Surfacing Influences
Influence mapsPart I · Framing · Chapter 3 of 12 · the one chapter on influence maps
Which things affect an outcome, before you know how each changes it? An influence map shows the variables that bear on one outcome, and which bears on which, without saying which way each acts. A claim gets a direction only where its effect has been measured.
Print this chapter, with a sheet for each exercise and the answers at the back, from its PDF.
Signals you need this diagram
Section titled “Signals you need this diagram”- Many things bear on one outcome, and nobody knows which way most of them act.
- A list of causes keeps growing, with no order to it.
- People argue over which way something pushes before anyone has counted it.
- Some effects have been measured and others only suspected, and a causal loop diagram would show them alike.
Nia’s reading for pleasure
Section titled “Nia’s reading for pleasure”Nia is ten, and her parents would like her to read more for pleasure. Asked what bears on the time she spends reading, they list how well she reads, the length of the books she picks, how much she enjoys reading, the books at home, their visits to the library, her screen time, her after-school clubs, and the evenings one of them reads with her.
Her school’s reading log holds the minutes she reads each day and each book she finishes; her teacher’s assessments give her reading level each term. Over a year the two measured three effects: in terms when she logged more minutes, her level rose further; as her level rose, she picked longer books; and with a longer book on the go, she logged more minutes a day. Nothing records the rest of the list.
Her parents rank her enjoyment highest, her screen time and the length of her books next, and the books at home and her clubs lowest.
What the notation expresses
Section titled “What the notation expresses”The central outcome
Section titled “The central outcome”The central outcome is the one variable the map is drawn around: here, time Nia spends reading. Its name is double-underlined. A map has exactly one; a second outcome gets a map of its own.
Like every variable, it is a quantity that can rise or fall: time Nia spends reading, not Nia reads.
Influence claims
Section titled “Influence claims”An influence claim says that one variable bears on another, without saying which way. More screen time might mean less reading or, with books on a tablet, more. It is drawn as a solid line with an arrowhead and no + or −, from the variable that bears to the one it bears on.
Two variables that bear on each other take two claims, one each way.
Direct and indirect influences
Section titled “Direct and indirect influences”A direct influence is a claim ending at the central outcome: screen time → time Nia spends reading. An indirect influence ends at another variable and reaches the outcome through it: library visits per month reaches time Nia spends reading through books at home.
From every variable, a path of claims runs to the central outcome. A variable with no path there either gets the claim it lacks or comes off the map.
Clusters
Section titled “Clusters”A cluster holds two or more variables that share something, under a label naming what they share: books to hand holds books at home and library visits per month. It is drawn as four corner brackets, the label inside the top-left one. A variable belongs to the cluster whose brackets it sits within.
Clusters neither nest nor overlap, and the central outcome sits in none. With no continuous outline, a cluster can’t be read as a boundary, which marks what a model explains.
Weight
Section titled “Weight”Weight is an influence’s relative importance, where influences are ranked: one, two or three dots beside the middle of the claim’s line. Nia’s parents rank her enjoyment highest, so its claim carries three dots, and her clubs’ claim one.
Weight says how much, not which way or how sure. Every line is drawn alike: a thicker one means nothing.
Causal claims
Section titled “Causal claims”A causal claim says which way a change runs, by its polarity: + when the two variables move in the same direction, − when they move in opposite directions. Giving an influence claim a polarity is an upgrade; the claim keeps its ends and its weight. Taking the polarity off makes it an influence claim again.
Upgrade a claim where you can say how you know its direction. The reading log and the assessments measured three effects, each +, so those three claims are upgraded. Enjoyment, weighted highest, stays an influence claim: nothing measured it.
Conversion to a causal loop diagram
Section titled “Conversion to a causal loop diagram”A conversion carries an influence map into a new causal loop diagram. The variables and the causal claims carry over; the influence claims, weights, clusters and the central outcome’s double underline are left behind. An influence claim isn’t carried over without a polarity: in a causal loop diagram, an effect without one is unfinished.
