Tier 2

sya - Systems Analysis

Systems Analysis

Input: $ARGUMENTS

Interpretations

Before executing, identify which interpretation matches the user’s input:

Interpretation 1 — Diagnose a system producing bad outcomes: The user has a system (organization, market, process) that is behaving badly and wants to understand the underlying feedback structures causing the problem. Interpretation 2 — Predict intervention effects: The user is considering changing something in a complex system and wants to trace how that change will propagate through feedback loops before committing. Interpretation 3 — Map an unfamiliar system: The user needs to understand how a complex system works — its key variables, feedback loops, and archetypes — before making any decisions about it.

If ambiguous, ask: “I can help with diagnosing why a system is producing bad results, predicting how a proposed change will ripple through a system, or mapping out how an unfamiliar system works — which fits?” If clear from context, proceed with the matching interpretation.

Overview

Analyze complex systems using causal loop diagrams, stock and flow models, feedback loop identification, and system archetypes

Steps

Step 1: Define system boundary

Establish what is inside and outside the system:

  1. IDENTIFY THE PROBLEM/BEHAVIOR:

    • What behavior are we trying to understand?
    • What is the problem symptom?
    • What pattern do we observe over time?
      • Growth (exponential, linear, S-curve)
      • Decline (gradual, rapid, oscillating)
      • Oscillation (boom-bust, cycles)
      • Equilibrium (stable, stuck)

  2. DEFINE SYSTEM BOUNDARY:

    • What elements are “in” the system?
    • What is treated as external (given)?
    • Time horizon: How far back and forward to consider?

    Include in boundary:

    • Elements that directly cause the behavior
    • Elements affected by the behavior
    • Elements involved in feedback loops

    Exclude from boundary:

    • Elements that are truly external (weather, laws)
    • Elements too distant to matter
    • Elements we cannot influence at all

  3. IDENTIFY KEY VARIABLES: List the important quantities that change:

    • Stocks: Things that accumulate (inventory, reputation, skills)
    • Rates: Things that flow (sales per day, hires per month)
    • Auxiliary: Factors that influence but don’t accumulate

  4. ESTABLISH TIME SCALE:

    • What is the dominant time constant?
    • Days, weeks, months, years?
    • This affects what feedback matters

Step 2: Map causal relationships

Create a causal loop diagram showing cause-effect relationships:

NOTATION:

  • Arrow: A → B means “A affects B”
    • sign: Same direction (A increases, B increases)
    • sign: Opposite direction (A increases, B decreases)

PROCESS:

  1. Start with the problem variable
  2. Ask: “What directly affects this?”
  3. Draw arrows from causes to effects
  4. For each arrow, determine polarity (+/-)
  5. Ask: “Does this effect feed back to earlier causes?”
  6. Continue until major relationships are mapped

CAUSAL LINK TYPES:

Positive link (+): Same direction

  • “Higher prices → Higher revenue” (+) [if demand holds]
  • “More training → Higher skill” (+)
  • “More customers → More word-of-mouth → More customers” (+)

Negative link (-): Opposite direction

  • “Higher prices → Lower demand” (-)
  • “More inventory → Less urgency to order” (-)
  • “More workload → Lower quality” (-)

DIAGRAM ELEMENTS:

  • Boxes or labels for variables
  • Arrows showing direction of causation
  • +/- signs on arrows showing polarity
  • R/B labels for feedback loops (added in next step)

QUALITY CHECKS:

  • Each link has clear causal mechanism
  • Polarity is correct (test: if A doubles, what happens to B?)
  • No missing intermediate variables
  • Important delays are noted

Step 3: Identify feedback loops

Find and classify feedback loops in the causal structure:

LOOP IDENTIFICATION:

  1. Start at any variable
  2. Follow arrows until you return to the starting variable
  3. This is a feedback loop
  4. Classify the loop type

LOOP TYPES:

REINFORCING LOOP (R): Self-reinforcing, exponential

  • Count the negative signs in the loop
  • EVEN number of negatives (or zero) = Reinforcing
  • Creates exponential growth OR exponential decline
  • “Vicious cycle” or “Virtuous cycle”

Example: Compound Interest Savings → (+) Interest Earned → (+) Savings This is reinforcing: growth begets more growth

Example: Bank Run Fear → (+) Withdrawals → (+) Bank Instability → (+) Fear Reinforcing: fear creates more fear

