I built the calculator below to pressure-test a startup idea, and the first thing it told me was uncomfortable: a textbook “realistic” UK SaaS (800 customers, £200/month, a small team, modest churn) loses money on every customer it acquires. LTV:CAC comes out below 1x. Plenty of founders would still call that business “viable” because the headline expected value clears the entry cost. The calculator refuses to: it flags the contradiction instead of hiding it.

That tension is the point. Most startup advice is pattern-matching: “raise 18 months of runway”, “hit $100K MRR before Series A”. These heuristics ignore the market you’re entering and the competitor waiting to displace you. The calculator is built on the Aghion-Howitt quality ladder model, the work that earned Philippe Aghion and Peter Howitt the 2025 Nobel Prize in Economics and which formalises innovation as creative destruction (Aghion & Howitt, 1992). Try it first; the theory is below if you want it.

Start with a preset to see how different archetypes perform, then adjust the parameters to model your own situation.

The Economic Foundation

The Aghion-Howitt framework (1992) treats innovation as discrete quality improvements that replace existing products. When you build a startup, you’re creating a quality improvement over existing solutions. The framework helps answer: Is this improvement valuable enough to justify the cost of building it?

The Core Equation

The model centres on a simple inequality:

Where:

• EV = Expected value (survival probability × business value)
• wη = Entry cost to build and launch

Viability reduces to a simple question: can expected returns justify upfront investment?

Let’s break down each component:

Business Value (V)

Your business value is determined by the perpetuity formula adjusted for growth:

Where:

• π = Annual profit at Series A scale (target customers × profit per customer)
• r* = Adjusted discount rate accounting for displacement risk and churn
• g = Growth rate from innovation (g = λ·log(γ))

The adjusted discount rate accounts for real risks:

This means higher displacement risk and customer churn directly reduce your business value.

Expected Value

Your expected value is survival probability multiplied by business value:

Where λ represents displacement risk, the probability that competitors or market changes make your solution obsolete. Higher displacement risk means lower expected value.

Entry Cost (wη)

The actual capital required to build and launch:

For UK startups, this includes:

• Employee salaries with employer NI: 1.2–1.4x base salary (1.15x if running lean)
• Infrastructure: legal, accounting, software, and cloud
• Runway: months required to build and launch

What the Model Teaches Us

After experimenting with the calculator, several patterns emerge about startup viability:

Churn Destroys Value Exponentially

At 3% monthly churn, only 69% of customers remain after a year. Compare this to 2% churn (78% retention): the difference cuts LTV by more than half. Retention trumps acquisition for most businesses.

Gross Margin Matters Immensely

Sub-60% gross margins prevent SaaS-level valuations. You’ll be valued like a services or logistics business (lower multiples), affecting fundraising, exit potential, and strategic flexibility.

Defensibility Compounds Over Time

A business with 60% switching costs and 40% network effects achieves 46% defensibility, significantly reducing displacement risk. Early moats matter more than fast growth.

Entry Costs Arrive Before Revenue

Entry cost (wη) arrives upfront, before revenue. A £50k reduction in entry cost has the same impact as a £50k increase in expected value, but is usually faster to achieve. Lower entry costs reduce the viability threshold.

How to Use the Calculator

Now that you’ve seen the core insights, here’s how to model your specific startup:

1. Start with a Preset

Try the presets to understand different startup archetypes:

• Realistic Optimised: Balanced assumptions for a typical UK SaaS startup
• Lean Startup: Minimal viable team, focus on efficiency
• Best Case: Strong unit economics with competitive advantages
• Defensive Moat: High switching costs and network effects

2. Adjust Entry Costs

Model your build phase honestly:

• Team size: How many people are needed to build the MVP?
• Salaries: UK market rates for your roles (£40–80k typical for tech)
• Employment multiplier: Include employer NI (13.8%), pension (3–10%), and equipment
• Months to build: Be realistic. Most products take 6–12 months
• Infrastructure: Legal (£5–15k), accounting (£3–8k annually), software licences, and cloud

3. Define Unit Economics

This is where most startups succeed or fail:

• Monthly revenue per customer: Customer payment amount
• COGS: Direct costs to deliver (hosting, fulfilment, materials)
• Operating costs: Support, platform fees, transaction costs
• Gross margin: Target 60%+ for SaaS valuations

