plain-language version in HBR)
So why should the founder do the work the investor skipped?
Fair question. Three answers.
The price doesn’t stop at the handshake. An investor who arrived at your number by dividing cheque size by target ownership still has to take it to an investment committee, and the fund still has to report the holding to its limited partners at a defensible fair value. Reasoning has to appear at some point. Whoever brings it first sets the terms of the discussion.
A number built from stated assumptions also changes what gets argued about. Without one you are trading intuitions: $6M against $3M, with the more experienced negotiator usually winning. With one, the disagreement moves to specific inputs, whether 40% growth is credible, whether an 8x exit multiple fits the sector, whether the survival odds are right for your country and stage. Those are arguments where evidence counts and where you know the business better than they do.
And where the investor holds no valuation position at all, the 17% using no metric, the 31% not forecasting cash flows, yours is the only analysis in the room. That is not a guarantee of anything, but an empty chair on the other side is an odd reason to leave your own chair empty.
Why no single method works
You won’t fix this by finding the one right method. The systematic literature review by Montani, Gervasio and Pulcini (2020) concludes that “there is currently no ‘perfect’ method to assess a startup’s value. Each model discussed has significant limits.” It names what a good approach needs, forward-looking forecasts, probability across scenarios and business-model specificity, then finds that “none of the discussed methods integrates these three features harmoniously.”
The five-method combination is built against that gap: the two DCFs and the VC method are forward-looking, country-level survival rates and stage-specific required returns carry the probability, and Scorecard and Checklist carry the business-model and team specificity no financial model captures.
The five startup valuation methods, and what each is measuring
Qualitative Assessment: how to value a pre-revenue startup
The first lens reads the company rather than its spreadsheet, which is why it does most of the work before there is revenue to model.
1. Scorecard method: startup valuation against regional peers
The Scorecard method starts from the average pre-money valuation of comparable companies in your region, sector and stage, then adjusts for how you compare on weighted factors. Bill Payne’s published methodology weights management team 0–30%, size of opportunity 0–25%, product and technology 0–15%, competitive environment and sales channels 0–10% each, and need for additional investment and “other” 0–5% each; Equidam’s implementation folds those last two into a single 10% weight for funding required, leaving six factors. Each factor is scored by how far it diverges from the assumed average, the scores are weighted and summed, and the total is applied to the baseline as a percentage adjustment. On an illustrative -2 to +2 scale, a $4M regional seed baseline with team +1, market +2, product +1, competition -1, partnerships 0 and funding needs -1 gives a +0.75 adjustment: $4M × 1.75 = $7M.
That baseline is a published input, not a house guess. Equidam builds it from real transactions recorded worldwide since 15 January 2023 and publishes the resulting average and maximum pre-money valuations for 89 countries: the Scorecard average sits at $6.96M in the United States, £4.22M in the United Kingdom, €4.30M in Germany and €5.01M in the Netherlands. Identical scores, different country, different starting point. That is the method working as designed, and it is also its main weakness.
(A separate Equidam dataset, the Startup Valuation Delta, measures something else entirely: the valuations the five methods produce for companies raising. Its H1 2026 edition puts the median pre-seed valuation at $5.20M globally, with a $3.30M median in Europe against $5.16M in the United States. That is output, not input. It is not what the Scorecard baseline is built from.)
The method inherits whatever the transaction market is doing, and Montani et al. name a second limit: the “great discretion used to assign a weight to different factors that determine the final startup value.” The DCF methods never reference peer pricing, which is what offsets both.
2. Checklist method (Berkus): startup valuation by risk retired
The Checklist method works the other way. Start from a realistic maximum pre-money valuation for your stage and region, drawn from the same table of real transactions ($16M in the United States, £9.46M in the United Kingdom), then award a percentage of that ceiling across five achievement areas. Dave Berkus built the original around five risk-reduction elements with an equal maximum on each, and has since written that the per-element maximum should reflect what investors in your region actually pay. Equidam’s version weights the areas unequally: core team (30%), quality of the idea (20%), product development and IP (15%), strategic relationships (15%), operating stage (20%).
Against a $2.5M ceiling with team 80% achieved, idea 90%, product/IP 50%, relationships 40%, operating stage 20%: $600K + $450K + $187.5K + $150K + $100K = $1,487,500. What it gives up is hard grounding in the inputs, which Montani et al. put as “high subjectivity in the financial valuation of the […] considered risk factors”. Scorecard’s relative scoring and the quantitative model both pull against that.
Those two examples disagree, $7M against $1.49M. Scorecard asks how you compare to peers; Checklist asks how much risk you have retired. The spread is information.
Future Cash Flows: DCF for startups, run twice
The second lens is a single discounted cash flow model, run twice with one deliberate difference.