Nia’s three causal claims close a path: more minutes, a higher level, longer books, more minutes. Declared in the causal loop diagram, the path is a loop. It has no − effects, so by the parity rule it is a reinforcing loop: a change in any of the three comes back around in the same direction.
What stays informal
Section titled “What stays informal”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: Nia’s parents think screen time cuts into her reading.
The map shows no amounts and no timing: not how many minutes screen time takes, nor when.
The bad diagram
Section titled “The bad diagram”What’s wrong with this map of turnout in a town’s local election?
Every claim carries a + or −. The council’s ward records measured only two effects: more postal votes issued, higher turnout; a longer distance to a polling station, lower turnout. The other five polarities, on rainfall, candidates, news stories, trust in the council and newcomers, are guesses drawn as findings. Converted, the map would carry all seven into a causal loop diagram.
The lab’s checks test structure, not evidence: they report this map only under a brief requiring at least one influence claim.
The corrected diagram
Section titled “The corrected diagram”Corrected, the two measured claims keep their polarities and the other five are influence claims: the same variables and the same claims, with five fewer polarities.
Labels unchanged. Claims: 5 returned to influence claims.
A count of turnout on wet and dry polling days, ward by ward, would let a third claim be upgraded.
Notation moves
Section titled “Notation moves”| Notation move | When | What it shows | Example |
|---|---|---|---|
| Mark the central outcome | You can name the one quantity in question | What the map is drawn around | time Nia spends reading |
| Draw an influence claim | One variable bears on another, its direction unmeasured | That it bears, not which way | screen time → time Nia spends reading |
| Draw an indirect influence | A variable acts on the outcome through another | The path by which it reaches the outcome | library visits per month → books at home |
| Draw a cluster and label it | Several variables share something | What they share | books to hand |
| Give a claim a weight | Influences are ranked | Relative importance | three dots on enjoyment of reading |
Upgrade a claim with + or − | Something measured the effect | Which way the change runs | reading level → length of the books she picks, + |
| Convert to a causal loop diagram | Causal claims close a path | The loop, to declare and read there | R1 reading breeds reading |
Check your understanding
Section titled “Check your understanding”Causes of tropical deforestation, redrawn
Section titled “Causes of tropical deforestation, redrawn”Redrawn from Helmut J. Geist and Eric F. Lambin, “Proximate Causes and Underlying Driving Forces of Tropical Deforestation”, BioScience 52(2), 143–150 (2002), Figure 2. © 2002 American Institute of Biological Sciences; its structure and short labels only.
Tropical deforestation, named in the figure’s title, added as the central outcome, with a claim from each of the four proximate causes; the two tiers drawn as clusters, the five underlying names ending in forces, as the source names their tier, and the last proximate cause named other causes; each line’s width, the share of the 152 cases, drawn as one dot (under a third), two or three (over two thirds); the two dashed lines labeled Feedback drawn solid; the lines within each tier, the colors and the percentages left out.
Exercises
Section titled “Exercises”Passing the checks means meeting the brief, not being right.
IM 01Cycling to work through the winter
A central outcome and its direct influences
Tomás rides nine kilometres to work and takes the bus on the days he doesn't. From October he counts the days he rides each week. The hours of daylight fall through the autumn, and the rainy days per week rise. The council is putting street lights along his route, so the length of lit route grows month by month. His office has two showers, and on busy mornings fewer are free when he arrives. His fitness, built up over the summer, makes the ride quicker. The bus fare went up in September. Nobody has measured how much any of these moves the days he rides.
The brief
- Draw at least four direct influences on days cycled per week. checked by the lab
- Draw no indirect influences: each influence claim ends at days cycled per week. checked by the lab
- Each variable is a quantity that can rise or fall: hours of daylight, not the dark. you check this
Your palette
variable influence claim central outcome
To draw in the lab, use a tablet or a larger screen. Everything else reads normally here.
