Chapter 2: First Principles Thinking in Strategy¶

Chapter Overview¶

Key Questions This Chapter Answers¶

1. What distinguishes first principles thinking from conventional reasoning?
2. When does analogical reasoning work, and when does it lead to strategic failure?
3. How can you systematically break down assumptions to find strategic opportunities?
4. What mental models are most valuable for strategic thinking?
5. Why do "best practices" often destroy competitive advantage?

Connection to Previous Chapters¶

Chapter 1 established that strategy requires a clear diagnosis of the key challenge. This chapter explores HOW to develop breakthrough diagnoses by reasoning from fundamentals rather than accepting inherited assumptions.

What Readers Will Be Able to Do After This Chapter¶

• Decompose complex business problems into fundamental components
• Identify when analogical reasoning is appropriate and when it is dangerous
• Apply the Assumption Breakdown Framework to any strategic question
• Use 20 mental models to enhance strategic analysis
• Recognize and escape the "best practices" trap

Core Narrative¶

2.1 The Tyranny of Analogy¶

In 2002, Elon Musk wanted to buy a rocket. The Russian Dnepr rocket cost $18 million per launch. American rockets cost even more. The conventional wisdom was clear: rockets are expensive because that is what rockets cost.

Most entrepreneurs would have accepted this premise and built their business around it. They might have reasoned: "Rockets have always been expensive. The aerospace industry is mature. Smart people have worked on this for 60 years. The current pricing must reflect real constraints."

This is reasoning by analogy. The rocket costs what rockets have cost. The future will resemble the past.

Musk did something different. He asked: "What is a rocket made of? What are the raw materials?"

The answer: aerospace-grade aluminum alloys, titanium, copper, and carbon fiber. Total raw material cost for a rocket: roughly $2 million - about 2% of the selling price.

This is reasoning from first principles. Strip away history, precedent, and assumption. Ask what is fundamentally true.

The gap between $2 million in materials and $60+ million in selling price represented opportunity. Not all of that gap could be captured - manufacturing, testing, labor, and overhead are real. But the 98% gross margin embedded in traditional aerospace pricing suggested massive inefficiency.

SpaceX now launches rockets for roughly $2,720 per kilogram to low Earth orbit, compared to $54,500 per kilogram for the Space Shuttle. The company achieved this not by copying aerospace best practices better than Boeing, but by questioning whether those practices were necessary at all.

2.2 Defining First Principles Thinking¶

First principles thinking is the practice of breaking down complex problems into their most fundamental truths and reasoning up from there.

The term comes from Aristotle, who defined a first principle as "the first basis from which a thing is known." In physics, first principles are the fundamental laws from which all other phenomena derive.

In strategic thinking, first principles are the irreducible facts about physics, economics, and human behavior that cannot be broken down further.

Examples of first principles in business:

Physics:

• Energy is conserved (you cannot create something from nothing)
• Information can travel at most at the speed of light
• Manufacturing has a minimum theoretical energy requirement

Economics:

• People respond to incentives
• Prices coordinate supply and demand
• Comparative advantage creates gains from trade

Human Behavior:

• People discount the future relative to the present
• Loss aversion exceeds gain attraction (~2x)
• Status and belonging are fundamental human needs

These principles do not change based on industry, geography, or era. They constrain what is possible and enable what is achievable.

2.3 First Principles vs. Analogical Reasoning¶

Analogical reasoning says: "This situation resembles that situation, so what worked there will work here."

First principles reasoning says: "What is fundamentally true about this situation? What must be true regardless of what has happened before?"

Both have their place. The strategic skill is knowing when to use which.

When Analogical Reasoning Works:

1. Mature, stable environments: When industry dynamics have been consistent for decades, historical patterns are predictive.

2. Incremental improvements: When seeking to optimize an existing model rather than create a new one.

3. Speed requirements: When you need to act quickly and cannot afford deep analysis.

4. Pattern matching: When the analogous situation is genuinely similar in the relevant dimensions.

Example: A restaurant entering a new neighborhood can reasonably use analogies from other neighborhoods. The fundamentals of restaurants (food costs, labor ratios, rent economics) are well-understood.

When Analogical Reasoning Kills You:

1. Technological discontinuities: When new technology changes what is possible, historical analogies mislead.

2. Business model innovation: When competitors are playing a different game, analogies to competitors' past behavior fail.

