Pragmatic Governance

Pragmatic Governance

Evaluate every proposal, policy, or strategy by one criterion: Does it work? Learn from others who have solved similar problems. Abandon approaches that fail regardless of their theoretical elegance.

When to Use

• Evaluating policies or decisions by results rather than ideology
• Cutting through theoretical debates to practical outcomes
• Choosing between multiple approaches with different philosophical foundations
• When a proposal sounds good but you're uncertain it will work
• User asks "How do I make this work?" or "Theory vs. practice"

Inputs

The Lee Kuan Yew Framework

Lee Kuan Yew governed Singapore with radical pragmatism: "I was never a prisoner of any theory. What guided me were reason and reality. The acid test I applied to every theory or scheme was: Would it work?"

Why Pragmatic Governance Works

1. Reality is the test: Elegant theories that fail in practice serve no one. Messy solutions that work serve everyone.

2. Others have gone before: "I discovered early in office that there were few problems confronting me in government which other governments had not met and solved."

3. Ideologies blind: Commitment to any "-ism" prevents seeing clearly what the situation actually requires.

4. Adaptation is survival: What worked yesterday may not work tomorrow. The pragmatist adjusts; the ideologue fails.

The Key Insight

"The acid test is in performance, not promises."

Good intentions count for nothing. Impressive theories count for nothing. Only results matter.

The Results Test

Step 1: Strip Away the Theory

What is actually being proposed? Separate the philosophy from the mechanism. A proposal can have bad philosophy and good mechanics, or good philosophy and bad mechanics.

Ask:

• What would this actually do in practice?
• What behavior would it incentivize?
• What are the second and third-order effects?

Step 2: Find Precedents

Who has faced this problem before? How did they solve it? How well did it work?

The Lee Method: "I made a practice of finding out who else had met the problem we faced, how they had tackled it and how successful they had been. Whether it was to build a new airport or to change our teaching methods, I would send a team of officers to visit and study those countries that had done it well. I preferred to climb on the shoulders of others who had gone before us."

Ask:

• Where has this been tried?
• What actually happened?
• What can we learn from both successes and failures?

Step 3: Test Against Human Nature

Assume people will act in their self-interest. Will this proposal still work?

The Incentive Test:

• If people behave selfishly, does this still produce good outcomes?
• If enforcement is imperfect, does this collapse?
• What behavior does this reward? What does it punish?

Step 4: Evaluate Adaptation Requirements

How will this need to change as circumstances change?

Ask:

• What assumptions does this depend on?
• How will we know if it's working?
• What triggers should cause us to adjust?
• Are we committing to a method or an outcome?

Step 5: Make the Decision

Choose based on expected results, not theoretical appeal.

Criteria:

• Highest probability of achieving desired outcomes
• Most robust to human nature and imperfect implementation
• Most adaptable to changing circumstances
• Supported by precedent where available

Techniques

1. The Borrow-and-Adapt Methodology

Don't invent when you can learn.

Process:

1. Identify the core problem
2. Research who has solved similar problems
3. Study their approaches and results
4. Adapt the best elements to your context
5. Test and iterate

2. The Ideology Audit

Check if ideology is clouding judgment.

Questions:

• Would I evaluate this differently if it came from the "other side"?
• Am I defending this because it works or because I believe in the principle?
• What would I think if the results were the same but the philosophy opposite?

3. The Pre-Mortem

Assume the proposal has failed. Why?

Process:

1. Imagine implementation is complete and results are poor
2. Identify the most likely causes of failure
3. Assess whether the proposal addresses these risks
4. Modify or reject based on findings

4. The Incentive Map

Trace who benefits and who loses under the proposal.

Map:

• Who gains from compliance?
• Who gains from non-compliance?
• Who enforces? What's their incentive to enforce?
• Where are the weak points?

Workflow

Step 1: Gather and Review Inputs

Collect all relevant information:

• Review the provided data and context
• Identify key parameters and constraints
• Clarify any ambiguities or missing information
• Establish success criteria

Step 2: Analyze the Situation

Perform systematic analysis:

• Identify patterns and relationships
• Evaluate against established frameworks
• Consider multiple perspectives
• Document key findings

Step 3: Generate Recommendations

Create actionable outputs:

• Synthesize insights from analysis
• Prioritize recommendations by impact
• Ensure recommendations are specific and measurable
• Consider implementation feasibility

Output Format

## Pragmatic Governance Analysis

### The Proposal
[What is actually being proposed, stripped of philosophy]

### Precedent Research
- **Similar cases:** [Where has this been tried?]
- **Results:** [What actually happened?]
- **Lessons:** [What can we learn?]