Press an empty spot to add a variable and type its name. Drag a variable to move it. Select a variable or an influence claim to change it. Double-click or double-tap a variable to edit its words in place, or select it and use Rename or the fields under the canvas.
Nothing selected. Select a variable or an influence claim on the canvas, and what you can change shows here.
The tools
- Variables V
- add a variable (press an empty spot), move one (drag it), rename one (double-click it, or Rename under the canvas), or select anything.
- Influence claims E
- draw an influence claim by dragging from one variable to another.
Keys
- R reverse the selected claim
- O mark the selected variable as the central outcome, or take the mark off
- Delete delete what's selected
- Ctrl+Z undo
- Ctrl+Shift+Z redo
- Esc clear the selection
- Enter finish the words you're writing
- Esc cancel them
Keys act on the lab you last used, or on the open lab view, and never while you type.
0 of 5 checks passed; 5 pending.
- Draw at least four direct influences on days cycled per week. (Not started)
- Draw no indirect influences: each influence claim ends at days cycled per week. (Not started)
Always checked
- One central outcome (Not started)
- Every variable has a path of claims to the central outcome (Not started)
- No variable's name breaks the more test's three rules (Not started)
Written feedback
One defensible answer
It opens here once you've drawn at least one variable in the lab above. Your attempt saves as you draw.
IM 02World food prices
Influences that reach the central outcome through another variable
The FAO food price index tracks what the world pays for cereals, vegetable oils, dairy, meat and sugar. The size of the world's grain harvest sets how much is on sale, and the area in drought across growing regions cuts the harvest. Farmers spread less fertilizer when its cost climbs, and the grain harvest falls with it. Fertilizer is made and shipped with fossil fuels, so its cost follows the oil price, which also sets what it costs to move and process food. A dear barrel makes ethanol and biodiesel pay, and biofuel demand takes maize and vegetable oil off the food market. When a harvest fails, some governments ban grain exports, and the more grain under export bans, the fewer cargoes importers can bid for. The area in drought and fertilizer cost act on the index only through the grain harvest; the oil price acts on it straight and through fertilizer cost and biofuel demand.
The brief
- Draw at least four direct influences on the world food price index. checked by the lab
- Draw at least three indirect influences. checked by the lab
- Each indirect influence reaches the index through the variable it acts on. you check this
Your palette
variable influence claim central outcome
To draw in the lab, use a tablet or a larger screen. Everything else reads normally here.
Press an empty spot to add a variable and type its name. Drag a variable to move it. Select a variable or an influence claim to change it. Double-click or double-tap a variable to edit its words in place, or select it and use Rename or the fields under the canvas.
Nothing selected. Select a variable or an influence claim on the canvas, and what you can change shows here.
The tools
- Variables V
- add a variable (press an empty spot), move one (drag it), rename one (double-click it, or Rename under the canvas), or select anything.
- Influence claims E
- draw an influence claim by dragging from one variable to another.
Keys
- R reverse the selected claim
- O mark the selected variable as the central outcome, or take the mark off
- Delete delete what's selected
- Ctrl+Z undo
- Ctrl+Shift+Z redo
- Esc clear the selection
- Enter finish the words you're writing
- Esc cancel them
Keys act on the lab you last used, or on the open lab view, and never while you type.
0 of 5 checks passed; 5 pending.
- Draw at least four direct influences on the world food price index. (Not started)
- Draw at least three indirect influences. (Not started)
Always checked
- One central outcome (Not started)
- Every variable has a path of claims to the central outcome (Not started)
- No variable's name breaks the more test's three rules (Not started)
Written feedback
One defensible answer
It opens here once you've drawn at least one variable in the lab above. Your attempt saves as you draw.
