gh-lyndonkl-claude/skills/systems-thinking-leverage/resources/methodology.md

Advanced Systems Thinking & Leverage Methodology

Workflow

Copy this checklist and track your progress:

Advanced Systems Thinking Progress:
- [ ] Step 1: Advanced system mapping techniques
- [ ] Step 2: Identify system archetypes
- [ ] Step 3: Analyze multi-loop interactions
- [ ] Step 4: Model time delays and tipping points
- [ ] Step 5: Design archetype-specific interventions

Step 1: Use 1. Advanced Causal Loop Techniques for complex multi-loop systems.

Step 2: Match your system to 2. System Archetypes Library (10 common patterns).

Step 3: Apply 3. Multi-Loop Interaction Analysis to understand loop conflicts and synergies.

Step 4: Use 4. Time Delays & Tipping Points to model non-linear dynamics.

Step 5: Implement archetype-specific strategies from 5. Intervention Strategies by Archetype.

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1. Advanced Causal Loop Techniques

Link Polarity Analysis

Every link in a causal loop has polarity:

• Positive (+): Variables move in same direction (A↑ causes B↑, A↓ causes B↓)
• Negative (-): Variables move in opposite directions (A↑ causes B↓, A↓ causes B↑)

Loop polarity (overall):

• Reinforcing (R): Even number of negative links (0, 2, 4, ...) → Amplifies change
• Balancing (B): Odd number of negative links (1, 3, 5, ...) → Resists change, seeks goal

Example:

Quality → (+) → Customer Satisfaction → (+) → Referrals → (+) → New Customers → (+) → Revenue → (+) → Investment in Quality → (+) → Quality

Links: 6 positive, 0 negative → Reinforcing (growth or collapse loop)

Example:

Inventory → (-) → Gap from Target → (+) → Order Rate → (+) → Inventory

Links: 2 positive, 1 negative → Balancing (seeks target inventory level)

Nested Loops

Real systems have multiple interconnected loops:

Technique: Identify primary loop, then secondary loops that modulate it.

Example - Product Development:

R1 (Growth): Better Product → More Users → More Revenue → More Investment → Better Product

B1 (Quality Gate): Feature Count → (+) → Complexity → (+) → Bugs → (-) → User Satisfaction → (-) → Revenue

Analysis: R1 drives growth, but B1 limits it if quality isn't maintained. High-leverage intervention: Strengthen B1 by making complexity visible earlier (information flow).

Variable Typology

Exogenous (external) - Low leverage, must adapt | Stock (accumulates) - High leverage but slow | Flow (rate) - Medium leverage | Policy (rule) - High leverage

Strategic focus: Intervene on policies (high leverage) rather than stocks (slow) or exogenous variables (uncontrollable).

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2. System Archetypes Library

Overview

System archetypes are recurring patterns across different domains. Recognizing them provides:

• Predictable failure modes
• Known high-leverage interventions
• Time-tested solutions

Ten Common Archetypes:

Archetype 1: Fixes That Fail

Pattern: Quick fix addresses symptom → Problem temporarily improves → Unintended consequence worsens problem → Need for fix increases

Structure:

• R loop: Problem → Quick Fix → Symptom Relief (immediate)
• B loop (delayed): Quick Fix → Unintended Consequence → Problem (long-term)

Example: Crunch time → Ship features → Technical debt → Slower development → More crunch time

High-leverage intervention: Address root cause (realistic scheduling, refactoring time), not symptom (work hours)

Warning sign: Solutions that work initially but need repeating at increasing frequency

Archetype 2: Shifting the Burden

Pattern: Symptomatic solution (easy, fast) vs. Fundamental solution (hard, slow) → Symptomatic solution chosen repeatedly → Capability for fundamental solution atrophies → Dependency on symptomatic solution increases

Structure:

• B1 (quick): Problem → Symptomatic Solution → Problem (temporary relief)
• B2 (slow): Problem → Fundamental Solution → Problem (lasting fix)
• R (addictive): Use of Symptomatic Solution → Atrophy of Fundamental Solution Capability

Example: Hire contractors (symptomatic) vs. Build internal capability (fundamental) → Internal capability declines → More contractor dependency

High-leverage intervention: Invest in fundamental solution while gradually reducing symptomatic solution. Don't cut symptomatic cold-turkey.

Warning sign: "We keep throwing money at this problem" or "We can't function without [workaround]"

Archetype 3: Eroding Goals

Pattern: Performance gap → Pressure → Lower goal instead of improving performance → Gap closes (temporarily) → Lowered expectations become new normal

Structure:

• B1 (easy): Gap → Lower Goal → Gap Closes
• B2 (hard): Gap → Improve Performance → Gap Closes

Example: Team velocity declining → Lower sprint commitment → "New normal" → Capability erodes further

High-leverage intervention: Anchor goals to external standard (customer needs, market), not internal capability. Make goal erosion visible.