3. DCF with Long-Term Growth: the company as a going concern
Project free cash flow to equity (FCFE, what is left for shareholders after costs, tax, investment and debt service), typically over three to five years, beyond which projections carry little information. Discount each year by a country-level survival rate, then to present value at a CAPM cost of equity: the risk-free rate from 10-year government securities, a country-specific market risk premium, and a four-factor beta (how far the business moves with the wider market) adjusted for industry, number of employees, stage and profitability. Terminal value, the lump sum standing in for everything earned after the forecast window, here assumes the company continues indefinitely at long-term growth of 0.1–2.5%, with an illiquidity discount for shares that can’t be sold on demand. That 0.1–2.5% is the perpetual rate after the forecast ends, not the company’s growth during the forecast period. Nothing grows at 40% a year forever, and no economy would contain it if it did. Every parameter is published with its source on the Data Sources page (full DCF adaptations).
4. DCF with Multiples: the same model, priced at exit
Identical projection, identical survival rates, identical discount rate. One thing changes: terminal value becomes final-year EBITDA × an industry EBITDA multiple × the final-year survival rate (mechanics here).
Why there are two DCFs, not one
This is what most guides miss. Terminal value usually accounts for the bulk of a DCF result on an early-stage company, and the two ways of estimating it encode two different futures: an independent business compounding modestly forever, or an acquisition at market multiples. Picking one silently is a judgement call disguised as arithmetic; running both keeps the judgement visible.
Both share a blind spot: each is only as good as the projections fed in. Scorecard and Checklist never touch the forecast, and the VC method tests the output against an outsider’s return requirement.
Investor Returns: the venture capital method
The third lens holds the one method that models the buyer instead of the business.
5. Venture capital method valuation: working backwards from the exit
The VC method estimates exit value (projected exit-year revenue or EBITDA × an industry multiple), divides by the return the investor requires at your stage, and subtracts the investment for pre-money. Worked: $20M exit-year revenue × 4 = $80M exit value; ÷ 20x = $4M post-money; less a $1M investment = $3M pre-money.
Alone among the five, it models the investor’s constraint: whether your number clears the hurdle of a fund that needs a portfolio-level return.
The required return is the input that does the most work here. Halve it and the valuation doubles, which makes the round 20x in that worked example the least defensible thing in it. So here is ours, in public: at idea stage Equidam uses a required ROI of 94.08% a year, the rate an investment has to compound at over an eight-year horizon to satisfy a 5x fund multiple given a 5.94% success rate and a 42% retention rate. Compounded, that is a far more demanding hurdle than 20x, and it produces a lower valuation. The required return then falls as the stage advances and the odds improve: fund multiples come down toward 3x, success rates rise from roughly 6% at idea stage to about 33% at growth, retention from 42% to 84%. The derivation for every stage is set out in The Logic of the VC Method.
The annual required return and the fund multiple are not the same measurement: 94.08% a year is what one investment must promise, 3–5x is what the whole fund aims to return once most of its investments have returned nothing.
Publishing the figure is the point of the exercise. Gompers et al. found 64% of VCs adjust target returns for risk, but only 5% discount systematic risk more than idiosyncratic risk, and 23% apply the same metric to every investment. Required return is where arbitrariness hides, so it belongs in a table set before anyone knows whose valuation it will affect. The two DCFs, built from a CAPM cost of equity and observable survival data, are a second check on it.
The five methods at a glance
| Method | What it measures | Key inputs | Weight by stage |
|---|---|---|---|
| Scorecard | How you compare to regional peers | Published regional average pre-money (real transactions); six weighted factors | 38% at idea, 6% at expansion, 0% from growth |
| Checklist | How much risk you have retired | Published regional maximum for the stage; five achievement areas | 38% at idea, 6% at expansion, 0% from growth |
| DCF with Long-Term Growth | Value as an ongoing independent business | FCFE projections, survival rates, CAPM cost of equity, LTG 0.1–2.5% | 4% at idea, 36% at expansion, 50% at maturity |
| DCF with Multiples | Value if acquired at market rates | Same projections and discount rate; EBITDA multiple × final-year survival rate | 4% at idea, 36% at expansion, 50% at maturity |
| Venture Capital method | Whether the price clears an investor’s return hurdle | Exit value, stage-specific required ROI, dilution, timing | 16% from idea through expansion |
How are the five methods weighted?
Equidam runs all five on every company (Scorecard, Checklist, DCF with Long-Term Growth, DCF with Multiples and the Venture Capital method) and combines them into a single weighted average, on a schedule published in advance and set by the company’s development stage rather than by the deal in front of you. At idea stage, Scorecard and Checklist carry 38% each: team, market and product are the only parts of the company there is real evidence about yet. By startup stage they are down to 15% each while the two DCFs are up to 27% each, their projections now anchored to actual performance. At expansion stage the qualitative pair falls to 6% each and the DCFs carry 36% each, because by then the value of team and assets shows up in the cash flows. By growth stage the qualitative pair drops out entirely, and at maturity the two DCFs carry the full weight at 50% each. The VC method holds 16% from idea through expansion, while its required-ROI input changes substantially by stage. The full default schedule, stage by stage, is published in the appendix of Equidam’s sample valuation report, alongside the source of every parameter feeding the five methods.
A standardised schedule earns its keep because it is set before anyone knows the answer. Your advisor picked Berkus and a DCF, the investor picked the VC method and comparables, and now you’re arguing about method selection instead of about the business. A published default moves the argument onto the assumptions you can actually discuss and change: growth, cost structure, market size, exit potential, required return.