3. Paradigm shifts: When fundamental assumptions are changing, reasoning from the old paradigm guarantees failure.

4. High-stakes, low-frequency decisions: When the cost of being wrong is catastrophic, analogies are insufficient.

Example: Kodak's leadership reasoned by analogy - they had successfully navigated transitions before (from plates to film, from black-and-white to color). Digital was just another transition. This analogy was fatally flawed because digital eliminated the film consumable entirely, not just improved it. (For analysis of disruption patterns, see Chapter 17: Disruption Theory.)

2.4 The Assumption Breakdown Process¶

First principles thinking requires systematically identifying and challenging assumptions. Here is a structured process:

Step 1: State the current belief

Write down the conventional wisdom about your strategic question. What does everyone in your industry believe? What do experts say?

Example: "Building a premium electric car is impossible because battery costs make them uneconomical without subsidies."

Step 2: List all supporting assumptions

Break down the belief into its component assumptions. Why is the conventional wisdom believed to be true?

Example assumptions:

• Battery costs are fundamentally high due to rare materials
• Manufacturing scale economies have been fully captured
• Consumer willingness to pay for EVs is limited
• Charging infrastructure limitations reduce EV utility
• Traditional auto OEMs have optimized the car business

Step 3: Challenge each assumption

For each assumption, ask:

• Is this necessarily true?
• What would make it false?
• Is there evidence that contradicts it?
• What would we do if this assumption were wrong?

Example challenges:

• Battery costs: What are the raw materials? (Lithium, nickel, cobalt, aluminum.) What is their cost per kWh? ($50-80 in materials for a $200 cell in 2012.) Where is the manufacturing margin?
• Manufacturing scale: Have EVs been produced at scale? (No, in 2012.) Are there economies yet to capture?
• Consumer WTP: What do luxury car buyers pay? ($60K+.) Is an EV less valuable than a BMW?
• Charging: Can this be solved with infrastructure investment? (Yes, though requires capital.)
• OEM optimization: Have they optimized for EVs or for ICE vehicles? (ICE - their entire system assumes internal combustion.)

Step 4: Identify which assumptions are actually first principles

Some assumptions will survive challenge. They are physical limits, mathematical truths, or well-documented behavioral constants. These are your first principles.

Other assumptions are actually conventions, habits, or outdated constraints. These are opportunities.

Example findings:

• First principle: Battery chemistry determines energy density limits
• First principle: Electric motors are more efficient than ICE
• NOT first principle: "Battery packs cost $500/kWh" (was convention, not limit)
• NOT first principle: "Charging takes hours" (was infrastructure choice, not physical limit)

Step 5: Reason up from first principles

With false assumptions removed, what is actually possible? What strategy would you pursue if you started from scratch?

Example reasoning: If battery cells are $200/kWh and can reach $100/kWh at scale, and electric motors are 90% efficient vs. ICE 20% efficiency, the total cost of ownership for EVs could be lower than ICE. The strategic opportunity is to build a premium EV that competes on performance AND economics, using premium pricing to fund the battery cost until scale economies arrive.

2.5 Twenty Essential Mental Models for Strategic Thinking¶

Mental models are frameworks for understanding how the world works. They compress experience into reusable patterns. Here are 20 models particularly valuable for strategic thinking:

Economics & Competition:

1. Supply and Demand: Prices adjust to balance supply and demand. Pricing power comes from constrained supply or intense demand.

2. Opportunity Cost: The true cost of anything is what you give up to get it. Every strategic choice forecloses alternatives.

3. Comparative Advantage: Focus on what you can do relatively better, even if not absolutely better. Trade creates value.

4. Economies of Scale: Unit costs decrease with volume. This creates winner-take-most dynamics in scale-sensitive industries.

5. Network Effects: Product value increases with users. Creates exponential returns to early leaders.

Systems & Dynamics:

1. Feedback Loops: Positive loops amplify; negative loops stabilize. Identify which loops dominate your strategic situation.

2. Second-Order Effects: The consequence of the consequence. Most strategic mistakes happen in second-order effects.

3. Bottlenecks: System performance is limited by the scarcest resource. Identify and address bottlenecks first.

4. Leverage: Small inputs create large outputs at leverage points. Find the levers in your strategic system.

5. Reversibility: Reversible decisions can be made quickly; irreversible ones require caution. Match decision speed to reversibility.

Psychology & Behavior:

1. Incentives: People respond to incentives, especially misaligned ones. "Show me the incentive and I will show you the outcome."

2. Loss Aversion: Losses hurt ~2x as much as equivalent gains feel good. This shapes competitive response.

3. Anchoring: First information disproportionately affects judgment. Control the anchor in negotiations and positioning.

4. Status Quo Bias: People prefer current state over change. Incumbents benefit; attackers must overcome.

5. Social Proof: People follow others' behavior, especially in uncertainty. Early adoption signals drive later adoption.

Problem Solving:

1. Inversion: Sometimes the best way to solve a problem is to avoid what causes failure. "What would guarantee failure? Don't do that."

