PUBLIC POLICY
Test a public decision
before it divides.
Ministries, public agencies, local authorities: test your reforms, action plans and structural decisions on coherent populations of citizens, users and constituents, before announcement or implementation.
THE THESIS — CARDINAL PROMISE
A public policy is never judged on its rationality. It is judged on what it triggers: in the social fabric, in territories, in anger, in silence.
Our system lets you see what your decision will trigger, before you have announced it.
CASE STUDY — MINISTRY OF THE ECONOMY AND ECOLOGICAL TRANSITION
“ How do you introduce a progressive carbon tax on fuel without triggering a new social crisis? ”
Simulated on 8.2 million working French people who use personal vehicles · 24 territories with distinct socio-economic structures · 56 compensation schemes tested
The climate objective requires a continuous increase in carbon taxation on fuel. The obstacle isn't technical: it's political. Any announcement lacking compensations perceived as “fair” triggers a social revolt. The state knows the measure is necessary. It doesn't know how to present it without breaking the coalition that theoretically supports it.
The ministry must decide: expanded fuel voucher, territorial exemption, income-based indexing, vehicle conversion incentive? With what sequencing? With what messaging? Without reviving the “punitive ecology against rural residents and the middle class” narrative.
What the system revealed
The rejection isn't fiscal, it's symbolic.
The workers who reject carbon taxation most violently aren't those who would pay the most. They are those who don't feel part of the ecological transition: those who feel the transition is being decided without them, against them, in Paris. Financial compensation isn't enough: the sense of political exclusion must be repaired.
The national fuel voucher backfires in rural areas.
A uniform national fuel voucher gets 62% acceptance in urban areas and 32% in rural areas. Why? Because it's read as “a symbolic handout” to keep taxing. The same amount, framed as a “territorial mobility bonus” and rolled out at the departmental level, gets 71% acceptance in the same rural areas.
The order of announcement determines 80% of acceptance.
Announcing the tax before the compensations triggers a media crisis in 87% of simulated scenarios. Announcing the compensations before the tax (even three weeks earlier) flips the narrative: the tax becomes “the funding for a fair mobility plan,” not “a punishment that comes with a bandage.”
What Imagine All The People did that no one else could have done
Our system surveyed 9,600 synthetic citizens across the 24 target territories, tested 56 compensation schemes in variable combinations, and simulated media and political cascades over 12 weeks for each scenario. The “compensations announced first + territorial bonus + prefectoral dialogue” strategy dominates 21 of 24 territories.
No polling institute can test 56 schemes across 9,600 territorialized profiles. No think tank can project media cascades over 12 weeks. No classic citizen consultation can brainstorm unprecedented political scenarios.
- NATIONAL ACCEPTABILITY
- 41% → 67%with recommended strategy
- RISK OF MAJOR SOCIAL CRISIS
- −78%vs direct announcement
- POLITICAL COST AVOIDED
- highimpact on executive approval rating and opposition rebound
APPLICATIONS
Three uses for public policy.
Structural reforms
Test a pension reform, tax reform, labor law, or public health reform before its announcement. Identify segments that adhere, those that flip, those that block, and the compensation levers that redistribute acceptability.
Mobilization & transition
Calibrate the messaging of an ecological plan, an inclusion program, or a prevention policy. Identify the audiences to mobilize, those who will drop off, and the sequencing that sustains the coalition over time.
New regulation
Anticipate real behaviors in response to a regulation coming into force: environmental constraints, traffic restrictions, professional obligations, control mechanisms. Detect disproportionate friction and unintended effects before rollout.
METHODS
Three ways to test a decision.
Comparing what a synthetic-population simulation brings against existing methods.
| AI PERSONAS | TRADITIONAL SURVEYS | IMAGINE ALL THE PEOPLE |
|---|---|---|
| SCALE | ||
| 5 to 10 fixed personas | 500 to 2,000 respondents | Up to 10 million coherent individuals |
| DYNAMICS | ||
| Frozen characteristics | Pre-written questions, static answers | Agents that ask, probe and brainstorm |
| TIME HORIZON | ||
| Assumed current state | Snapshot of the present | Projection of future consequences |
| DEPTH | ||
| One synthetic answer | Aggregated statistical tables | Individual dialogue + collective analysis |
| DATA & SOVEREIGNTY | ||
| Limited demographic data · US public cloud | Personal data collected at scale · Public cloud | Zero personal data · Infrastructure in France · On-premise possible |
OTHER CASES
Three other decisions tested in this sector.
LOCAL AUTHORITY — LOW-EMISSION ZONE
“How do you roll out a low-emission zone in a metropolitan area without triggering a revolt among peripheral workers?”
Simulated on 3.2 million residents of the metropolitan area · 28 vehicle-use profiles
The rejection doesn't come from owners of old vehicles: they are resigned. It comes from self-employed workers and home care providers who cross the zone several times a day and cannot electrify their vehicle within 18 months. A scheme dedicated to this 4% of the population resolves 78% of the political conflict.
- OVERALL ACCEPTABILITY
- 38% → 64%
- RISK OF PROFESSIONAL BLOCKADES
- −71%
MINISTRY — UNEMPLOYMENT INSURANCE REFORM
“Anticipating reactions to tighter unemployment benefit conditions.”
7 reform scenarios tested · 42 dynamic follow-ups on social and union friction points
Jobseekers don't reject stricter conditions as such: they reject the insufficient support that makes them unreachable. Pairing any tightening with a massive reinforcement of personalized counseling flips the narrative: the reform becomes “demanding but supported” instead of “punitive.”
- JOBSEEKER ACCEPTANCE
- 22% → 51%
- RISK OF MAJOR UNION CONFLICT
- −54%
AGENCY — RURAL MOBILITY PLAN
“Anticipating adoption of a shared mobility plan in low-density areas over 5 years.”
Projection over 60 months of behavioral change · 11 typologies of relationship to rural solo-driving
Adoption isn't linear: it comes in waves, triggered by signal events (service closure, fuel price increase, arrival of a new operator). The strategy that maximizes adoption isn't the one that promotes the service from day zero, but the one that prepares the waves to absorb demand when the signal events occur.
- ADOPTION AT 5 YEARS
- 12% → 34%
- COST OF POORLY-TIMED ROLLOUT
- +EUR 18M
METHOD — PUBLIC POLICY
A fifteen-minute study.
How a test runs on our system, from the brief to the delivered study.
1
You formulate your decision
A question in plain language, phrased the way you would phrase it in the executive committee. No formalism required.
2
The system builds the populations
Target segments are reconstructed from public aggregates and industry data. No personally identifying data enters the system.
3
The agents interview, discuss, brainstorm
The system runs the interviews itself, probes friction points, and proposes alternative scenarios you had not considered.
4
You explore the study
You talk with individual voices, challenge the reasoning, change the decision and watch the impact in real time.
Your next decision
Which decision do you want to explore?
Describe your need. We can point you to the right level of support.