Warning sign: "Let's be more realistic" becoming repeated refrain

Archetype 4: Escalation

Pattern: A's actions threaten B → B retaliates → A feels more threatened → A escalates → B escalates → Spiral

Structure: Two reinforcing loops feeding each other

Example: Team A adds abstraction to isolate from Team B → Team B adds abstraction to protect from A → Integration cost explodes

High-leverage intervention: One party unilaterally de-escalates (paradigm shift from competitive to cooperative)

Warning sign: "Arms race" dynamics, tit-for-tat retaliation

Archetype 5: Success to the Successful

Pattern: A and B compete for resource → A gains slight advantage → Resource flows to A → A's advantage grows → B starved → Winner-take-all

Structure: Two reinforcing loops, one winning

Example: Successful product gets more investment → More features, marketing → More success. Failing product starved → Decline accelerates

High-leverage intervention: Diversification rules (minimum investment per option), explicit exploration budget

Warning sign: "Betting on winners" strategy leading to monoculture

Archetype 6: Tragedy of the Commons

Pattern: Shared resource → Each actor maximizes individual gain (rational) → Resource depletes → Everyone suffers

Structure: Multiple reinforcing loops (individual gains) deplete shared stock

Example: Shared codebase → Each team adds dependencies → Build time/complexity explodes → Everyone slowed

High-leverage interventions:

• Information flow: Make total resource usage visible to all users
• Rules: Usage limits, quotas, or pricing
• Self-organization: Enable collective governance

Warning sign: "Prisoner's dilemma" dynamics, externalities not accounted for

Archetype 7: Limits to Growth

Pattern: Reinforcing loop drives growth → Hits limiting constraint → Growth slows or reverses

Structure:

• R (growth): Success → Investment → More Success
• B (limit): Success → Resource Constraint → Slows Success

Example: Viral product growth → Support overwhelmed → Bad experience → Negative word-of-mouth → Growth reverses

High-leverage intervention: Anticipate limit before hitting it. Invest in expanding constraint proactively.

Warning sign: S-curve growth pattern, "growing pains"

Archetype 8: Growth and Underinvestment

Pattern: Growth → Need for capacity → Underinvestment (cost-cutting) → Performance degrades → Lower growth

Structure: R loop (growth) weakened by inadequate investment in capacity

Example: Customer growth → Need more support staff → Hire slowly to control costs → Service quality drops → Churn increases

High-leverage intervention: Invest ahead of demand (leading indicator), not reactively

Warning sign: Chronic capacity shortages, "doing more with less" leading to quality drops

Archetype 9: Accidental Adversaries

Pattern: A's actions inadvertently harm B → B takes protective action that harms A → Cycle repeats

Structure: Two balancing loops that conflict

Example: Engineering builds for technical elegance → Product complains features take too long → Engineering feels constrained, quality drops → Product complains about bugs

High-leverage intervention: Make interdependence visible. Joint success metrics. Communication.

Warning sign: Silos blaming each other, misaligned incentives

Archetype 10: Rule Beating

Pattern: Rule created to achieve goal → Rule becomes target → Gaming behavior optimizes for rule, not goal → Goal not achieved

Structure: B loop seeks rule compliance, not goal achievement (Goodhart's Law: "When measure becomes target, it ceases to be a good measure")

Example: "Close 10 tickets/day" KPI → Developers close easy tickets, defer hard ones → Customer problems unsolved

High-leverage intervention: Tie metrics to actual goals (outcomes), not proxies (outputs). Multi-dimensional metrics.

Warning sign: "Teaching to the test", optimizing metrics while performance declines

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3. Multi-Loop Interaction Analysis

Loop Dominance

In systems with multiple loops, ask:

1. Which loop is dominant now? (Drives current behavior)
2. Which loop will dominate next? (After current limit hits)
3. What shifts dominance? (Trigger conditions)

Example - Startup:

• Early stage: R loop (product-market fit → growth) dominant
• Scale stage: B loop (operational complexity → slow down) becomes dominant
• Mature stage: B loop (market saturation → plateau) dominates

Intervention timing: Strengthen next-dominant loop before transition (build ops capability before scaling hits)

Loop Conflict vs. Synergy

Conflict: Loops work against each other

• Example: R1 (ship fast) vs. B1 (maintain quality) → Tension
• Resolution: Higher-order goal that integrates both (sustainable velocity)

Synergy: Loops reinforce each other

• Example: R1 (learning improves skill) + R2 (skill improves confidence) → Virtuous cycle
• Leverage: Activate both loops simultaneously

Archetype Combinations

Real systems often combine archetypes:

Fixes That Fail + Shifting the Burden:

