Theory of Change framework
The Theory of Change framework is designed to aid social innovation projects to hypothesise about the outcome and impact of their work, in order to be able to respond to rapidly changing contexts and emergent insights while remaining accountable to stakeholders and funders.
Social innovation by definition addresses complex situations. It is ‘the development of creative and practical solutions to complex social problems’ (Dr. Neil Stott & Prof. Paul Tracey, Co-Directors of the Cambridge Center for Social Innovation).
In complex situations, according to the Cynefin framework, the relationship between cause and effect can only be perceived in retrospect. The recommended route to action is PROBE→ SENSE→RESPOND. There is no possibility for analysis and planning.
Meanwhile, in order to convince funders and supporters to invest in social innovation, one needs to present a plan of action with projected outcomes. In brief, social innovation projects need to plan in situations where it is impossible or even harmful to plan. In such a situation, how can we maintain accountability, and prove the value of our work?
One way to overcome this dilemma is to use the Theory of Change framework for project design, which allows shifting the emphasis from prescription and delivery towards hypothesis and confirmation/refutation. While this method is sometimes contested because it can be read as a logframe for projects (if we do this, then that happens…), we at collaboratio helvetica focus on the ‘theory’ aspect of it. Instead of viewing it as prescriptive, we use it as a tool to theorise and speculate about what needs to be done in order to enable innovation and change.
The framework slices the project into 4 parts: input, output, outcome and impact. Input and output are connected in a straightforward causal relationship: if we want these activities (output) to happen, we need the following resources (input). The relationship between output and outcome, as well as the relationship between outcome and impact, are hypothetical: we assume that if we do our planned activities (output), the direct outcome of that is going to be an important step towards change (outcome), and that step eventually will lead to lasting systems change (impact). The assumptions about outcome and impact are often
INPUT: What resources need to be invested (time, money) in the project? It is important to quantify capacity that is needed, even if the work is covered by volunteers.
OUTPUT: What will we do? Concrete and detailed map of actions we need to take in order to deliver the project. This is what we normally have to report on to funders.
We also articulate our ASSUMPTIONS about how what we do will lead to the outcome(s) we wish to achieve. If our assumptions are not proved right, we modify either our outputs or and/our assumptions, and reiterate the program to achieve our outcomes.
OUTCOME: What will happen as a direct result of what we do? Social innovation projects don’t have singular routes from output (what we do) to short term goals (outcomes) and long term impact. We essentially run social experiments based on hypotheses about what actions will eventually lead to, and we learn from our actions.
We make articulated ASSUMPTIONS about how the direct result(s) of our activities (outcome) will lead to the envisioned systems change (impact) we envision.
IMPACT: What is the long term systems change we are aiming for? A shared vision of the future, towards which we work.
Katalin Hausel is responsible for organisational health and evaluation at collaboratio helvetica. She has gained three Masters degrees over the years. Katalin has a past in writing code, making and teaching art, working on rural regeneration and social cohesion projects, building IT tools, designing learning and evaluation tools, developing learning and evaluation solutions, working on new forms of collaboration and generally putting her mind to complex situations and finding a way through. Lately, she has been focusing on developing a framework for social innovation initiatives to use observation and organisational learning as a project evaluation methodology instead of predefining objectives. As a dedicated discipline-roamer and paradigm-shifter, she has been exploring how to craft situations, tools and spaces for transformation and learning to support systemic change and the implementation of the Sustainable Development Goals (SDGs).