58 lines
2.3 KiB
Markdown
58 lines
2.3 KiB
Markdown
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# Chapter 7: Finding a New Purpose
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## Core Focus
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Validating the evolution axis of Wardley Maps through research, and discovering that evolution can be measured (but not time-predicted).
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## Purpose Requirements
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Meaningful purpose requires three elements:
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- Clear objective
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- Defined scope
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- Moral imperative
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## The Evolution Breakthrough
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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.
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### The Discovery
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Analyzing thousands of publications revealed predictable language pattern shifts:
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- Articles progress: "wonder" -> construction -> operation/features -> everyday use
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- This linguistic evolution indicates increasing certainty about an activity
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- Activities evolve through multiple diffusion waves of improving versions, not single S-curves
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## Evolution Curve: Ubiquity vs. Certainty
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Rather than time or adoption %, evolution tracks how **widespread AND certain** an activity becomes:
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- Genesis -> Custom-built -> Product -> Commodity -> Utility
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## Diffusion vs. Evolution
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Critical distinction:
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- **Diffusion**: adoption of specific innovations over time
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- **Evolution**: changing nature of an activity across multiple improving versions
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Activities don't follow predictable timelines but follow predictable paths.
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## Supply vs. Demand Competition
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Two forces drive evolution:
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- **Demand**: useful activities spread (ubiquity driver)
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- **Supply**: providers improve activities (certainty driver)
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## Chain of Needs
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Maps extend beyond single organizations, connecting supplier needs -> user needs -> end-consumer needs. Misalignment between these creates conflict.
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## Key Insight
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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.
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## Key Takeaways
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1. Evolution is measurable but not time-predictable - you know *what* will happen, not *when*
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2. Understanding landscape context prevents strategic mismatch
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3. Activities follow consistent evolutionary paths regardless of time or adoption rates
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4. Maps are useful models, not reality - windows on wider systems
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5. Revenue should flow from meeting user needs, not extracting value
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