• Quick fix becomes symptomatic solution
• Fundamental solution capability atrophies
• Dependency deepens

Example: Manual workarounds (quick fix) prevent automation investment (fundamental) → More manual work needed → Less time for automation

Intervention: Reserve capacity for fundamental solutions (20% time, dedicated team)

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4. Time Delays & Tipping Points

Types of Delays

Delay Type	Description	Example	Impact on System
Physical	Material transport, construction	Shipping, building	Predictable, manageable
Information	Data collection, reporting	Metrics lag, surveys	Can reduce with better systems
Decision	Analysis, approval cycles	Committee reviews	Process improvement opportunity
Perception	Recognition that change occurred	"This isn't working" realization	Most dangerous - causes premature abandonment

Perception delays are most problematic because people conclude "intervention failed" before effects manifest.

Mitigation: Set realistic timelines. Track leading indicators. Communicate expected delays upfront.

Tipping Points

Definition: Threshold where small additional change causes large, often irreversible shift in system state.

Warning signs of approaching tipping point:

• Non-linear acceleration (change rate increasing)
• Increased variability (system becoming unstable)
• Slower recovery from perturbations (resilience declining)
• Bifurcation signs (system choosing between two stable states)

Example - Team Morale:

• Stable state: High morale, productive
• Tipping point: Key person leaves, others question staying
• New stable state: Low morale, attrition spiral

Intervention strategies:

• Preventive: Increase buffer before tipping point (resilience)
• Early warning: Monitor leading indicators (voluntary turnover, engagement scores)
• Circuit breaker: Automatic intervention if approaching threshold

Stock-Induced Oscillations

Pattern: Stock accumulates → Corrective action taken → Overcompensation due to delay → Stock depletes → Opposite action → Oscillation

Example - Hiring:

Backlog accumulates (3 months) → Hire burst → Training delay (6 months) →
Meanwhile backlog shrunk → Overstaffed → Layoffs → Cycle repeats

Fix:

1. Reduce information delays (real-time backlog metrics)
2. Smooth flow adjustments (hire steadily, not in bursts)
3. Increase stock buffers (reduce sensitivity to fluctuations)

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5. Intervention Strategies by Archetype

Strategy Matrix

Archetype	Low-Leverage (Avoid)	High-Leverage (Prioritize)
Fixes That Fail	Keep applying fix harder	Address root cause; make unintended consequences visible early
Shifting Burden	Cut symptomatic solution cold-turkey	Invest in fundamental while gradually reducing symptomatic
Eroding Goals	Accept lower standards	Anchor goals externally; make goal erosion visible and costly
Escalation	Match escalation	Unilateral de-escalation; shift to cooperative paradigm
Success to Successful	"Back the winner" harder	Enforce diversity (quotas, exploration budget)
Tragedy of Commons	Appeal to altruism	Make usage visible; add usage rules; enable self-governance
Limits to Growth	Push growth harder	Anticipate limit proactively; invest in expanding constraint ahead
Growth & Underinvestment	Cut costs to preserve margins	Invest ahead of demand (leading indicators)
Accidental Adversaries	Optimize local metrics	Joint metrics; make interdependence visible; align incentives
Rule Beating	Add more rules and enforcement	Tie metrics to actual goals (outcomes not outputs); multi-dimensional

Leverage Point Tactics by Level

Level 12 (Parameters) - Weak:

• Tactic: Adjust numbers (budget +10%, salary +5%)
• When useful: Temporary relief, testing hypotheses
• Limitation: Competitors match, effects fade

Level 9 (Delays) - Medium:

• Tactic: Speed up feedback (daily standups vs. monthly reviews)
• When useful: System is stable, faster feedback helps
• Limitation: Too-fast feedback can destabilize (overreaction)

Level 6 (Information Flows) - Strong:

• Tactic: Show consequences to decision-makers (developers see support tickets their code causes)
• When useful: Information asymmetry causing bad decisions
• Limitation: Requires action authority, not just visibility

Level 5 (Rules) - Strong:

• Tactic: Change incentives (team outcomes vs. individual metrics)
• When useful: Behavior misaligned with goals
• Limitation: Can be gamed (Rule Beating archetype)

Level 3 (Goals) - Very Strong:

• Tactic: Redefine system purpose ("maximize learning" vs. "minimize failures")
• When useful: Current goal produces perverse outcomes
• Limitation: High resistance (threatens identity)

Level 2 (Paradigms) - Strongest:

• Tactic: Shift mental models ("employees are costs" → "employees are investors of human capital")
• When useful: Deep cultural/strategic transformation needed
• Limitation: Hardest to change, requires patience and evidence

Intervention Sequencing

For complex systems, sequence interventions:

Phase 1: Stabilize (Balancing loops)