2. Occam's Razor: Simpler explanations are more likely correct. Prefer simple strategies to complex ones.

3. Falsification: Seek to disprove hypotheses, not confirm them. What would prove your strategy wrong?

4. Margin of Safety: Build in buffer for error. Strategies that require everything to go right usually fail.

5. Circle of Competence: Know what you know and what you don't. Stay within your circle or expand it deliberately.

2.6 The Best Practices Trap¶

"Best practices" is one of the most dangerous phrases in business strategy. Here is why:

Best practices assume the past predicts the future. A practice was "best" in a particular context. If the context changes, the practice may become irrelevant or harmful.

Best practices assume one size fits all. A practice that works for one company may fail for another with different capabilities, culture, or strategic position.

Best practices converge competitors. If everyone adopts the same practices, no one gains advantage. Best practices are table stakes, not strategy.

Best practices optimize within paradigms. They cannot help you when the paradigm itself is changing. Blockbuster's best practices for retail video rental were industry-leading - store location optimization, inventory management, late fee revenue maximization - and became worthless when streaming eliminated physical rental.

The Alternative: Best Questions

Instead of "What are the best practices?" ask:

• What is uniquely true about our situation?
• What assumptions underlie current practices?
• What would we do if we started from scratch?
• What practices would be "worst" for our competitors to adopt?
• What is possible now that was not possible five years ago?

The goal is not to ignore others' experience but to use it as input rather than blueprint. Learn from best practices, but do not copy them blindly.

The Math of the Model¶

The Assumption Breakdown Framework¶

First Principles Cost Equation:

Theoretical Minimum Cost (TMC) = Raw Materials + Minimum Energy + Minimum Labor + Physical Space

Current Industry Cost (CIC) = TMC + Convention Margin + Inefficiency + Profit

Strategic Opportunity (SO) = CIC - Achievable Cost

Where Achievable Cost lies between TMC and CIC based on your strategic capability.

The P&L Structure: Cost Decomposition Analysis¶

Key Insight: SpaceX achieved roughly 50% cost reduction by attacking the 83% of cost structure that was convention, not physics.

The "Killer" Metric: Assumption-to-Principle Ratio (APR)¶

APR = Number of assumptions that survive challenge / Total assumptions tested

• APR > 0.8: Most constraints are real; optimize within them
• APR 0.5-0.8: Some opportunity for paradigm shift
• APR 0.3-0.5: Significant opportunity for disruption
• APR < 0.3: Industry ripe for first-principles disruption

Example: Zerodha Analysis

Assumptions about stock brokerage (2010):

1. Brokers need physical branches (False - digital suffices)
2. Customers need relationship managers (False - tech-savvy users don't)
3. Commission model is essential (False - volume model works)
4. Trading platforms are expensive (False - open-source alternatives)
5. Regulatory compliance requires large teams (True - irreducible)
6. Settlement requires banking relationships (True - irreducible)
7. High touch service differentiates (False - for target segment)
8. Brand trust requires history (Partially true - but can be built)

Zerodha APR = 3 surviving / 8 tested = 0.375

This low APR indicated significant disruption opportunity, which Zerodha captured.

Worked Numerical Examples¶

Example: SpaceX vs. Traditional Aerospace - Detailed Cost Breakdown

Traditional Aerospace Cost Structure (Expendable Rocket, ~$60M)

SpaceX Cost Structure (Falcon 9, ~$28M estimated FY24)

The arithmetic of first principles:

• SpaceX started from $2M in irreducible materials
• Added minimum necessary labor, testing, and overhead
• Achieved 53% cost reduction by eliminating non-essential cost
• Higher profit margin (25% vs 10%) despite lower price

Sources: SpaceX investor presentations, NASA Commercial Crew cost analyses, industry analyst reports (Based on founder interviews and industry analyst consensus for detailed breakdowns)

Example: Zerodha vs. Traditional Broker - Revenue Model Math

Traditional Discount Broker (India, 2010)

Margin: Rs. (200) to Rs. 2,800 per customer

Zerodha Model (Launched 2010)

Margin: Rs. 800 per customer (67% margin)

Why This Math Works:

1. Zero delivery commission attracts users: Lower revenue per user, but near-zero acquisition cost
2. F&O traders are high-frequency: They pay Rs. 20 per trade x many trades
3. Technology replaces labor: Rs. 150 tech cost vs. Rs. 2,300 branch + RM cost
4. Scale economics compound: Each additional user costs Rs. 400, not Rs. 3,200

Result (FY24):

Sources: Zerodha annual reports FY24, NSE market share data, SEBI registered broker data

Sensitivity Analysis: What Changes If Assumptions Differ?¶

Key insight: First principles disruption works best when raw materials/irreducibles are a small percentage of current cost. The larger the "soft" cost (conventions, margins, inefficiencies), the greater the opportunity.