4. Estimate Market Dynamics

• Monthly churn: 2-3% is excellent for B2B SaaS, >5% is problematic
• TAM: Total addressable market in number of customers
• Series A target: Typically 600-1200 customers depending on ACV

5. Assess Competitive Position

This is where the Aghion-Howitt model shines:

• Quality improvement (γ): How much better is your solution? 2-3x is incremental, 5-10x is transformative
• Displacement risk (λ): What’s the probability competitors or market changes make you obsolete?
• Switching costs: How hard is it for customers to leave? (Data lock-in, integrations, training)
• Network effects: Does value increase with more users?
• Competitor strength: How formidable are incumbents?

6. Interpret the Results

The calculator shows:

• Viability gap: The £ difference between EV and wη
• Positioning score: Overall competitive strength (0-100)
• Key metrics: LTV, CAC payback, gross margin, burn rate
• Insights: Specific warnings and recommendations based on your inputs

Limitations and Considerations

This model has key limitations:

1. Assumes stable parameters: Real markets exhibit uncertainty and variance
2. Ignores pivots: Market learning may require strategic changes
3. Linear customer growth: Actual growth is usually sporadic
4. No seasonality: Many businesses have seasonal cycles
5. Generic CAC: Uses £2k as a default rather than your actual acquisition cost
6. Heuristic defensibility weights: The calculator weights switching costs and network effects equally (50% each) in reducing displacement risk. Economic literature confirms these drive competitive moats, but lacks a theory for their precise relative importance. Similarly, competitor strength (0–50% increase) and regulatory risk (0–30% increase) are calibrated heuristics, not derived from first principles

Treat this as a structured analytical framework, not a predictive tool. Its value lies in forcing rigorous thinking:

• What makes your solution valuable?
• What threatens your position?
• What is the minimum viable investment?
• When should you abandon the idea?

The Nobel Prize Connection

The 2025 Nobel Prize in Economics recognised three economists for explaining innovation-driven growth:

• Joel Mokyr (Northwestern University / Tel Aviv University), “for having identified the prerequisites for sustained growth through technological progress”
• Philippe Aghion (Collège de France, INSEAD, LSE) and Peter Howitt (Brown University), “for the theory of sustained growth through creative destruction”

Aghion and Howitt’s quality ladder model, which this calculator implements, explains how innovation creates value by replacing existing products with better ones. Building a startup is not just business creation. It is participation in the creative destruction that drives economic progress.

This calculator translates Nobel Prize-winning economic theory into actionable business decisions. When circumstances change, mechanism-based reasoning adapts; pattern-matching fails.

Further Reading

If you want to dive deeper into the economic foundations:

• Aghion & Howitt (1992): “A Model of Growth Through Creative Destruction”. The original paper establishing the quality ladder framework
• Acemoglu (2008): “Introduction to Modern Economic Growth”. Comprehensive textbook on endogenous growth theory and innovation economics
• Tirole (1988): “The Theory of Industrial Organization”. Essential reading on market structure, competition, and strategic positioning
• Christensen (1997): “The Innovator’s Dilemma”. Bridges theory and practice by explaining how displacement actually happens in markets

For practical startup guidance grounded in these principles:

• Kerr & Nanda (2015): “Financing Innovation”. Explains how VC economics and funding structures shape viable startup strategies
• Ries (2011): “The Lean Startup”. Practical methodology for rapid iteration that aligns with learning about displacement risk
• Blank (2013): “The Four Steps to the Epiphany”. Customer development framework for validating quality improvements

Conclusion

Most startup advice relies on pattern-matching: “X worked for Y company, so try that.” This calculator offers something different: mechanism-based reasoning about why businesses succeed or fail.

The Aghion-Howitt model cannot tell you whether to build your specific idea. But it forces you to confront hard questions:

• Is your quality improvement (γ) large enough?
• Can you build defensibility before competitors respond?
• Does your entry cost (wη) leave enough margin for error?
• Will your unit economics survive real-world churn and competition?

Answer these honestly, and you’ll understand whether you have a viable business before spending 9 months and £200k discovering the answer the hard way.

Build something valuable. Build something defensible. Use economic theory to improve your odds.