BALANCING LOOP (B): Goal-seeking, stabilizing

  • ODD number of negative signs = Balancing
  • Seeks equilibrium, resists change
  • Creates oscillation if delays exist
  • “Checks and balances”

Example: Thermostat Temperature Gap → (+) Heating → (+) Temperature → (-) Temperature Gap This is balancing: seeks the goal temperature

Example: Market Price Price → (-) Demand → (-) Inventory → (-) Price Balancing: price adjusts to clear inventory

FOR EACH LOOP:

  1. Name the loop (descriptive)
  2. Classify as R (reinforcing) or B (balancing)
  3. Describe the behavior it drives
  4. Note any significant delays in the loop
  5. Assess loop strength (dominant or secondary?)

Step 4: Model stocks and flows

Identify accumulations (stocks) and rates of change (flows):

STOCKS: Things that accumulate over time

  • Physical: Inventory, cash, equipment
  • Intangible: Reputation, skills, relationships
  • Informational: Knowledge, data, backlog

Properties of stocks:

  • Change gradually (can’t jump instantly)
  • Create memory in the system
  • Create delays between cause and effect
  • Can only change through flows

FLOWS: Rates that change stocks

  • Inflows: Add to the stock
  • Outflows: Remove from the stock

Stock change = Inflows - Outflows

STOCK-FLOW STRUCTURE:

[Inflow] → [STOCK] → [Outflow]

Example: Workforce [Hiring Rate] → [EMPLOYEES] → [Attrition Rate]

Example: Technical Debt [Debt Creation Rate] → [TECHNICAL DEBT] → [Debt Paydown Rate]

FOR EACH STOCK:

  1. Name the stock (noun - what accumulates)
  2. Identify inflows (what adds to it)
  3. Identify outflows (what depletes it)
  4. Estimate typical time to fill/drain
  5. Note current level (high, medium, low)

LINKING TO CAUSAL LOOPS:

  • Stocks often appear in feedback loops
  • The stock level affects the flows
  • This creates the feedback structure

Step 5: Recognize system archetypes

Identify common system behavior patterns:

ARCHETYPE 1: LIMITS TO GROWTH Structure:

  • Reinforcing loop drives growth
  • Balancing loop creates limiting constraint
  • Initially growth dominates
  • Eventually constraint dominates

Behavior: S-curve growth, then plateau or decline

Example: New product adoption

  • R: Success → Word of mouth → More customers → More success
  • B: Market saturation → Fewer remaining prospects → Slower growth

Leverage: Focus on the constraint before it bites

ARCHETYPE 2: SHIFTING THE BURDEN Structure:

  • Symptom prompts quick fix
  • Quick fix reduces symptom
  • But undermines fundamental solution
  • Dependency on quick fix grows

Behavior: Short-term improvement, long-term degradation

Example: Technical debt

  • Quick fix: Skip tests to ship faster
  • Fundamental solution: Build quality processes
  • Side effect: More bugs → more quick fixes needed

Leverage: Invest in fundamental solution; avoid quick fixes

ARCHETYPE 3: FIXES THAT FAIL Structure:

  • Fix addresses symptom
  • Unintended consequence makes problem worse
  • After delay, problem returns stronger

Behavior: Oscillation, worsening over time

Example: Firefighting mode

  • Fix: Heroic effort to solve crisis
  • Consequence: No time for prevention
  • Delay: Next crisis is worse

Leverage: Break the link to unintended consequences

ARCHETYPE 4: SUCCESS TO THE SUCCESSFUL Structure:

  • Two activities compete for resources
  • Success in one attracts more resources
  • Less resources for the other
  • Winner takes all

Behavior: One grows, other shrinks; lock-in

Example: Internal project competition

  • Successful project gets more budget
  • Other project starves
  • Eventually only “winner” survives

Leverage: Create separate resource pools; explicit portfolio balance

ARCHETYPE 5: TRAGEDY OF THE COMMONS Structure:

  • Shared resource benefits individual users
  • Each user gains by using more
  • Total use depletes the resource
  • Everyone loses

Behavior: Resource depletion, collapse

Example: Technical infrastructure

  • Each team benefits from using shared service
  • No one invests in maintenance
  • Service degrades, everyone suffers

Leverage: Regulate the commons; assign ownership; align incentives

ARCHETYPE 6: ESCALATION Structure:

  • One party acts to gain advantage
  • Other party responds to restore balance
  • First party escalates further
  • Arms race ensues