Case Studies¶

Case Study 1: SpaceX's Cost Structure Reimagination (Global)¶

Context and Timeline

2001: Elon Musk attempts to buy Russian ICBMs for Mars missions. Price: $8 million each, but Russians kept raising price.

2002: Musk does first-principles analysis of rocket costs. Discovers raw materials are ~2% of rocket cost.

2002: SpaceX founded with goal of 10x cost reduction in launch costs.

2008: Falcon 1 becomes first privately-funded liquid-fuel rocket to reach orbit (fourth attempt).

2010: Falcon 9 first launch. NASA Commercial Crew contract awarded.

2015: First successful landing of orbital rocket booster (first stage).

2024: SpaceX launching roughly twice per week. Starship in active development.

Strategic Decisions Made

First Principles Diagnosis:

Traditional aerospace assumed rockets were inherently expensive because:

• Rockets have always been expensive
• Aerospace is a mature industry
• Smart engineers have optimized for 60 years
• Government contracts reward cost-plus behavior

Musk's first principles analysis revealed:

• Raw materials are 2% of cost
• Manufacturing processes were optimized for government cost-plus contracts
• Component prices included enormous supplier margins
• Rockets were treated as disposable when physics did not require it

Guiding Policy: Vertical integration + reusability + iterative development

Coherent Actions:

1. Vertical Integration: SpaceX manufactures 80%+ of components in-house, including engines (Merlin, Raptor), avionics, structures, and fairings. This eliminates supplier margins and enables rapid iteration.

2. Reusability: First-stage boosters are designed to land and be reused. This was considered impossible by aerospace consensus. Physics disagreed - landing requires fuel mass penalty but enables 10x+ reduction in per-launch cost.

3. Iterative Development: Rather than traditional aerospace's "test to perfection, then fly," SpaceX "tests by flying." Starship prototypes have exploded repeatedly - this is intentional learning.

4. Commercial Focus: Serving commercial customers (satellite operators) rather than just government created price pressure that drove efficiency.

5. Talent Acquisition: Recruited from video game industry (simulation), automotive (manufacturing), and software (iteration speed), not just aerospace.

Financial Data

Source: NASA OIG reports, SpaceX investor presentations, FAA launch data

Outcome and Lessons

SpaceX is now the world's most valuable private company (~$350B valuation, 2024). It has fundamentally changed the economics of space access.

Key lessons:

1. First principles unlock opportunity others cannot see. Aerospace veterans "knew" rockets had to be expensive. They were wrong.
2. Vertical integration enables first principles. You cannot redesign what you do not control.
3. Reusability was a paradigm shift, not an optimization. This was not making existing rockets 10% better; it was changing the fundamental model.
4. Iteration beats perfection. SpaceX's willingness to fail publicly accelerated learning.

Sources:

• Vance, A. (2015). Elon Musk: Tesla, SpaceX, and the Quest for a Fantastic Future. Ecco Press.
• NASA Office of Inspector General, "NASA's Management of Crew Transportation" (2019)
• SpaceX investor presentations (2020, 2023)
• FAA Office of Commercial Space Transportation, launch statistics

Case Study 2: Zerodha's Zero-Brokerage Model (Indian)¶

Context and Timeline

2000s: Indian stockbroking dominated by full-service brokers (ICICI Direct, Kotak, HDFC) charging 0.5-1% brokerage plus hidden fees.

2010: Nithin Kamath founded Zerodha with zero brokerage for delivery trades and flat Rs. 20 for intraday/F&O.

2010-2015: Slow growth as market remained skeptical. Competitors dismissed model as unsustainable.

2015-2019: Rapid acceleration as demonetization and digital payments drove online trading.

2020: COVID-19 lockdowns create retail trading boom. Zerodha becomes India's largest broker by active clients.

2024: Zerodha has 13+ million customers, 15%+ market share, and ~Rs. 8,320 Cr revenue with 56.5% PAT margins.

Strategic Decisions Made

First Principles Diagnosis:

Nithin Kamath, himself a trader, asked: "Why do brokers charge per-trade commissions?"

