Feedback loops

Five structural levers to reopen feedback loops that are resistant to external evidence

By Lachlan S. McGill.

lachlan-mcgill
Lachlan S. McGill (biography)

When feedback loops have become resistant to external evidence, what are some potential ways of intervening to reopen them?

This i2Insights contribution builds on my previous post which covers understanding why feedback loops can become resistant to external evidence and how to diagnose such a structural problem.

Here I introduce five structural ways to intervene in such a closed feedback loop. These are structural levers, each targeting a different aspect of how signals flow, how authority is allocated, and how evaluative standards are defined.

One practical note before beginning. Applying the interventions below often requires institutional authority, coalition building, or regulatory support, so that isolated actors may not be able to deploy them fully, leaving the problematic dominant structure intact.

Read more

Understanding and diagnosing when feedback loops become resistant to external evidence

By Lachlan S. McGill.

lachlan-mcgill
Lachlan S. McGill (biography)

Why does better evidence sometimes fail to improve decision making? How can we tell if this is caused by feedback loops becoming resistant to external evidence?

Understanding how structural patterns become problematic

In most organisations, decisions are embedded in feedback loops that connect indicators, incentives, and authority structures. These loops determine what counts as success, which signals influence decisions, and how performance is evaluated over time.

When feedback loops are well aligned with system goals, they support learning. However, feedback loops can also evolve in ways that reinforce a narrow definition of success. This is generally associated with a system relying on a small number of indicators to guide decisions.

Read more

Five core concepts for understanding systems

By Andrei Savu.

andrei-savu
Andrei Savu (biography)

What concepts are key to understanding systems?

A system is a set of interdependent elements whose coordinated interactions give rise to an outcome none of the pieces can deliver alone. The key word is relationship: change the relationships and the behavior of the whole shifts, even if every component remains identical.

Five core concepts for systems thinking are: purpose, boundary, feedback, leverage and emergence.

Purpose and boundary

Every system exists to fulfill a purpose, defined by boundaries that separate internal elements from external factors. These two fundamental concepts—purpose and boundary—determine how we understand, analyze, and influence systems of all types.

Read more

Combining subjectivity and objectivity in systems thinking: The SOS sandwich

By James Stauch and Daniela Papi-Thornton.

mosaic_authors_james-stauch_daniela-papi-thornton
1. James Stauch (biography)
2. Daniela Papi-Thornton (biography)

In seeking to understand, map, and then act to intervene in a system, how can we make the best use of both subjectivity and objectivity? How can we effectively toggle between facts and norms, between what is true (or at least broadly verifiable) and what is valued (or valuable)?

In the book that this i2Insights contribution is based on (Stauch et al., 2025), the case is made for people to spend far more time understanding a problem, and proportionally less time acting to “solve” the problem. To help frame this approach, the SOS (subjective-objective-subjective) sandwich is used as a simple heuristic to show where subjectivity and objectivity can be taken into account when dealing with a system.

In this work, objectivity is considered as a vector, not a destination, with true objectivity always out of reach, as we can never be completely objective in our approach to research. That said, we can strive for it by recognizing our biases and seeking diverse viewpoints.

Read more

Key systems thinking lessons from Donella Meadows

By Geoff Marlow

geoff-marlow
Geoff Marlow (biography)

The book “Thinking In Systems: A Primer” by Donella (Dana) Meadows (2008) offers a useful entry point into systems thinking via seven lessons.

Lesson 1: Systems are always more than the sum of their parts

Feedback loops are pivotal, as is looking beyond the players to the underlying rules of the game.

Meadows (p. 13) offers guidance as to “whether you are looking at a system or just a bunch of stuff:

  • Can you identify parts? . . . and
  • Do the parts affect each other? . . . and
  • Do the parts together produce an effect that is different from the effect of each part on its own? . . . and perhaps
  • Does the effect, the behavior over time, persist in a variety of circumstances?” 