Why not just use comparables?
Because a comparable tells you what someone else paid, not what this business is worth. Aswath Damodaran of NYU Stern, whose public datasets are one of the sources Equidam draws multiples, long-term growth rates, market risk premia and betas from (Data Sources), puts it in Living with Noise: Valuing Young Companies:
“As investors/analysts face more uncertainty about the future, they become less willing to grapple with it […] Instead, they choose to price companies/assets, thus anchoring what they are willing to pay to what others are paying for similar assets. […] You are letting the crowd, just as uncertain as you are, determine what you should pay.”
And the headline numbers you’d anchor to aren’t what they appear. Gornall and Strebulaev modelled 135 US unicorns and found reported post-money valuations averaged 50% above fair value once contractual terms were priced in, with 65 of the 135 losing unicorn status. Those are prices produced by term sheets, not estimates of value.
Comparables do have a job, just a later one: once you have a valuation from the five methods, compute the implied multiples and benchmark those against peers. An out-of-line multiple is a prompt to re-examine an assumption. That is a check on the model rather than the thing driving it (more on multiples).
The standard the same number is held to a day later
The IPEV Valuation Guidelines are the fair-value standard professional PE and VC funds report against. They do not govern how a fund prices your round. That is a negotiation, and IPEV has nothing to say about it. What they govern is what happens to the number afterwards, when the fund has to carry the holding on its books and report a fair value to its own limited partners.
At that point the guidelines call for a written valuation policy documenting the procedures and methodologies behind each valuation, plus the inputs, assumptions and significant judgements involved, applied consistently from one measurement date to the next and calibrated back against the price paid at entry. Independent review of methodologies and significant inputs sits alongside those as recommended practice.
So the same figure that both sides may have reached by feel on Tuesday becomes, on Wednesday, a documented and periodically reviewed fair value in a fund’s reporting. Look at the asymmetry there. The party selling is told to improvise two methods and defend a range. The party buying will be documenting and re-deriving that same number for years.
Isn’t a standardised model just a black box?
The literature puts that challenge directly: Montani et al. group “the Equidam calculator” with automatic web valuators whose “main limits are excessive simplification and standardization.” The standardisation is the intended feature; simplification is the fair challenge, so check it. The sample valuation report shows every parameter and calculation for all five methods, and the Data Sources page names each input’s origin, from Damodaran at NYU Stern and Crunchbase to a weekly-refreshed database of 30,000+ public-market comparables across 90+ countries and 600+ industries (Equidam internal data). A black box is a model whose workings you cannot inspect. Every input above is inspectable, down to the required return and the country baseline, which is why they can be argued with.
What to do with this
Run all five. But be clear about which of them you can run yourself.
Three you can do on paper this afternoon. Scorecard needs a regional baseline and six scores, and the country averages are published. Checklist needs a regional ceiling and five percentages, from the same page. The VC method needs an exit assumption and a required return. The worked examples above are the entire procedure for all three, and doing them by hand pays off twice over: the disagreements they surface are the ones you will have with an investor.
The two DCFs are not paper work, and it would be dishonest to pretend otherwise. They need country-level survival rates, a beta adjusted for industry, stage, size and profitability, a country-specific market risk premium and a current risk-free rate. No founder has those to hand, and all of them go stale. That is the part software exists for, and it is why the parameters are published rather than merely asserted.
Either way, the move is the same: get the conversation onto the assumptions (growth, costs, survival, exit, required return) and treat the valuation as their output. That is what Equidam’s methodology does; what startup valuation is covers the price-versus-value ground underneath it, the Ultimate Guide is the wider primer, and we’ve covered the four methods worth skipping separately.
The stakes run past your round. A working paper by Xiyue (Ellen) Li finds startups steer projects toward what investors already know how to value, and that the 7,669 patent applications it identifies as “catering” are 19.3% less likely to receive approval. When the available tools only handle familiar business models, founders get pushed toward familiar businesses.
A valuation is an estimate under stated assumptions. What this one gives you is a number you can reconstruct, interrogate and defend. You can run the five on your own numbers whenever you want to see what they say.
FAQ
How many valuation methods should you use? All five, combined into a weighted average. Selecting two or three case by case is where bias enters, and in practice that selection collapses to about 2.1 metrics (Gompers et al.).
Which startup valuation methods apply to a pre-revenue company? All five still run. Scorecard and Checklist carry the heaviest weight at idea and development stage, because a pre-revenue company’s evidence sits in its team, market and product rather than its accounts.
What’s the difference between DCF with Long-Term Growth and DCF with Multiples? The projections and the discount rate are identical. They part company only at the terminal value: one prices a business that keeps operating, the other prices one that gets bought.
How are the five methods weighted? By development stage, on a default schedule Equidam publishes in advance. Scorecard and Checklist start at 38% each and fall to 6% by expansion stage, dropping out altogether by growth and maturity; the two DCFs climb from 4% each at idea to 50% each at maturity; the VC method holds 16% from idea through expansion.
Is the Berkus method still used? Yes, as the Checklist method, with subjectivity in scoring as its documented limit. That’s why it belongs in a combination.