### The Results Test
- **Expected outcomes:** [What will this actually produce?]
- **Incentive alignment:** [Does self-interest support the goals?]
- **Failure modes:** [How might this fail?]
- **Adaptation requirements:** [What will need to change over time?]

### Recommendation
[Accept / Modify / Reject with rationale based on expected results]

### If Modified
[Specific changes to improve probability of success]

### Success Metrics
[How will we know if this is working? When do we reassess?]

Constraints

• This framework is for decisions where results matter more than symbolic value
• Some situations legitimately require principled stands regardless of outcomes
• Pragmatism without values becomes mere expedience; values provide the goals, pragmatism the method
• Learning from others requires understanding context; what worked elsewhere may not work here
• Past results don't guarantee future performance; precedent informs but doesn't determine

Outputs

Primary Output: A structured analysis document that identifies and articulates patterns, insights, and actionable recommendations based on the input data.

Format:

## Analysis: [Topic]

### Key Findings
- [Finding 1]
- [Finding 2]
- [Finding 3]

### Recommendations
1. [Action 1]
2. [Action 2]
3. [Action 3]

Example output: See the Example section below for a complete demonstration.

Example

Input: "Our company is debating between a fully remote work policy (some employees strongly prefer) and returning to office (some executives believe is better for collaboration). The debate has become ideological."

Output:

Pragmatic Governance Analysis

The Proposal

Two competing approaches to work location: fully remote vs. full return to office. The question has become philosophical ("the future of work" vs. "real work happens in person") rather than empirical.

Precedent Research

• Similar cases: Companies that went fully remote (GitLab, Automattic) vs. those that mandated return (Goldman Sachs, Apple). Hybrid implementations (Microsoft, Salesforce).
• Results: Fully remote companies report strong results but are self-selected for remote-compatible cultures. Mandated returns have faced significant resistance and attrition. Hybrid models show mixed results depending on implementation.
• Lessons: No single model is universally superior. Success depends on: nature of work, company culture, implementation quality, and measurement rigor.

The Results Test

• Expected outcomes:

  • Full remote: Higher retention of remote-preference employees, lower real estate costs, potential collaboration challenges, geographic talent access
  • Full office: Higher retention of office-preference employees, potential collaboration benefits, higher real estate costs, limited talent pool
  • Hybrid: Moderate outcomes on all dimensions, complexity in coordination

• Incentive alignment:

  • Employees will choose based on their own productivity and preference, not company benefit
  • Managers may resist remote oversight difficulty
  • No natural alignment between individual and organizational interest

• Failure modes:

  • Remote: Collaboration decay, culture erosion, management difficulty
  • Office: Talent attrition, resentment, productivity loss from commute
  • Hybrid: Coordination overhead, unequal treatment, worst of both worlds

• Adaptation requirements: Any policy must be adjustable based on results; measuring the right outcomes is critical

Recommendation

Modify the framing. This is not an ideology question; it is an empirical question. Different roles may have different optimal arrangements.

Recommended approach:

1. Categorize roles by collaboration requirements (high/medium/low)
2. Set default policies by category while allowing exceptions
3. Define clear metrics: productivity (output-based), collaboration (project completion, innovation metrics), retention
4. Run for six months with quarterly reviews
5. Adjust based on data, not philosophy

The executives who believe office is better and employees who believe remote is better are both making untested assumptions. Test them.

Success Metrics

• Output metrics by role category in each arrangement
• Retention rates across groups
• Collaboration project velocity
• Employee satisfaction (weighted appropriately)

Reassess policy quarterly. Be willing to change based on results.

Integration

This skill is part of the Lee Kuan Yew expert persona. Lee governed for 31 years by one principle: what works matters more than what sounds good. He borrowed from capitalism, socialism, and Confucianism without loyalty to any, because his loyalty was to results.

The acid test is in performance, not promises.