REFORM
A uniform rule rarely produces uniform effects.
A rule meets unequal situations. What public decision-making calls an exception is often, on the ground, the most frequent case. That gap is what determines acceptability and effectiveness.
- 01RULE
- 02REAL CONSTRAINT
- 03CAPACITY TO ADAPT
- 04DIFFERENTIATED EFFECTS
- 05ACCEPTABILITY
- 06EFFECTIVENESS
02 — WHAT THIS DECISION ACTUALLY CHANGES
What actually moves.
A rule turns an abstract constraint into a concrete one, different depending on each person's resources.
Opposition does not always come from disagreement in principle: it comes from the practical impossibility of complying.
Support measures shift acceptability more than the wording of the rule does.
03 — WHAT MUST BE SIMULATED
What must be simulated.
- The real distribution of the situations covered by the rule
- The populations with no capacity to adapt within the planned timeframe
- The effect of exemptions, waivers and support measures
- The gap between expected effect and obtained effect
04 — POPULATIONS CONCERNED
Populations concerned.
- Populations directly constrained by the rule
- Intermediate populations, able to adapt at a cost
- Audiences not concerned but attentive to the fairness of the scheme
- Agents and institutions in charge of applying the rule
05 — MECHANISMS TO OBSERVE
Mechanisms to observe.
- Real constraint and room for manoeuvre
- Differentiated capacity to adapt
- Sense of fairness between comparable situations
- Non-take-up and exit from the scheme
- Acceptability over time
06 — EXAMPLE QUESTIONS TO TEST
Questions to test.
- “Who cannot comply?”
- “Which effects does the rule produce outside its target?”
- “Which support measure changes acceptability?”
These formulations are examples of testable decisions. They do not report on any executed simulation.
07 — REAL CASE STUDIES
Decisions already tested.
- PUBLIC POLICY“ How can a ZFE be deployed in a metropolitan area without triggering a revolt among workers living on the outskirts? ”3.2M residents · 28 car-use profiles · 24 months
- SOCIAL PROGRAMS“How can the RSA support pathway be redesigned around stronger contractual commitments without increasing non-take-up among the most vulnerable groups?”340,000 benefit-receiving households · 36 months of trajectories
- SOCIAL PROGRAMS“How can the departmental APA program be redesigned to preserve aging at home under budget constraints?”28,000 people supported at home · 36-month projection
- SOCIAL PROGRAMS“How can support for young people leaving child welfare be designed to prevent a break in support at age 21?”4,800 young people affected each year · 12 profiles · 60 months
- PUBLIC POLICY“ Anticipate reactions to tighter unemployment-benefit conditions. ”4.2M jobseekers · 16 typologies · 18 months
- FINANCIAL SERVICES“How can we anticipate private clients' reception of the new MIF II regime?”340,000 private-banking customers · 6 reaction typologies · 24 months
08 — HOW IMAGINE ALL THE PEOPLE SIMULATES
The method applied to this decision.
- Building a population that reflects the real diversity of situations.
- Applying the rule as it would be experienced, constraints included.
- Comparing several variants: timeframes, thresholds, waivers, support measures.
- Reading the differentiated effects and the zones of failure.
Explore another decision
- LaunchTest what will drive adoption — or rejection — of something new.
- PriceUnderstand what a price change actually transforms in people's behaviour.
- RepositionChange perception without destroying the value that was already there.
- TransformChange an existing system without triggering the side effects that cancel out the expected benefit.
- ArbitrateCompare several possible futures before making a decision that is hard to reverse.
- AnticipateExplore what can happen when behaviours evolve over time.
- ReactTest a response when time, trust and cascading reactions become critical.
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