Read more

Using archetypes as a systemic lens to understand the complexity of sustainable development

By Hossein Hosseini, Enayat A. Moallemi, Sibel Eker, Edoardo Bertone and Katrina Szetey

authors_hossein-hosseini_enayat-moallemi_sibel-eker_edoardo-bertone_katrina-szetey
1. Hossein Hosseini; 2. Enayat A. Moallemi; 3. Sibel Ekern; 4. Edoardo Bertone; 5. Katrina Szetey (biographies)

What are systems archetypes and how can they be used to bring a deeper understanding of causal drivers, potential dynamic behaviour in the future, and policy resistance when tackling complex problems, including those in sustainable development?

Systems archetypes are recurring generic systems structures found in many kinds of organisations, under many circumstances, and at many levels and scales. They are distinctive combinations of reinforcing and balancing processes theoretically rooted in systems thinking and modelling.

There are eight common archetypes, each with specific underlying causal drivers (eg., feedback loops, delay), expected dynamic behaviour (eg., acceleration, disruption, tipping point), and policy implications (eg., how to respond, where to intervene). Archetypes can help shift an analytical focus from simple behavioural correlations or a limited understanding of interactions between certain goals to a generalised knowledge of recurring patterns, causes, and consequences.

Read more

Seven methods for mapping systems

By Pete Barbrook-Johnson and Alexandra S. Penn

authors_pete-barbrook-johnson_alexandra-penn
1. Pete Barbrook-Johnson (biography)
2. Alexandra S. Penn (biography)

What are some effective approaches for developing causal maps of systems in participatory ways? How do different approaches relate to each other and what are the ways in which systems maps can be useful?

Here we focus on seven system mapping methods, described briefly in alphabetical order.

1. Bayesian Belief Networks: a network of variables representing their conditional dependencies (ie., the likelihood of the variable taking different states depending on the states of the variables that influence them). The networks follow a strict acyclic structure (ie., no feedbacks), and nodes tend to be restricted to maximum two incoming arrows. These maps are analysed using the conditional probabilities to compute the potential impact of changes to certain variables, or the influence of certain variables given an observed outcome.

Read more

Fifteen characteristics of complex social systems

By Hamilton Carvalho

Author - Hamilton Carvalho
Hamilton Carvalho (biography)

What is it about complex social systems that keeps reproducing old problems, as well as adding new ones? How can public policy move away from what I call the Mencken Syndrome (in reference to a quotation from American journalist Henry Mencken) – that is, continually proposing clear and simple solutions to complex social problems – that are also wrong!

With this goal in mind, I have compiled a list of fifteen major characteristics of complex social systems based on the system dynamics and complexity sciences literatures, as well as my own research.

Read more

Four patterns of thought for effective group decisions

By George P. Richardson and David F. Andersen

authors_george-richardson_david-andersen
1. George P. Richardson (biography)
2. David F. Andersen (biography)

What can you do if you are in a group that is trying to deal with problems that are developing over time, where:

  • root causes of the dynamics aren’t clear;
  • different stakeholders have different perceptions;
  • past solutions haven’t worked;
  • solutions must take into account how the system will respond; and,
  • implementing change will require aligning powerful stakeholders around policies that they agree have the highest likelihood of long-term success?

The fields of systems thinking and system dynamics modelling bring four important patterns of thought to such a group decision and negotiation:

Read more

Scaling up amidst complexity

By Ann Larson

ann-larson
Ann Larson (biography)

How can new or under-utilized healthcare practices be expanded and institutionalized to achieve audacious and diverse global health outcomes, ranging from eliminating polio to reversing the rise in non-communicable diseases? How can complex adaptive systems with diverse components and actors interacting in multiple ways with each other and the external environment best be dealt with? What makes for an effective scale-up effort?

Four in-depth case studies of scale-up efforts were used to explore if there were different pathways to positively change a complex adaptive system.

Read more