Conventional answer: "That's how brokers have always made money."

First principles analysis:

• Executing a trade costs the broker approximately Rs. 2-5 in technology and settlement costs
• The incremental cost of each trade is near zero once infrastructure is built
• Brokerage commissions exist because customers accepted them, not because they reflected cost
• The broker's cost structure was primarily branch network and relationship managers, not trade execution

Guiding Policy: Eliminate all costs that do not directly enable trading. Pass savings to customers as zero/low brokerage. Monetize through volume and ancillary services.

Coherent Actions:

1. Zero Delivery Brokerage: Free equity delivery trades. This was unprecedented and attracted price-sensitive retail investors.

2. Flat Fee F&O: Rs. 20 per trade regardless of size. This attracted high-volume F&O traders who were Zerodha's most profitable segment.

3. In-House Technology: Built Kite (trading platform), Console (back office), and other tools internally. Technology cost Rs. 150/customer vs. licensed platforms at Rs. 500+.

4. No Branch Network: 100% digital. Zero physical branches. Zero relationship managers.

5. Education Content: Zerodha Varsity provides free financial education. This built trust and reduced support costs (educated users need less help).

6. Word-of-Mouth Marketing: Near-zero marketing spend. Growth driven by referrals from satisfied customers.

Financial Data

Source: Zerodha annual reports, NSE market share data, Ministry of Corporate Affairs filings

Why Incumbents Could Not Respond

ICICI Direct's rational response to Zerodha would have been to cut prices 70% while also closing branches and laying off relationship managers. This would have destroyed short-term profits, angered existing customers who valued branch access, and created labor relations problems. The response was strategically blocked.

Outcome and Lessons

Zerodha is now India's most profitable brokerage with the highest market share among active traders. It achieved this with ~1,500 employees vs. 10,000+ at traditional brokers.

Key lessons:

1. First principles questioning unlocks new business models. "Why do we charge commissions?" led to "What if we didn't?"
2. Technology enables first principles models. Without modern web/mobile platforms, Zerodha's model was impossible.
3. Founder experience provides authentic diagnosis. Nithin Kamath was a trader; he understood trader needs better than bank executives.
4. Counter-positioning prevents incumbent response. Traditional brokers' cost structures made matching Zerodha's pricing suicidal.

Sources:

• Zerodha Annual Reports FY18-FY24
• NSE Market Share Reports
• Kamath, N. (various). Zerodha blog posts on company history
• The Ken, "Zerodha's profits are unreal" (2022)

Case Study 3: Digital Transformation Failures - Copying Without Understanding (Global/Indian Mix)¶

Context and Timeline

2015-2020: "Digital transformation" becomes the most common strategic initiative in corporate strategy. McKinsey reports 70% of digital transformations fail.

The pattern: Company sees competitor or startup succeeding with digital. Company launches "digital transformation" initiative. Company invests in technology. Technology fails to deliver expected results. Company declares "execution problem."

Case A: GE Digital (Global)

2011-2018: GE invests $4 billion in GE Digital, attempting to become a "digital industrial company."

The analogy: "Amazon built a cloud platform. We should too."

The flaw: Amazon built AWS from internal capability (running Amazon.com). GE was trying to build a platform without the internal customer that drove Amazon's development.

2018: GE Digital effectively abandoned. $4 billion written off.

Case B: Indian Banking "Digital" Initiatives (Indian)

2015-2020: Multiple Indian banks launch "digital banks" as separate brands.

Examples: Kotak 811, HDFC Bank PayZapp, SBI YONO

The analogy: "Fintech startups are digital-first. We should create digital-first brands."

The flaw: Creating a new app does not change the bank's core processes, regulatory constraints, or cost structure. The digital brands faced the same unit economics as the parent bank with additional marketing costs.

Result: Most digital banking initiatives are absorbed back into parent banks or run at losses.

Case C: Traditional Retailer E-commerce (Global/Indian)

Pattern: Traditional retailer launches e-commerce to compete with Amazon/Flipkart.

The analogy: "Amazon is an online store. We will create an online store."

The flaw: Amazon is not an online store. Amazon is a logistics and technology company that happens to sell products. The competitive advantage is in supply chain, not in having a website.

Indian example: Future Group's Big Bazaar Direct, Reliance's JioMart (version 1.0), various regional retailer e-commerce attempts.

Result: Most fail or struggle. Unit economics of e-commerce (delivery cost, returns) were not solved by launching a website.

