wardley/ch07-finding-a-new-purpose/SUMMARY.md

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Chapter 7: Finding a New Purpose

Core Focus

Validating the evolution axis of Wardley Maps through research, and discovering that evolution can be measured (but not time-predicted).

Purpose Requirements

Meaningful purpose requires three elements:

  • Clear objective
  • Defined scope
  • Moral imperative

The Evolution Breakthrough

Initial assumptions proved wrong: evolution doesn't correlate with adoption percentages or time. "When 10% adopt something, it becomes a product" doesn't hold across technologies.

The Discovery

Analyzing thousands of publications revealed predictable language pattern shifts:

  • Articles progress: "wonder" -> construction -> operation/features -> everyday use
  • This linguistic evolution indicates increasing certainty about an activity
  • Activities evolve through multiple diffusion waves of improving versions, not single S-curves

Evolution Curve: Ubiquity vs. Certainty

Rather than time or adoption %, evolution tracks how widespread AND certain an activity becomes:

  • Genesis -> Custom-built -> Product -> Commodity -> Utility

Diffusion vs. Evolution

Critical distinction:

  • Diffusion: adoption of specific innovations over time
  • Evolution: changing nature of an activity across multiple improving versions

Activities don't follow predictable timelines but follow predictable paths.

Supply vs. Demand Competition

Two forces drive evolution:

  • Demand: useful activities spread (ubiquity driver)
  • Supply: providers improve activities (certainty driver)

Chain of Needs

Maps extend beyond single organizations, connecting supplier needs -> user needs -> end-consumer needs. Misalignment between these creates conflict.

Key Insight

Many "innovations" are predictable consequences of evolution, not accidents. Amazon EC2 wasn't a surprise - utility computing was inevitable once computing became sufficiently certain and widespread.

Key Takeaways

  1. Evolution is measurable but not time-predictable - you know what will happen, not when
  2. Understanding landscape context prevents strategic mismatch
  3. Activities follow consistent evolutionary paths regardless of time or adoption rates
  4. Maps are useful models, not reality - windows on wider systems
  5. Revenue should flow from meeting user needs, not extracting value