IM 03An amateur football team's season
Clusters, each labeled for what its variables share
The Rovers, an amateur team, play on Sunday mornings in a county league, and their season is counted in league points. The squad size was twenty-two in September; players leaving for work or university cut it through the winter. Training attendance on Wednesday nights runs from eight to eighteen, and the players who come keep their match fitness. The players injured each week, mostly with pulled hamstrings, are fewer when match fitness is high. The coach spends half of each session on how the back four hold their line, and the training time on tactics shows in clean sheets. Team morale shows in how hard the players run in the last twenty minutes of a match, and players with low morale leave. The players at post-match socials in the clubhouse keep the team's morale up. Nobody at the club has measured how much any of these moves the points.
The brief
- Draw at least three clusters. checked by the lab
- Put every variable but league points in a cluster. checked by the lab
- Draw at least three direct influences on league points. checked by the lab
- Each cluster's label names what its variables share. you check this
Your palette
variable influence claim central outcome cluster
To draw in the lab, use a tablet or a larger screen. Everything else reads normally here.
Press an empty spot to add a variable and type its name. Drag a variable to move it. Select a variable or an influence claim to change it. Drag a cluster by its label or a corner to move it, and by the square at its corner to resize it. Double-click or double-tap a variable or a cluster's label to edit its words in place, or select it and use Rename or the fields under the canvas.
Nothing selected. Select a variable, an influence claim or a cluster on the canvas, and what you can change shows here.
The tools
- Variables V
- add a variable (press an empty spot), move one (drag it), rename one (double-click it, or Rename under the canvas), or select anything.
- Influence claims E
- draw an influence claim by dragging from one variable to another.
- Clusters C
- drag out a cluster around variables, and label it with what they share.
Keys
- R reverse the selected claim
- O mark the selected variable as the central outcome, or take the mark off
- Delete delete what's selected
- Ctrl+Z undo
- Ctrl+Shift+Z redo
- Esc clear the selection
- Enter finish the words you're writing
- Esc cancel them
Keys act on the lab you last used, or on the open lab view, and never while you type.
0 of 9 checks passed; 9 pending.
- Draw at least three clusters. (Not started)
- Put every variable but league points in a cluster. (Not started)
- Draw at least three direct influences on league points. (Not started)
Always checked
- One central outcome (Not started)
- Every variable has a path of claims to the central outcome (Not started)
- No two clusters overlap (Not started)
- Every cluster holds two or more variables (Not started)
- The central outcome sits in no cluster (Not started)
- No variable's name breaks the more test's three rules (Not started)
Written feedback
One defensible answer
It opens here once you've drawn at least one variable in the lab above. Your attempt saves as you draw.
IM 04Algal blooms in a lake
Weight, and upgrading only the influences that were measured
Lake Esk supplies drinking water to three towns, and most Augusts its surface turns green with algae. The lake authority counts the weeks of algal bloom each summer. Over ten years it has measured three things that rise and fall with them: phosphorus in farm runoff, sewage overflows per year from the towns' treatment works, and summer water temperature. Farm runoff carries about two-thirds of the phosphorus that reaches the lake, and sewage overflows most of the rest; the three warmest summers had the longest blooms. Fertilizer spread on the fields around the lake feeds the runoff, and heavy rainstorms, a few each summer, wash it into the streams. Anglers blame the shrinking area of reed beds along the shore, and boat operators blame the number of summer visitors. The authority has measured neither.
The brief
- Give each direct influence on weeks of algal bloom each summer a weight. checked by the lab
- Upgrade exactly three influences, giving each a + or −. checked by the lab
- Leave at least two influences without a + or −. checked by the lab
- Each causal claim is one the authority measured; every other claim stays an influence claim. you check this
Your palette
variable polarity influence claim weight central outcome cluster
To draw in the lab, use a tablet or a larger screen. Everything else reads normally here.
Press an empty spot to add a variable and type its name. Drag a variable to move it. Select a variable or an influence claim to change it. Drag a cluster by its label or a corner to move it, and by the square at its corner to resize it. Double-click or double-tap a variable or a cluster's label to edit its words in place, or select it and use Rename or the fields under the canvas.