Why These Failures Share a Pattern

All three failures resulted from analogical reasoning without first principles analysis:

The First Principles Questions They Should Have Asked:

1. What is the successful company actually doing? (Not just "being digital")
2. What capabilities enable their success? (Technology is usually not the answer)
3. What is their cost structure, and why is it different from ours?
4. What would we have to change fundamentally to achieve similar economics?
5. Is the change worth the cost, given our existing business?

Financial Data

Outcome and Lessons

The "digital transformation" graveyard is filled with companies that copied without understanding.

Key lessons:

1. Analogy is not analysis. "They did X, so we should do X" is not strategy.
2. Technology is rarely the differentiator. The differentiator is usually business model, capabilities, or cost structure.
3. First principles reveals what you actually need to change. It is usually more than buying software.
4. "Bolt-on digital" does not work. If the core business model does not support digital economics, adding digital just adds cost.

Sources:

• McKinsey, "Why do most transformations fail?" (2018)
• Financial Times, "GE's $4bn bet on digital" (2018)
• The Ken, multiple articles on Indian digital banking (2019-2022)
• Company annual reports and investor presentations

Indian Context¶

First Principles Thinking in Indian Business¶

The Advantage of "Fresh Eyes"

Indian entrepreneurs often have an advantage in first principles thinking: they are not burdened by decades of "the way things are done" in mature industries.

When Bhavish Aggarwal started Ola in 2010, there was no established ride-hailing playbook in India. He had to reason from first principles about what Indian consumers needed (cash payment options, auto-rickshaws, not just cars).

When Byju Raveendran started BYJU'S, Indian ed-tech had no established model. He reasoned from first principles about how Indian students actually learn (video content in vernacular, at own pace, with gamification).

The Constraint of "Indian Conditions"

However, Indian entrepreneurs also face a trap: assuming "Indian conditions" make certain approaches impossible.

First principles questions to ask:

• Is this constraint actually based on physics/economics, or is it regulatory/cultural?
• If regulatory, might regulation change? Should we prepare for that future?
• If cultural, is the culture actually changing (especially in younger demographics)?
• Are we solving for India of 2010 or India of 2030?

Example: Zerodha's First Principles Approach to Indian Markets

Zerodha's zero-brokerage model was initially dismissed as impossible in India:

• "Indian investors need hand-holding" - First principles: Do tech-savvy young Indians need hand-holding?
• "Zero revenue cannot sustain a business" - First principles: What if costs are also near-zero?
• "Regulators won't allow it" - First principles: Is zero brokerage illegal? (No, it is not.)

Regulatory First Principles¶

Indian businesses must conduct first principles analysis of regulation:

Question 1: What does the regulation actually say vs. what does industry assume it says?

Many Indian regulatory constraints are industry convention, not regulatory requirement. SEBI does not mandate brokerage charges. RBI does not mandate branch networks for all banking services.

Question 2: What is the regulation protecting, and is that protection still needed?

Many regulations were designed for a pre-digital era. Understanding their purpose helps predict whether they will change.

Question 3: What can we do within current regulation that no one else is doing?

Often, first principles analysis reveals that the regulatory space allows more innovation than industry practice suggests.

Strategic Decision Framework¶

When to Use First Principles Thinking¶

Decision Tree: First Principles vs. Analogy¶

flowchart TD
    Start["START: Strategic question requires analysis"]
    Q1{"Is the industry undergoing fundamental change<br/>(technology, regulation, consumer behavior)?"}
    Q2{"Are competitors with different<br/>business models succeeding?"}
    Q3{"Is this a high-stakes,<br/>hard-to-reverse decision?"}
    Q4{"Is the analogous situation genuinely similar<br/>in relevant dimensions?"}

    FP1["First principles required.<br/>Analogies to past may mislead."]
    FP2["First principles required.<br/>Your model may be obsolete."]
    FP3["First principles analysis as validation,<br/>even if analogy suggests answer."]
    FP4["First principles required.<br/>Surface similarity may hide deep differences."]
    Analog["Analogy appropriate but<br/>verify key assumptions."]

    Start --> Q1
    Q1 -->|YES| FP1
    Q1 -->|NO| Q2
    Q2 -->|YES| FP2
    Q2 -->|NO| Q3
    Q3 -->|YES| FP3
    Q3 -->|NO| Q4
    Q4 -->|YES| Analog
    Q4 -->|NO| FP4

Common Mistakes and How to Avoid Them¶

Mistake 1: First Principles as Excuse to Ignore Experience¶

Error: "We are reasoning from first principles, so we do not need to study what others have done."

Why wrong: First principles thinking does not mean ignoring data. It means not being constrained by conventional interpretation of data. You should study others' experience intensively - then question whether their conclusions are necessary.

