How systems mapping can help you build a better theory of change
Theories of change (ToCs) have become increasingly prevalent in the development and nonprofit sectors, with many donors now requesting them as requirements to receive funding. A theory of change can be a useful tool to articulate assumptions about how a given project or organization expects change to happen and how their efforts will positively contribute to such a change process. But when the resulting theory of change is too linear, it can lead to blindspots and limit your ability to design effective strategy.
The limitations of linear theories of change
Many proponents of ToCs see them as part of a wider approach to management through which people can more effectively understand and engage with the complexities of social, political and economic change processes. For example, Hivos defines a theory of change as:
“a process-oriented approach to analyzing the complex systems in which we and our partners and allies work, and for planning actions we think will influence parts of the system in a positive way… ToC starts from the premise that social change processes are complex and unpredictable, that different perspectives exist on what needs to change and why, and that a full analysis of the context of a change intervention and of the assumptions underlying its design are crucial to enhance its chance of success.”
But while the theory of change approach has done much to advance thinking beyond the kinds of linear, reductionist and rigid approaches to planning and management epitomized by the infamous logical frameworks, theory of change diagrams (the product that tends to be most associated with the term “theory of change”) lag behind these aspirations and end up encouraging linear, reductionist thinking.
For example, the authors of the aforementioned guide by Hivos, whilst on the one hand promoting an approach to ToCs grounded in a recognition that “social change processes are complex and characterized by non-linear feedback loops: our own actions interact with those of others and a myriad of influencing factors”, also concede that “in practice, the ToC visualization often presents a diagram or flow-chart of the pathways of change, in a linear way. The result is a logic model that does not explain key elements. This carries the risk of losing — or at least not using — the diverse and rich information the ToC process provided and of pushing us back into linear thinking.” This concern is not only held by Hivos. It was also highlighted in a 2014 study by Craig Valters on the use of ToCs in international development (p4).
These concerns point to a disconnect that has emerged between the way that we think about social change and theories of change and the ways in which we visualize these change processes and our involvement in them through the diagrams we create as part of a theory of change process.
“This carries the risk of losing — or at least not using — the diverse and rich information the ToC process provided and of pushing us back into linear thinking.”
Systems mapping to the rescue
In this post, we’ll explore potential ways systems maps can be used as an alternative to conventional theory of change diagrams in order to bridge this disconnect and enable theory of change diagrams to be more in tune with the complexity of the contexts they purport to change.
The aim of this post is not to propose a new methodology for developing a theory of change from start to finish. Rather, the aim is to generate ideas about how systems mapping — particularly with the aid of Kumu — can be integrated with existing approaches to theories of change (see the guides developed by Hivos, INTRAC, Keystone and NPC), particularly in the area of developing visual ToC diagrams.
The ideas proposed in this post will be most effective when complemented by the emerging best practices for ToCs (see publications by Craig Valters and Isabel Vogel, as well as the Wageningen ToC Portal). These include:
- high levels of participation and local ownership in ToC development
- developing a narrative theory of change to complement a ToC diagram
- conducting a power analysis
- using a theory of change process to facilitate ongoing critical reflection and learning
- regularly reviewing, updating and adapting a ToC as it is put into practice
Having said this, whilst the focus of this post is very much on developing visual diagrams as part of a wider process of developing and applying a theory of change, the ideas in this post can also serve to enrich the theory of change process as a whole by facilitating some of the best practices identified in the ToC literature.
So how can system mapping help practitioners overcome the weaknesses of conventional ToC diagrams?
Applying the language of “loops”
Loops are a primary component of any systems map. Loops highlight those dynamics which are playing out over and over again and which end up acting as either significant drivers of change or maintainers of the status quo. When applied to theories of change, loops have two key advantages:
- They are capable of depicting a wider diversity of change processes than linear diagrams.
- They are better able to capture what are considered by many to be critical aspects of social change: nonlinearity, iteration, adaptation and learning.
Loops come in two flavors, reinforcing and balancing. Let’s discuss reinforcing loops first.
Reinforcing loops
Reinforcing loops are effective tools for visualizing iterative approaches to change, where it is expected that a single pathway of cause and effect relationships (i.e. A -> B -> C, where C is the desired change) will not be sufficient to generate a desired change. Instead, it is envisaged that the desired change will be achieved through a continuous process of growth and/or improvement brought about by multiple iterations of the same causal sequence of events (i.e. A -> B ->C -> A -> …), with each iteration building on the successes of the previous one and increasing in its effectiveness.
There are many change situations which could be useful to depict in this way. These include economic growth or income generation, infrastructure development, (domestic) resource mobilization, technology research and development, awareness-raising or shifting public opinion, citizen mobilization, or capacity building, to name a few. With these types of change processes, there isn’t necessarily a concrete ceiling to what you are seeking to achieve. Rather, your goal is to facilitate and sustain an engine of growth that drives a continuous process of improvement to a situation.
A very basic example of a reinforcing loop depicted for this purpose is illustrated below. Here an intervention of increasing investment in primary education serves to facilitate a reinforcing loop of continuous improvement in education levels (over the long-term).
In this diagram only one specific intervention is illustrated (investment in primary education). However, it is possible for theory of change diagrams with reinforcing loops to incorporate interventions that strengthen each element identified as part of a desirable reinforcing loop. For example, in this diagram one could add interventions such as employment support services to enhance the ability of families to secure better paid jobs and/or conditional cash transfers to enhance the element related to families’ capacities to keep their children in school.
