Thinking in Systems

A team increases work pressure to clear a backlog. Performance initially rises. A few weeks later, errors, overtime and absences accumulate; the backlog grows again. The initial measure was not illogical – it simply considered only part of the system.

Donella Meadows describes a system as interconnected elements whose relationships produce a particular behaviour. Systems thinking shifts attention from isolated events to patterns and structures: what changes over time, what feeds it and which feedback loops sustain it?

1. Make stocks and flows visible

A stock is something that accumulates or diminishes over time: an order backlog, trust, knowledge, staff or water in a reservoir. Inflows increase it; outflows reduce it. This simple distinction prevents premature interpretations.

A backlog, for example, decreases only if more is consistently completed than newly taken on. Even if inflow is reduced immediately, the existing stock does not disappear at once. Looking only at the current figure can lead us to stop an effective measure too soon or recognise a harmful development too late.

2. Feedback explains dynamics

Reinforcing feedback loops drive growth or decline: good experiences create trust, trust increases use, and use generates further experiences. Balancing feedback loops, by contrast, seek to maintain a desired state – for example when additional capacity reduces a backlog.

Many problems contain several loops simultaneously. Working faster clears tasks but may create errors that generate additional work later. Delays make steering harder: a decision may take effect only after further adjustments have already been made. This produces overreactions and oscillations.

3. Choose system boundaries and leverage points consciously

Every representation draws a boundary. Anything treated as “outside” disappears from the analysis, even though it may bear consequences. Affected perspectives, longer timeframes and unintended side effects should therefore be deliberately included.

Meadows distinguishes intervention points at different levels of depth. Numbers and parameters are visible but not always especially effective. Access to information, rules, goals and underlying assumptions can change behaviour more profoundly. A leverage point is not a magic spot, however; even a well-chosen intervention can trigger new feedback loops.

Your exercise: map a recurring problem

Choose a problem that keeps returning after it has been solved. Take three minutes:

1. Minute 1 – stocks and flows. What accumulates or diminishes? What increases and what reduces this stock?
2. Minute 2 – loop and delay. Draw an effect that reinforces or balances itself. Where does time pass before the consequence becomes visible?
3. Minute 3 – the leverage question. Alongside a number, examine information, a rule, a goal or an assumption: what might change the pattern rather than just today's symptom?

Add a person who experiences the system differently. Which connection or side effect would they probably draw in?

What we take from this

Systems thinking strengthens the ability to structure complexity without simplifying it prematurely. In WEITER7 , the system sketch extends the reality check: it reveals conditions and possible side effects before a small change experiment is chosen.

Which recurring problem am I treating as an isolated event even though a feedback loop or delay might lie behind it?

Context: This insight summarises selected core ideas from Meadows' introduction in our own words. The exercise and WEITER7 connection are our own adaptations. A simple system sketch is a hypothesis, not the system itself. Boundaries, relationships and directions of influence may be wrong or incomplete; consequential decisions require data, multiple perspectives and specialist modelling.

Sources and further reading: Donella Meadows Project: Book page ↗ · Book description and bibliographic details ↗