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V Viswanathan Associates

Chartered Accountants | FRN: 013713S

Pre-Revenue Startup Valuation: Berkus Method vs Scorecard Method Compared

February 22, 2026 V Viswanathan Associates 11 min read

How do you value a startup that has no revenue? Two of the most widely used frameworks — the Berkus Method and the Scorecard Method — offer structured approaches to this challenge. This guide compares both methods side-by-side, walks through Indian startup examples, and explains when professional valuers use each approach.

Why Pre-Revenue Valuation Is Different

Traditional valuation methods like DCF rely on historical cash flows and projectable revenue streams. Pre-revenue startups have neither. Instead, value resides in the quality of the idea, the team's ability to execute, the market opportunity, and the progress made toward reducing key risks. Both the Berkus and Scorecard methods attempt to quantify these qualitative factors into a defensible valuation number.

The Berkus Method Explained

How It Works

Created by angel investor Dave Berkus, this method assigns a value of up to ₹50 Lakhs (adapted for Indian context; $500K in US) to each of five risk-reducing factors. The maximum pre-money valuation is ₹2.5 Crores.

FactorWhat It MeasuresMax Value
Sound IdeaAttractiveness of concept and basic business risk₹50 Lakhs
Working PrototypeTechnology risk reduction₹50 Lakhs
Quality Management TeamExecution risk reduction₹50 Lakhs
Strategic RelationshipsMarket risk reduction (partnerships, early customers)₹50 Lakhs
Product Rollout / SalesFinancial and production risk reduction₹50 Lakhs

Berkus Method Example: Indian EdTech Startup

Case: "LearnBridge" — AI Tutoring Platform

Stage: Pre-revenue, MVP built, seeking angel round

FactorAssessmentValue Assigned
Sound IdeaAI-personalised learning for CBSE/ICSE — large TAM, strong demand₹40 Lakhs
Working PrototypeMVP with 500 beta users, 82% retention₹45 Lakhs
Quality ManagementIIT founders, ex-Byju's CTO — strong credentials₹50 Lakhs
Strategic Relationships3 school partnerships signed, AWS credits secured₹30 Lakhs
Product RolloutNot yet launched commercially₹10 Lakhs

Berkus Valuation: ₹1.75 Crores pre-money

The Scorecard Method Explained

How It Works

Developed by Bill Payne, the Scorecard Method starts with the average pre-money valuation for recently funded startups in the same region and sector, then adjusts up or down using weighted factor scores. Each factor is scored as a percentage (e.g., 125% means 25% above average) and multiplied by its weight.

FactorWeightScoring Basis
Management Team30%Experience, track record, completeness of team
Size of Opportunity25%TAM, growth rate, market timing
Product / Technology15%IP, technical moat, prototype completeness
Competitive Environment10%Barriers to entry, existing competitors
Marketing / Sales Channels10%Go-to-market readiness, channel partnerships
Need for Additional Funding5%Capital efficiency, runway needs
Other Factors5%Regulatory, geographic, timing advantages

Scorecard Method Example: Same EdTech Startup

Applying Scorecard to "LearnBridge"

Regional average pre-money valuation: ₹1.5 Crores (Chennai angel round average, 2025–26)

FactorWeightScoreWeighted Factor
Management Team30%130%0.390
Size of Opportunity25%120%0.300
Product / Technology15%125%0.188
Competitive Environment10%90%0.090
Marketing / Sales10%100%0.100
Additional Funding Need5%110%0.055
Other Factors5%115%0.058
Total Adjustment Factor1.181

Scorecard Valuation: ₹1.5 Cr × 1.181 = ₹1.77 Crores pre-money

Head-to-Head Comparison

DimensionBerkus MethodScorecard Method
CreatorDave Berkus (angel investor)Bill Payne (angel investor)
ApproachAbsolute value per risk factorRelative to regional average
Requires Benchmark Data?No — standalone scoringYes — needs average valuation
Maximum ValuationCapped (₹2.5 Cr)Uncapped (can exceed average)
Best ForVery early ideas, no comparable dataActive funding markets with comparables
Subjectivity LevelHighModerate (anchored to market)
Investor AcceptanceAngel rounds, idea stageAngel and pre-seed rounds
Indian Context FitGood for Tier 2/3 cities with sparse dataBetter for Bangalore/Chennai/Mumbai

Professional Valuer's Recommendation

Best Practice: Use Both + Risk Factor Summation

In our practice, we never rely on a single pre-revenue valuation method. The standard approach involves applying Berkus, Scorecard, and Risk Factor Summation methods in parallel, then triangulating the results into a defensible range. For IBBI-compliant reports, these methods provide supporting context alongside a primary DCF or NAV approach with probability-weighted scenarios.

  • Use Berkus for quick sanity-check of absolute value caps
  • Use Scorecard when regional funding data is available
  • Use Risk Factor Summation for granular risk adjustment
  • Present the range across all methods for credibility

Frequently Asked Questions

The Berkus Method assigns up to ₹50 Lakhs to each of five risk-reducing factors: sound idea, prototype, quality management team, strategic relationships, and product rollout/sales. The maximum pre-money valuation is ₹2.5 Crores. It is designed for pre-revenue startups where DCF analysis is impractical.

The Scorecard Method compares a target startup against the average pre-money valuation of recently funded startups in the same region and sector. It assigns percentage weights to factors like management team (30%), market size (25%), product/technology (15%), and others, then calculates an adjustment factor applied to the benchmark valuation.

Both have merits. Berkus works better for very early-stage ideas where comparable data is scarce. Scorecard is more robust when regional funding benchmarks are available. Most professional valuers use both methods alongside Risk Factor Summation and cross-check results for a defensible range.

For IBBI compliance and regulatory valuations, these serve as supporting approaches. IBBI standards typically require DCF or NAV as primary methods, with Berkus/Scorecard providing supplementary context. For very early-stage companies, these methods may be referenced with appropriate disclaimers about their qualitative nature.

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