How to fix: Study best practices thoroughly, then challenge each element. "Why is this done this way?" for every practice.

Mistake 2: Confusing "Different" with "First Principles"¶

Error: "Our approach is different from the industry, so it must be first principles."

Why wrong: Different can be random or wrong. First principles means different because fundamental analysis reveals a better path.

How to fix: Articulate the specific assumptions challenged and the first principles that support your approach. If you cannot, you are just guessing.

Mistake 3: Over-Applying First Principles to Stable Domains¶

Error: Trying to reason from first principles about everything, including well-solved problems.

Why wrong: First principles analysis is expensive. For stable, well-understood domains, convention usually reflects accumulated wisdom. Reinventing accounting methods or legal compliance wastes resources.

How to fix: Reserve first principles for strategic questions where convention may be wrong. Use analogy for well-solved problems.

Mistake 4: Ignoring Why Conventions Exist¶

Error: "This is just convention, so we can ignore it."

Why wrong: Conventions often exist for reasons. They may be outdated reasons, but understanding them prevents repeating past mistakes.

How to fix: Before discarding a convention, understand its origin. "Why did this practice develop? Does the original reason still apply?"

Mistake 5: Confusing Theoretical Possibility with Practical Achievability¶

Error: "First principles says this is possible, so we will do it."

Why wrong: First principles reveals theoretical limits, not what your organization can actually achieve. SpaceX could pursue reusability because of specific engineering capabilities. Not every company can.

How to fix: After first principles analysis reveals opportunity, assess whether you have the capabilities to capture it. Gap between theory and your capability is real.

Mistake 6: Analysis Paralysis¶

Error: Breaking down every assumption endlessly without acting.

Why wrong: First principles analysis is a tool for better decisions, not a substitute for decisions. At some point, you must commit.

How to fix: Set analysis boundaries. Identify the 3-5 most important assumptions. Challenge those. Accept others provisionally.

When to Stop: Rules for First Principles Analysis¶

First principles thinking can become an infinite regress. Here are concrete stopping rules:

Stop When You Hit Physics or Economics

Decomposition Chain Example (Delivery Costs):

Why is delivery expensive?
→ Labor + Fuel + Vehicles

Why is labor expensive?
→ Time per delivery × Wage rate

Why does delivery take time?
→ Distance × Speed + Stop time

Why can't speed increase indefinitely?
→ Traffic, safety, physics (STOP: physical constraint)

Why can't wages decrease indefinitely?
→ Minimum wage, labor market (STOP: economic/regulatory constraint)

The Five Stopping Signals:

Practical Stopping Heuristics:

1. The "So What?" Test: If challenging the next assumption wouldn't change your decision, stop.

2. The 10x Rule: Only decompose assumptions where 10x improvement is theoretically possible. Optimizing a 2% cost component rarely matters.

3. The Decision Deadline: Set a time limit. First principles with a 2-week deadline forces prioritization.

4. The Capability Gate: If you lack the capability to exploit a first principles insight, further analysis is academic.

5. The "Already Optimized" Check: If smart people have worked on this for decades (e.g., lithium-ion battery chemistry), assume remaining gains are incremental, not 10x.

Red Flags You've Gone Too Far:

• You're analyzing assumptions that affect <5% of the problem
• Your team is debating philosophy rather than business
• Analysis has continued for >2 weeks without actionable insight
• You're challenging well-established scientific consensus
• The opportunity cost of continued analysis exceeds potential insight value

The goal is insight for action, not complete decomposition. Perfect analysis of the wrong problem is worse than imperfect analysis of the right one.

Action Items¶

Exercise 1: Industry Cost Decomposition¶

Take your industry's cost structure. Break it down to raw materials, labor types, facilities, and overhead. Calculate what percentage of current cost is "irreducible" (materials, minimum labor) vs. "convention" (historical practices, margins, inefficiencies).

Exercise 2: Assumption Inventory¶

List 10 "facts" that everyone in your industry believes. For each, ask: "Is this based on physics/economics, or is it based on 'how we have always done it'?" Challenge at least 3.

Exercise 3: The Blank Sheet Test¶

If you were starting your company today with no legacy, what would you do differently? Write down the top 5 differences. For each, identify what prevents you from making that change now.

Exercise 4: Mental Model Application¶

Take a current strategic question. Apply 5 different mental models from the list of 20. What does each model reveal that the others miss?

Exercise 5: Competitor First Principles¶

Choose a successful competitor or disruptor in your industry. Reverse-engineer their first principles analysis. What assumptions did they challenge that you have accepted?