• Stop the bleeding (address immediate crises)
• Strengthen balancing loops that prevent collapse
• Reduce destabilizing delays

Phase 2: Improve (Parameters, Flows)

• Optimize current structure
• Improve information flows
• Adjust parameters for better performance

Phase 3: Transform (Structure, Goals, Paradigms)

• Redesign stock-flow structures
• Change system goals
• Shift underlying paradigms

Example - Turnaround:

1. Stabilize: Stop cash burn (balancing loop), reduce critical bugs (prevent churn)
2. Improve: Speed up deployment (reduce delay), improve customer feedback flow (information)
3. Transform: Shift from "ship features fast" to "solve customer problems sustainably" (goal/paradigm)

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6. Modeling Techniques

Behavior Over Time (BOT) Graphs

Purpose: Visualize how variables change over time to reveal patterns.

Technique:

1. Select key variables (stocks and critical flows)
2. Plot expected trajectory (time on X-axis, value on Y-axis)
3. Mark intervention points
4. Show multiple scenarios (baseline, with intervention)

Patterns to look for:

• Exponential growth/decay: Dominant reinforcing loop
• S-curve: Growth hitting limit
• Oscillation: Delayed balancing loops (stock-induced)
• Overshoot and collapse: Reinforcing growth + hard limit + delay
• Steady state: Balanced flows

Scenario Planning with Systems Thinking

Use cases: Long-term strategy, uncertainty, multiple futures

Process:

1. Identify key uncertainties (which exogenous variables could vary?)
2. Create scenarios (2-4 plausible futures based on uncertainty combinations)
3. Map each scenario's dominant loops (which archetypes activate?)
4. Design robust strategy (works across scenarios) or adaptive strategy (pivot points)

Example - Market Uncertainty:

• Scenario A (High demand): Limits to Growth archetype → Invest in capacity ahead
• Scenario B (Low demand): Eroding Goals archetype → Maintain quality standards
• Robust strategy: Flexible capacity (cloud vs. data center), core quality processes that scale up/down

Reference Modes

Definition: Generic behavior patterns used to diagnose systems.

Common reference modes:

• Linear growth: Constant flow, no feedback
• Exponential growth: Unconstrained reinforcing loop
• S-curve growth: Reinforcing loop hits balancing loop (limit)
• Overshoot and oscillation: Growth with delayed balancing loop
• Overshoot and collapse: Growth, hard limit, insufficient recovery

Diagnostic use: Match your system's actual behavior over time to reference mode → Infer loop structure → Identify leverage points

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7. Advanced Leverage Tactics

Counterintuitive Interventions

System thinking often reveals surprising leverage points:

1. Slow down to speed up

• Reduce deployment frequency → Allow time for quality → Fewer rollbacks → Faster net progress
• Paradox: Balancing loop (quality) strengthens reinforcing loop (learning)

2. Weaken feedback to enable change

• Reduce real-time monitoring during experimentation → Allow failure → Learning increases
• Paradox: Too-strong balancing loops prevent exploration

3. Strengthen delays strategically

• Add cooling-off period before decisions → Reduce impulsive actions → Better outcomes
• Paradox: Delay usually bad, but prevents overreaction oscillations

4. Reduce efficiency to increase resilience

• Maintain slack capacity (not 100% utilized) → Buffer against shocks → Faster recovery
• Paradox: "Waste" increases long-term throughput

Multi-Stakeholder Systems

Challenge: Different actors see different loops (paradigm diversity).

Technique - Participatory Modeling:

1. Bring stakeholders together
2. Each draws their view of the system (causal loops)
3. Integrate into unified map (reveals blind spots)
4. Identify conflicts (where loops oppose)
5. Find synergies (where loops align)
6. Design interventions that work for all

Benefit: Shared mental model → Aligned interventions → Less resistance

Adaptive Leverage

Principle: Leverage points shift as system evolves.

Example - Product Lifecycle:

• Early stage: Paradigm/goals leverage (define what product does)
• Growth stage: Stock-flow structure leverage (scale architecture)
• Maturity stage: Information/rules leverage (optimize operations)
• Decline stage: Goals leverage (pivot or exit)

Implication: Revisit leverage analysis periodically. Yesterday's high-leverage point may be low-leverage today.

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8. Common Pitfalls in Advanced Systems Thinking

Paralysis by analysis - Fix: Time-box, start simple (3-5 variables), iterate Missing dominant loop - Fix: Identify which loop explains 80% of behavior Ignoring paradigms - Fix: Ask "what mental model drives this?" Overcomplicating - Fix: Start simple, add complexity only if needed Confusing archetype with reality - Fix: Archetypes are lenses, not laws Static thinking - Fix: Use behavior-over-time graphs, model evolution Intervention without testing - Fix: Pilot small, monitor, adapt