methodatlas
Systems Thinking

Behavior Over Time Graph

Turns relationships, patterns, and leverage points into a tangible result by choosing a variable and time span, plotting the trend over time, and deriving cause hypotheses.

Core question
How did the chosen variable behave over time, which patterns such as growth, decline, oscillation, or stagnation appeared, and which systemic causes sit behind the pattern?
LowWorkshop + async20-45 min
Purpose

The method helps clarify relationships, patterns, and leverage points in a concrete way. It draws relationships, patterns, and feedback loops. The result is captured as a behavior over time graph, trend hypotheses, and key events.

How it works

The team follows the steps: choose the variable and time span, plot the trend over time, mark key events, discuss patterns and turning points, and derive cause hypotheses. Each step is captured visibly. At the end, a behavior over time graph, trend hypotheses, and key events are available so decisions, tests, or actions can follow directly.

Visual orientation

Method sketch for a quick mental model.

Behavior over Time · System-TrendVerlauf, Ereignisse und Hypothesen sichtbar machen, bevor Ursachen diskutiert werden
Behavior over Time GraphDie Skizze zeigt eine qualitative Kurve über Zeit, markierte Ereignisse, typische Muster und Hypothesen zur Systemdynamik.Vom aktuellen Zustand zum VerlaufsmusterEine relevante Variable wird über Zeit skizziert, Ereignisse werden markiert und als Systemhypothesen gelesen.hochniedrigStartheuteZeitWert / VerhaltenEreignisRedesignInterventionTemplatesAnstiegProblem eskaliertPlateauSystem stabilisiertKnickHebel wirkt verzögertHypothesenUrsache?Verzögerung?Hebelpunkt?

Flow

  1. 1Choose the variable and time span
  2. 2Plot the trend over time
  3. 3Mark key events
  4. 4Discuss patterns and turning points
  5. 5Derive cause hypotheses

The runsheet guides execution with 5 phases, timeboxes, 5 pitfalls, and clear stop criteria.

Open runsheet

Ideal for

  • Systems thinking
  • Problem framing
  • Trend reflection

Not good for

  • One-off events without a trend
  • Exact statistical modeling

Deep dive

In detail

Behavior Over Time Graphs make change visible before people argue about causes. A relevant variable is drawn as a curve over time, including notable events or interventions. That helps teams distinguish whether a problem is stable, escalating, cyclical, or responding with delay. The curve acts as a bridge to deeper system models such as causal loops or stock-and-flow diagrams.

Facilitation

Prepare axes, a time span, and a clear variable. Have people sketch separately first and then compare the curves, because differences often reveal important assumptions. Mark events and interventions without jumping into solution discussions too early.

Output artifacts
Behavior Over Time GraphTrend HypothesesKey Events
Tags
Artifact templates
Behavior Over Time Graph Working TemplateCompact working template for Behavior Over Time Graph with context, input, output artifacts, and next step.
markdown

behavior-over-time-graph-working-template.md

Compact working template for Behavior Over Time Graph with context, input, output artifacts, and next step.

Behavior Over Time Graph Working Template

Goal

Visualizes how a relevant variable changes over time and which patterns may lie beneath it.

Context

When and for what do we use this method?

Input

Which data, observations, decisions, or materials are available?

Execution

Short notes along the runsheet.

Output artifacts

  • Behavior Over Time Graph:
  • Trend Hypotheses:
  • Key Events:

Assumptions and open questions

  • ...

Decision / Next step

Owner, date, and success signal.

When to choose differently

Short decision aid for existing alternatives.

Causal Loop Diagram

Statt Behavior Over Time Graph, wenn nicht nur ein Verlauf, sondern die dahinterliegenden Rückkopplungen sichtbar werden sollen.

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