Exercise 6: Best Practices Audit¶

List your organization's "best practices." For each, identify its origin, its original purpose, and whether that purpose still applies. Mark practices that are continued from inertia rather than logic.

Exercise 7: The Zero-Based Question¶

For one significant cost category, ask: "If we had zero budget for this, what would we absolutely need to spend?" The difference between your answer and current spend is convention.

Exercise 8: First Principles Business Model Design¶

Design a competitor to your own company using first principles. Assume no legacy constraints. What would they do? This is your potential disruptor - and your opportunity.

Key Takeaways¶

1. First principles thinking asks "What is fundamentally true?" rather than "What has been done before?" This unlocks opportunities invisible to conventional thinkers.

2. Most industry "facts" are conventions, not principles. Raw materials and physics are principles. Pricing, processes, and practices are often conventions that can be changed.

3. Analogical reasoning works in stable environments and fails during disruption. Know which environment you are in.

4. The Assumption Breakdown Framework systematically identifies opportunity. State belief, list assumptions, challenge each, identify true principles, reason up.

5. Mental models accelerate first principles analysis. Twenty models in your toolkit enable rapid pattern recognition while maintaining rigor.

6. "Best practices" converge competitors and prevent differentiation. Ask "best questions" instead.

7. SpaceX and Zerodha demonstrate first principles at scale. Both identified that 90%+ of industry cost was convention, not physics, and built businesses attacking that gap.

One-Sentence Chapter Essence: First principles thinking strips away convention to reveal opportunity that analogical thinkers cannot see.

Red Flags & When to Get Expert Help¶

Red Flags Indicating First Principles Analysis Is Needed¶

1. "That's just how our industry works" - Convention masquerading as law
2. Competitors with 80%+ lower costs succeeding - They found principles you missed
3. "Our costs are industry-standard" - No one examined if the standard makes sense
4. New entrants ignoring "rules" and winning - Rules were conventions, not principles
5. Margins declining but no clear reason - Business model may be obsolete
6. "We need to be more innovative" without specific direction - No diagnosis of what to change

When to Get Expert Help¶

• Deep technical domains: When first principles require specialized knowledge (physics, chemistry, regulation)
• Capital-intensive experiments: When testing first principles conclusions requires significant investment
• Regulatory complexity: When challenging conventions may have compliance implications
• Organizational transformation: When first principles analysis reveals need for fundamental change

References¶

Primary Sources¶

1. SpaceX investor presentations (2020, 2023)
2. Zerodha Annual Reports FY18-FY24
3. NASA Office of Inspector General reports on commercial space
4. SEBI and NSE market data on brokerage industry

Secondary Sources¶

1. Vance, A. (2015). Elon Musk: Tesla, SpaceX, and the Quest for a Fantastic Future. Ecco Press.
2. The Ken, "Zerodha's profits are unreal" (2022)
3. McKinsey, "Why do most transformations fail?" (2018)
4. Financial Times, GE Digital coverage (2017-2019)

Academic Sources¶

1. Rumelt, R.P. (2011). Good Strategy Bad Strategy. Crown Business.
2. Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.
3. Munger, C. (1994). "A Lesson on Elementary, Worldly Wisdom." USC Business School speech.
4. Thiel, P. (2014). Zero to One. Crown Business.

Data Sources¶

1. FAA Office of Commercial Space Transportation, launch statistics
2. NSE Monthly Market Reports
3. Company annual reports (GE, Future Group, HDFC Bank)

Related Chapters¶

• Chapter 1: What Strategy Actually Is - Strategy fundamentals that first principles supports
• Chapter 3: Strategic Analysis Frameworks - Applying first principles to systematic analysis
• Chapter 4: Developing Strategic Intuition - Building pattern recognition from first principles
• Chapter 17: Disruption Theory - First principles applied to market disruption

Navigation¶

Connection to Other Chapters¶

Prerequisites¶

• Chapter 1 (What Strategy Actually Is): Understanding the strategy kernel helps apply first principles to strategic questions specifically.

Related Chapters¶

• Chapter 3 (Strategic Frameworks): Frameworks can be used to structure first principles analysis
• Chapter 4 (Strategic Intuition): Pattern recognition complements first principles with experience-based insight
• Chapter 6 (Business Model Design): First principles analysis directly informs business model choices
• Chapter 9 (Competitive Dynamics): Understanding how competitors can/cannot respond to first principles innovations

Next Recommended Reading¶

Chapter 3: Strategic Analysis Frameworks - A Critical Review - to understand how traditional frameworks can structure analysis while avoiding their limitations.