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Thinking in Diagrams

Influence map

Systems & feedbackField guide · Systems & feedback · 2 of 6

Which things affect an outcome, before you know how each changes it?

Over variables and effects, an influence map shows influence claims, effects with no polarity until their direction is measured; their weight in dots; one central outcome; and clusters.

Marks

Section titled “Marks”
  • Influence map Variables: hours of daylight. hours of daylight
    variable
  • Influence map Variables: rainy days; days cycled; rainy days; days cycled. Claims: rainy days to days cycled (influence claim); rainy days to days cycled (causal claim, −, opposite direction). − rainy days days cycled rainy days days cycled
    polarity
  • Influence map Variables: rainy days; days cycled. Claims: rainy days to days cycled (influence claim). rainy days days cycled
    influence claim
  • Influence map Variables: bus fare; rainy days; fitness; days cycled. Claims: bus fare to days cycled (influence claim, weight 1 of 3); rainy days to days cycled (influence claim, weight 2 of 3); fitness to days cycled (influence claim, weight 3 of 3). bus fare rainy days fitness days cycled
    weight
  • Influence map: days cycled per week Central outcome: days cycled per week. Other variables: rainy days; fitness. Claims: rainy days to days cycled per week (influence claim); fitness to days cycled per week (influence claim). rainy days fitness days cycled per week
    central outcome
  • Influence map Cluster weather: rainy days; hours of daylight. weather rainy days hours of daylight
    cluster

How each mark is drawn and read: chapter 3, What the notation expresses.

A line with an arrowhead

Section titled “A line with an arrowhead”

A line with an arrowhead with no + or − is an influence claim: the variable at its tail bears on the one at its head, which way unsaid. Upgraded with a polarity where its direction is measured, it becomes a causal claim and changes, as an effect in a causal loop diagram does.

Nia’s reading for pleasure

Section titled “Nia’s reading for pleasure”
Influence map: time Nia spends reading Central outcome: time Nia spends reading. Other variables: reading level; length of the books she picks; enjoyment of reading; evenings a parent reads with her; books at home; library visits per month; screen time; hours of after-school clubs. Claims: time Nia spends reading to reading level (influence claim); reading level to length of the books she picks (influence claim); length of the books she picks to time Nia spends reading (influence claim); enjoyment of reading to time Nia spends reading (influence claim); books at home to time Nia spends reading (influence claim); screen time to time Nia spends reading (influence claim); hours of after-school clubs to time Nia spends reading (influence claim); library visits per month to books at home (influence claim); evenings a parent reads with her to enjoyment of reading (influence claim). time Nia spends reading reading level length of the books she picks enjoyment of reading evenings a parent reads with her books at home library visits per month screen time hours of after-school clubs

Eight variables bear on time Nia spends reading, five directly and three through another; every claim is drawn without a polarity, the three effects her reading log and assessments measured included (chapter 3’s Nia).

When to draw one

Section titled “When to draw one”

Draw one when many things bear on one outcome and nobody knows which way most act, when a list of causes keeps growing with no order, or when some effects are measured and others only suspected (chapter 3’s signals).

When not to draw one

Section titled “When not to draw one”

With a few influences, each acting on the outcome and none on another, a list of variables does what the map would; with one influence in question, a sentence does. Amounts and timing aren’t drawn (chapter 3, what stays informal).

Reasoning and polish

Section titled “Reasoning and polish”
  • Reasoning4 of 5
  • Polish5 of 5brain dump → weighted argument map
  1. Central outcome with direct influences
  2. Clusters, upgrades, weight and uncertainty
  3. Evidence, viewpoints, and conversion to a causal loop diagram
Section titled “Related types”
  • An influence map is converted to a causal loop diagram: its variables and causal claims carry over, and its influence claims, weights and clusters are left behind.

In this book

Section titled “In this book”
  • Chapter 3, Surfacing Influences: the central outcome, influence claims, direct and indirect influences, clusters, weight, causal claims and conversion to a causal loop diagram; exercises IM 01–05.

Sources

Section titled “Sources”
  • The Open University, Diagramming for development 2: exploring interrelationships (OpenLearn), §3.1, Influence diagram, on influence diagrams: a snapshot of what can influence a situation, two influences that run both ways drawn as two lines, and stronger influences drawn thicker.
  • Geoff Coyle, Qualitative Modelling in System Dynamics, or What Are the Wise Limits of Quantification?, keynote to the System Dynamics Society’s conference (Wellington, 1999), on influence diagrams drawn and studied without simulation, and what they are used for: a problem on one page, loops found in the diagram, and a basis for a quantified model.
  • John D. Sterman, Business Dynamics: Systems Thinking and Modeling for a Complex World (Irwin/McGraw-Hill, 2000), chapter 5, on polarity in causal loop diagrams, with §5.2.1, Causation versus Correlation.
  • George P. Richardson, “Problems with Causal-Loop Diagrams”, System Dynamics Review 2, no. 2 (1986), on what polarity does and doesn’t mean.