Behavior: Mutual escalation, exhaustion

Example: Price war

  • Company A cuts price
  • Company B matches
  • Company A cuts more
  • Both margins destroyed

Leverage: Refuse to play; find non-zero-sum alternatives

ARCHETYPE 7: GROWTH AND UNDERINVESTMENT Structure:

  • Growth creates demand for capacity
  • Underinvestment in capacity
  • Performance degrades
  • Demand drops, “justifying” low investment

Behavior: Growth stalls, self-fulfilling low expectations

Example: Startup scaling

  • Growth creates load on infrastructure
  • Don’t invest in scaling infrastructure
  • Site becomes slow
  • Customers leave, growth stops

Leverage: Invest ahead of demand; watch performance standards

Step 6: Identify leverage points

Find high-leverage intervention points:

LEVERAGE POINTS (from least to most powerful):

  1. CONSTANTS AND PARAMETERS Numbers: taxes, subsidies, standards Easy to change but usually low leverage Example: Adjusting price by 5%

  2. BUFFER SIZES Stabilizing stocks relative to flows Example: Increasing inventory safety stock

  3. STRUCTURE OF STOCKS AND FLOWS Physical structure of the system Example: Adding a new warehouse location

  4. DELAYS Length of delays relative to system change rate Example: Faster feedback loops

  5. BALANCING FEEDBACK LOOPS Strength of stabilizing loops Example: Stronger quality control

  6. REINFORCING FEEDBACK LOOPS Strength of growth/decline drivers Example: Reducing viral coefficient

  7. INFORMATION FLOWS Who has access to what information Example: Making performance data visible

  8. RULES OF THE SYSTEM Incentives, constraints, agreements Example: Changing how bonuses are calculated

  9. POWER TO ADD/CHANGE RULES Self-organization, evolution Example: Enabling teams to set their own processes

  10. GOALS OF THE SYSTEM Purpose and direction Example: Shifting from growth to sustainability

  11. PARADIGM/MINDSET Deep beliefs and assumptions Example: From “resources are scarce” to “abundance”

  12. TRANSCENDING PARADIGMS Not being attached to any paradigm Highest leverage, hardest to achieve

FOR THE ANALYZED SYSTEM:

  1. List potential intervention points
  2. Classify by leverage level
  3. Assess feasibility (can we actually change this?)
  4. Assess unintended consequences
  5. Prioritize: High leverage + Feasible + Low risk

Step 7: Analyze interventions

Evaluate potential interventions and predict effects:

FOR EACH POTENTIAL INTERVENTION:

  1. DESCRIBE THE INTERVENTION:

    • What specific change would be made?
    • Which leverage point does it target?
    • What mechanism do we expect?

  2. TRACE DIRECT EFFECTS:

    • What variables change immediately?
    • What is the expected direction and magnitude?

  3. TRACE FEEDBACK EFFECTS:

    • Which feedback loops are affected?
    • Do reinforcing loops amplify the change?
    • Do balancing loops counteract it?
    • How strong are these effects?

  4. CONSIDER DELAYS:

    • How long until effects are visible?
    • Will there be oscillation during transition?
    • Could we declare failure before success appears?

  5. IDENTIFY UNINTENDED CONSEQUENCES:

    • What side effects might occur?
    • Which archetypes might we trigger?
    • Who else is affected and how might they respond?

  6. COMPARE TO DOING NOTHING:

    • What happens if we don’t intervene?
    • Is the system self-correcting?
    • Is patience an option?

INTERVENTION EVALUATION:

InterventionLeverageFeasibilityTime to EffectConfidenceUnintended Risks
………………

RECOMMENDATION:

  • Which interventions should be pursued?
  • In what sequence?
  • What should we monitor to verify effects?

When to Use

  • When dealing with problems that resist simple solutions
  • When interventions seem to make things worse
  • When symptoms keep recurring despite treatment
  • For understanding organizational dynamics
  • When there are long delays between action and effect
  • For strategic planning in complex environments
  • When multiple stakeholders with conflicting goals interact
  • For understanding market dynamics and competition
  • When exponential growth or decline is observed
  • For policy analysis with broad systemic effects

Verification

  • System boundary is clearly defined
  • Causal links have clear mechanisms (not just correlations)
  • Feedback loops are correctly classified (R vs B)
  • Stocks and flows are properly distinguished
  • Relevant archetypes are identified
  • Leverage points are prioritized by actual leverage
  • Interventions are traced through feedback effects