Nothing selected. Select a variable, an influence claim or a cluster on the canvas, and what you can change shows here.
The tools
- Variables V
- add a variable (press an empty spot), move one (drag it), rename one (double-click it, or Rename under the canvas), or select anything.
- Influence claims E
- draw an influence claim by dragging from one variable to another.
- Clusters C
- drag out a cluster around variables, and label it with what they share.
Keys
- R reverse the selected claim
- O mark the selected variable as the central outcome, or take the mark off
- W the selected claim's weight, in turn: none, 1, 2, 3, none
- +− upgrade the selected influence claim to a causal claim; the same key again makes it an influence claim again
- Delete delete what's selected
- Ctrl+Z undo
- Ctrl+Shift+Z redo
- Esc clear the selection
- Enter finish the words you're writing
- Esc cancel them
Keys act on the lab you last used, or on the open lab view, and never while you type.
0 of 9 checks passed; 9 pending.
- Give each direct influence on weeks of algal bloom each summer a weight. (Not started)
- Upgrade exactly three influences, giving each a + or −. (Not started)
- Leave at least two influences without a + or −. (Not started)
Always checked
- One central outcome (Not started)
- Every variable has a path of claims to the central outcome (Not started)
- No two clusters overlap (Not started)
- Every cluster holds two or more variables (Not started)
- The central outcome sits in no cluster (Not started)
- No variable's name breaks the more test's three rules (Not started)
Written feedback
One defensible answer
It opens here once you've drawn at least one variable in the lab above. Your attempt saves as you draw.
IM 05An open-source project's contributors
Upgrades that close a path of causal claims, read as a causal loop diagram
Ledger is an open-source library that reads spreadsheet files, and its maintainers count its active contributors each month. Six years of the project's records show three things. Releases made while more contributors are active carry more fixes. More fixes per release bring more users, as the package registry counts them. More users bring more active contributors, since most first contributions come from someone who hit a bug in their own work. The three run in a circle: active contributors, fixes per release, users, and back to active contributors. The maintainers believe newcomers stay when their first change is reviewed within a week, when the documentation pages explain how the code is laid out, and when issues are labeled for newcomers. Donations, about four thousand dollars a year, pay a maintainer for a few hours each week, most of them spent on review. None of these has been measured.
The brief
- Upgrade the influences the project's records show until they close a path of causal claims. checked by the lab
- Keep at least two influence claims. checked by the lab
- Draw at least two clusters. checked by the lab
- Every causal claim is one the project's records show. you check this
Your palette
variable polarity influence claim weight central outcome cluster
To draw in the lab, use a tablet or a larger screen. Everything else reads normally here.
Press an empty spot to add a variable and type its name. Drag a variable to move it. Select a variable or an influence claim to change it. Drag a cluster by its label or a corner to move it, and by the square at its corner to resize it. Double-click or double-tap a variable or a cluster's label to edit its words in place, or select it and use Rename or the fields under the canvas.
Nothing selected. Select a variable, an influence claim or a cluster on the canvas, and what you can change shows here.
The tools
- Variables V
- add a variable (press an empty spot), move one (drag it), rename one (double-click it, or Rename under the canvas), or select anything.
- Influence claims E
- draw an influence claim by dragging from one variable to another.
- Clusters C
- drag out a cluster around variables, and label it with what they share.
Keys
- R reverse the selected claim
- O mark the selected variable as the central outcome, or take the mark off
- W the selected claim's weight, in turn: none, 1, 2, 3, none
- +− upgrade the selected influence claim to a causal claim; the same key again makes it an influence claim again
- Delete delete what's selected
- Ctrl+Z undo
- Ctrl+Shift+Z redo
- Esc clear the selection
- Enter finish the words you're writing
- Esc cancel them
Keys act on the lab you last used, or on the open lab view, and never while you type.