Another advantage of using reinforcing loops in a theory of change diagram is that they can alternatively be interpreted as representing a negative situation that needs to be changed, therefore also serving as a justification for your organization’s work or your particular program. In the example above, this diagram could be interpreted as a sequence of events that results in increasing levels of education brought about by high levels of investment in primary education. But it could also be interpreted as representing a self-perpetuating cycle of low education levels that is caused by under-investment in primary education.
These kinds of reinforcing loops are externally-oriented: they are focused on (potential) engines of growth identified within the external environment that a particular program or organization seeks to facilitate and sustain through their interventions. However, reinforcing loops in theory of change diagrams can also be internally-oriented: depicting continuous cycles of improvement within an organization or program that serve to enhance its effectiveness in bringing about a desired change. This is where reinforcing loops can be a useful tool for integrating program or organizational learning into a theory of change diagram.
A basic representation of a program or organizational learning process which could be integrated into a theory of change diagram is illustrated below. Here, a process of monitoring, reflection and learning serves to identify and amplify the underlying causes of a successful program (R1), while simultaneously identifying and correcting the underlying causes of a program when it is ineffective at achieving its desired outcomes (B2).
Balancing loops
Balancing loops also have several potential uses in a theory of change diagram. At the most basic level, a goal-seeking loop can be used to depict a change process in which an organization seeks to shift an undesirable situation into a desirable situation, based on some pre-defined vision or objective for that desirable situation. The difference between these types of change processes and those depicted in reinforcing loops is that, rather than depicting general processes of continuous growth or improvement, the change processes represented by balancing loops are ones in which there is a specific desired state that a program or organization hopes to achieve. The program or organization would then seek to maintain this desired state once it is achieved.
These are often the types of change processes where there are clear, finite limits to what can be achieved. For example, an environmental restoration program can only restore a degraded environment up to a certain level, beyond which it would not make sense to undertake additional restorative work. Other examples of change processes that could be represented by balancing loops include health levels, legal protections, fulfilling human rights obligations, water quality (when the objective is to increase something positive to a desired level), crime, debt, inequality, gender or racial discrimination (when the objective is to decrease something negative to a desired level).
A basic example of how to represent these types of loops in a ToC diagram is presented below, which uses the example of drinking water quality. Here there is a current level of water quality that is undesirable which is contrasted with a desired water quality level. Taken together, these two elements result in a gap between the current situation and the desired situation that the intervention depicted in the loop (distributing household water filters) seeks to close.
An additional use for balancing loops is when an organization or program seeks to foster stability in a particular environment, either by preventing undesirable things from occurring and/or by quickly resolving them when they do. These types of change processes are particularly difficult to represent in linear ToC diagrams. Nonetheless, there are many kinds of programs to which they apply including peacekeeping or conflict prevention and resolution; human rights campaigning; disaster relief or disaster risk reduction; environmental protection and conservation; and corruption prevention, to name a few.
An example of how to depict these kinds of change processes using balancing loops is presented below, focusing on rapid response campaigning to threats of human rights violations.
Adaptive management
In International Development and the nonprofit sector more generally, adaptive management is increasingly proposed as a core strategy for navigating the complexity in which social change processes operate. However, this approach to management is conspicuously absent from traditional ToC diagrams (which is not altogether surprising given that linear diagrams, by their very nature, are incapable of depicting the feedback process that lies at the heart of adaptive management). Balancing loops can be used to integrate an adaptive management approach into a theory of change diagram, making these types of diagrams particularly appropriate for programs that have to operate in dynamic environments characterized by high levels of complexity and uncertainty.
A proposal for incorporating an adaptive management approach into a theory of change diagram is shown below.
This example builds upon the problem resolution balancing loop (B1) and the organizational learning diagrams presented above by integrating single and double loop learning in order to adapt program strategies in changing environments. The B2 loop depicts a process of strategy adjustment and refinement in order to make it more effective at achieving shorter-term performance targets (usually contained in output and outcome-level indicators).
However, if this desired outcome does not, over time, result in the desired impact then a deeper process of reflection and adaptation (double loop learning) is required. This type of learning involves a reflection on core assumptions in order to make more significant changes to program outcomes and corresponding strategies (B3 loop).
Time delays
The example above also illustrates another useful feature of system map when used for ToCs: the ability to incorporate time delays into a diagram. This enables a ToC diagram to better capture the temporal elements of the proposed change process — something that is also lacking in conventional ToC diagrams. Time delay symbols are particularly useful for depicting the difference between project outputs, which one expects to achieve in the short-term, and project outcomes and impact that are hoped to be achieved over a longer time-frame. For example, in the education reinforcing loop above, investment in primary education may achieve the (relatively) short-term objective of enabling more children to attend school. However, the longer-term goal of enhancing the population’s education levels (in terms of literacy and numeracy) would not be achieved until a longer timeframe had been taken into account, as one cannot expect literacy and numeracy levels to increase automatically as soon as more children become enrolled in school.
Integrating these principles into your theory of change approach
Creating a robust, non-linear theory of change will likely mean incorporating a variety of reinforcing and balancing loops (as well as time delays) to convey the true complexity of the change you’re seeking to create. So where should you start?
I see two potential approaches:
- Integrating your theory of change into an existing map
- Building a system map to explain your theory of change
Stay tuned for Part 2 where we’ll cover these approaches in detail.
