# 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