The Efficacy System
engage.re answers the question: "What's actually working - and how do we know?"
Whether you're tackling a crisis, addressing an issue or unlocking an opportunity, see - in real time - which strategies, projects, and teams are delivering outcomes at every level from your neighbourhood to the planet.
How It Works
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Communities gather around a shared issue - housing, climate, education, health, anything that matters.
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They set measurable goals - specific, trackable outcomes that define what "better" looks like.
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Anyone can contribute via strategies, projects, and teams - and see in real time what's moving the needle.
The Core Metaphor: Tide & Boats
The Gap (98) represents natural improvement, external factors, and untracked causes. This honesty is a feature, not a bug.
You're looking at youth unemployment in Manchester. The community has set a clear goal: 500 young people into employment by year-end. You see 4 strategies targeting this goal. One is outperforming the others by 3x. You click in - it's a mentorship model. Inside, 3 projects are running it, each with their own teams. You can see who's delivering, what's working, and how you can help.
What engage.re Is - and Isn't
engage.re IS NOT
- A replacement for official statistics or population data.
- Claiming that X definitely caused Y.
If engage.re shows "500 unemployed in Hackney", it means 500 tracked users - not the actual unemployment rate.
What Gets Measured
Outcome Tracking
"Who helped produce this change in the world?"
When people find employment or air quality sensors show improvement - when goals are being achieved - we show which strategies and projects contributed.
See: Tracking and Attribution
Input Equity
"What has each team member contributed to this initiative?"
Track time, money, knowledge, and other resources that participants invest - enabling fair recognition and equity distribution.
See: Equity
The Foundation: Contribution Analysis
Based on John Mayne's methodology (1999), used by UNDP, IUCN, and major foundations worldwide.
In complex systems, proving that X caused Y is often impossible. Too many factors interact in unpredictable ways.
Contribution analysis asks instead: "Was X a plausible contributor to Y?" - both more honest and more useful for decision-making.