Notes
Notes

Notes

Book ReviewsBook Reviews

📖 Learning Objectives

1. Start with the Customer and Work Backwards

  • Amazon’s product development begins with writing a mock press release and an FAQ, imagining the product is already launched.
  • This forces teams to think clearly, avoid feature bloat, and ensure that what they’re building truly solves a customer problem.
  • The PR/FAQ format aligns stakeholders early, revealing weak ideas before costly development begins.

2. Replacing PowerPoints with Written Narratives

  • Instead of slide decks, Amazon uses six-page memos to present ideas, strategies, or proposals.
  • Memos must be cohesive, complete, and evidence-backed, requiring authors to anticipate questions and counterarguments. Meetings begin with a silent reading period so that everyone starts with full context.
  • Writing forces clarity of thought and creates deeper, more productive conversations in meetings.

3. Institutionalise Innovation Through Repeatable Mechanisms

  • Amazon doesn’t rely on heroic individuals but builds systems that make good decisions more likely.
  • Mechanisms like the Weekly Business Review (WBR) enforce disciplined, data-driven monitoring of key metrics.
  • These mechanisms reinforce behaviours, like a WBR ensures that teams reflect regularly on performance gaps.
  • Institutional memory is preserved, and processes scale as teams and products multiply.

4. Make Better, Faster Decisions with a Type 1 vs Type 2 Framework

  • Decisions are split into:
    • Type 1: High-impact, hard to reverse - made carefully and slowly.
    • Type 2: Reversible and low-risk - made quickly with fewer layers.
  • Most decisions are Type 2, yet organisations often treat them like Type 1, slowing innovation.
  • Amazon encourages a bias for action while still protecting the integrity of big, strategic calls.

5. Embed Customer Obsession Deep in the Culture

  • “Customer Obsession” is Amazon’s first and most important leadership principle.
  • Teams constantly ask: “What’s best for the customer?” even if it means short-term sacrifice.
  • Amazon surveys customers, monitors feedback obsessively, and uses customer anecdotes in meetings.
  • This drives long-term trust and loyalty, and helps Amazon avoid complacency as it scales.

6. Build a Culture Where Data and Metrics Drive Insight

  • Every team tracks controllable input metrics, not just results.
  • Amazon is obsessed with metrics, but only meaningful ones that reflect customer value.
  • Teams identify controllable input metrics (delivery speed, error rate) that drive outcomes like customer satisfaction.
  • The WBR forces every team to justify performance with data, not excuses.
  • Measurement systems evolve over time to ensure relevance and focus.
  • Postmortems are created after operational failures (outages, service errors, bad launches).
    • A blameless document detailing:
      • What happened
      • Why it happened
      • How it was detected (or not)
      • What can be done to prevent recurrence
    • Focus is on systemic issues, not individual blame.
    • Enables organisation-wide learning and process improvement.
    • Encourages a culture of psychological safety and faster issue reporting.
    • Helps scale innovation by normalising intelligent failure and ensuring follow-through.

      • This approach turns mistakes into assets for future resilience, ensuring that failures teach the company how to operate smarter next time.

7. Invent and Simplify, Continuously

  • Simplification is considered a form of innovation, removing friction or complexity is as valuable as adding features.
  • Amazon’s teams are expected to invent on behalf of the customer, without waiting for explicit instructions.
  • Leadership reinforces a culture where failure is accepted, provided it’s smart, fast, and leads to learning.
  • Big bets like the Kindle or Prime came with significant risk, but were backed by conviction and long-term thinking.

8. Build for Scale from the Start

  • Amazon constantly looks for ways to automate, decentralise, and scale decisions (enabling teams to be independent with “two-pizza teams”).
  • Products and systems are designed to serve millions from day one.