Wellbeing Policy Design Guide — Embedding Subjective Well-Being in Public Policy

Introduction

GDP rises, yet residents are no happier. This question has been driving policymakers around the world.

The OECD's Better Life Index, Bhutan's GNH (Gross National Happiness), the United Kingdom's shift toward a Wellbeing Economy — the movement to place "quality of life," which economic indicators alone cannot capture, at the center of policy has moved well beyond the experimental stage. In Japan, the Cabinet Office launched its "Survey on Satisfaction and Quality of Life" in 2021, and at the municipal level, Arakawa Ward's GAH (Gross Arakawa Happiness) stands as a pioneering initiative.

Yet a significant gap exists between "measuring wellbeing" and "making policy based on wellbeing." Indicators are designed but never connected to policy. Surveys are conducted but never reflected in budget allocation. This guide presents a practical framework and methodology for bridging that gap.

Why This Approach Is Needed

The Limits of Conventional KPIs

Municipal master plans typically rely on indicators that measure administrative outputs: park area, childcare facility capacity, number of consultations handled. But parks exist while elderly residents remain isolated. Childcare slots increase while anxiety about child-rearing persists.

Output indicators make administrative effort visible, but they do not reflect how residents' lives have actually changed. Wellbeing indicators bridge the gap between "what the administration does" and "how residents experience their lives."

The International Trend

In 2011, the OECD published its Better Life Index, incorporating subjective indicators — life satisfaction, social connectedness, and safety — alongside income, employment, and education. In 2019, New Zealand introduced its "Wellbeing Budget," becoming the first country in the world to link budget formulation directly to wellbeing indicators.

These developments are beginning to reach Japanese municipalities as well. Toyama Prefecture formulated its "Toyama Wellbeing Indicators" in 2024 and has begun using them to set priority areas in prefectural governance.

Framework — Connecting Wellbeing Indicators to the Policy Cycle

To prevent wellbeing indicators from becoming a "measure and forget" exercise, they must be embedded within the PDCA cycle of policy. The following framework organizes the process from indicator design through policy integration in five stages.

A Three-Layer Indicator Structure

An effective wellbeing indicator system is composed of three layers:

Macro indicators alone provide weak linkage to policy; process indicators alone obscure the overall picture of wellbeing. Designing all three layers as a set is essential.

Practical Steps

Step 1: Conduct a Baseline Survey

Begin by understanding the current state of residents' wellbeing. Key points in survey design:

• Number of items: Approximately 20 to 30 questions (keeping respondent burden under 15 minutes)
• Subjective wellbeing: Life satisfaction (Cantril's Ladder), emotional balance (frequency of positive and negative affect)
• Domain-specific questions: Health status, economic security, social connectedness, living environment, sense of purpose (ikigai)
• Demographic attributes: Age, gender, area, household composition (essential for cross-tabulation)

Arakawa Ward measures GAH through an annual resident questionnaire structured around six domains: health, safety and security, social connectedness, sense of purpose, environment, and self-governance.

Step 2: Prioritize Issues

Analyze the survey results to identify which wellbeing domains present challenges. A particularly effective tool here is Importance-Satisfaction Analysis (ISA).

For each domain, ask residents how important they consider it and how satisfied they currently are, then plot the results on a scatter diagram. Domains with "high importance but low satisfaction" become priority targets for policy intervention.

Step 3: Translate into KPIs

For each identified priority, establish concrete policy KPIs. The key is to set both wellbeing indicators (outcome indicators) and administrative action indicators (process indicators).

For example, if "social connectedness" is the challenge:

• Outcome indicator: Percentage of residents who report "having someone to turn to in times of trouble"
• Process indicator: Number of community interaction hubs established; number of participants in intergenerational programs

Step 4: Implement Measures and Monitor

Implement measures based on the established KPIs. Set mid-year monitoring indicators as well, creating a structure that allows for course correction. Combining quarterly pulse surveys (approximately five questions) with annual surveys captures fluctuations that annual data alone would miss.

Step 5: Evaluate and Provide Feedback

At year-end, confirm changes in indicators and verify policy effects. A critical caution here: do not equate "improved numbers" with "successful policy." External factors — economic fluctuations, disasters, population changes — must be analyzed, and the contribution of policy assessed with care.

Common Pitfalls

1. Too Many Indicators, Blurred Focus

Adding indicator after indicator weakens the connection to policy. One or two macro indicators, five to eight domain indicators, and two to three process indicators per measure — this granularity represents the practical upper bound.

2. Survey Fatigue and Declining Response Rates

Repeating the same survey annually erodes residents' willingness to respond. The countermeasure is to feed back survey results to residents in an accessible manner. Making visible that "your voice led to this policy" is what sustains cooperation with future surveys.

3. Internal Resistance to Subjective Indicators

The response "there's no point in measuring residents' feelings" remains persistent. To overcome this resistance, presenting subjective and objective indicators in combination and demonstrating with examples that "subjective indicators capture issues invisible to objective data" is the most effective approach.

4. Unclear Causal Links Between Policy and Indicators

Because wellbeing is determined by multiple factors, establishing a causal relationship between a specific measure and indicator movement is far from straightforward. Rather than pursuing perfect causal proof, constructing "a plausible explanation grounded in a logic model" is the more practical course. See Logic Model Guide for details.

Conclusion

Wellbeing policy is not "policy that makes residents happy." It is a framework for re-examining how policy should be designed so that residents themselves can perceive an improvement in their quality of life.

Designing indicators is only the starting point. Embedding indicators within the policy cycle, making them function as the basis for budget allocation, and feeding results back to residents — when this cycle begins to turn, wellbeing policy transforms from "aspiration" to "implementation."

When combined with the evidence-based policy-making approach discussed in Introduction to EBPM, wellbeing indicators become a more robust foundation for policy. Additionally, Introduction to Systems Thinking provides an auxiliary lens for understanding the multilayered structure of wellbeing.

References

How's Life? 2024: Measuring Well-being

OECD (2024)

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満足度・生活の質に関する調査報告書 2024

内閣府 (2024)

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The Wellbeing Budget 2019

New Zealand Treasury (2019)

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荒川区民総幸福度（GAH）に関する研究

荒川区 (2023)

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