57 lines
2.3 KiB
Markdown
57 lines
2.3 KiB
Markdown
# 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
|