0 of 9 checks passed; 9 pending.
- Upgrade the influences the project's records show until they close a path of causal claims. (Not started)
- Keep at least two influence claims. (Not started)
- Draw at least two clusters. (Not started)
Always checked
- One central outcome (Not started)
- Every variable has a path of claims to the central outcome (Not started)
- No two clusters overlap (Not started)
- Every cluster holds two or more variables (Not started)
- The central outcome sits in no cluster (Not started)
- No variable's name breaks the more test's three rules (Not started)
Written feedback
One defensible answer
It opens here once you've drawn at least one variable in the lab above. Your attempt saves as you draw.
CS 03Kelsham Primary School: what decides where a child starts
Upgrading only the counted claims
Tom Hale asks what decides how many children start at Kelsham Primary School each September. The county council's records, which David Brennan keeps, show the starters following the births in the villages four years before: 22 births in 2016 and 19 starters in 2020, 13 births in 2022 and 9 starters in 2026. The school's records show that when its teachers fell from five to four in 2023, Years 3 and 4 became one class, and that its classes shrink with its roll: 88 pupils in four classes now. Ruth Okafor hears from parents that mixed-age classes send families to Brayford Primary School and that small classes keep them. Helen Marsh, Brayford's head teacher, says her school has spare places in most of its classes. David Brennan forecasts 0.25 children of primary school age for each new home at Mill Lane. Nobody has counted the parents' reasons, Brayford's places or the new homes against the starters.
The brief
- Draw at least four direct influences on children starting each September. checked by the lab
- Give each direct influence a weight. checked by the lab
- Upgrade exactly the three claims someone has counted, giving each a + or −. checked by the lab
- Leave at least three claims nobody has counted without a + or −. checked by the lab
- Draw at least two clusters. checked by the lab
- For each influence claim on the starters, name the count that would upgrade it. you check this
Your palette
variable polarity influence claim weight central outcome cluster
To draw in the lab, use a tablet or a larger screen. Everything else reads normally here.
Press an empty spot to add a variable and type its name. Drag a variable to move it. Select a variable or an influence claim to change it. Drag a cluster by its label or a corner to move it, and by the square at its corner to resize it. Double-click or double-tap a variable or a cluster's label to edit its words in place, or select it and use Rename or the fields under the canvas.
Nothing selected. Select a variable, an influence claim or a cluster on the canvas, and what you can change shows here.
The tools
- Variables V
- add a variable (press an empty spot), move one (drag it), rename one (double-click it, or Rename under the canvas), or select anything.
- Influence claims E
- draw an influence claim by dragging from one variable to another.
- Clusters C
- drag out a cluster around variables, and label it with what they share.
Keys
- R reverse the selected claim
- O mark the selected variable as the central outcome, or take the mark off
- W the selected claim's weight, in turn: none, 1, 2, 3, none
- +− upgrade the selected influence claim to a causal claim; the same key again makes it an influence claim again
- Delete delete what's selected
- Ctrl+Z undo
- Ctrl+Shift+Z redo
- Esc clear the selection
- Enter finish the words you're writing
- Esc cancel them
Keys act on the lab you last used, or on the open lab view, and never while you type.
0 of 11 checks passed; 11 pending.
- Draw at least four direct influences on children starting each September. (Not started)
- Give each direct influence a weight. (Not started)
- Upgrade exactly the three claims someone has counted, giving each a + or −. (Not started)
- Leave at least three claims nobody has counted without a + or −. (Not started)
- Draw at least two clusters. (Not started)
Always checked
- One central outcome (Not started)
- Every variable has a path of claims to the central outcome (Not started)
- No two clusters overlap (Not started)
- Every cluster holds two or more variables (Not started)
- The central outcome sits in no cluster (Not started)
- No variable's name breaks the more test's three rules (Not started)
Written feedback
One defensible answer
It opens here once you've drawn at least one variable in the lab above. Your attempt saves as you draw.
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.