Learning Ecology - an evolving practice
Organisational learning is important for all contexts, yet more important still for innovative, action research-based, prototype driven initiatives. Dedicated to catalysing social change in Switzerland, collaboratio helvetica designs and runs prototypes and experiments in order to find ways to achieve this goal, and often the learnings from these are the most valuable outcome of the projects. Social change work means focusing on notoriously complex, systemic issues, with no quick fixes in sight. Failing is just as much part of the work as success. This is why placing learning into the heart of our activities is essential to our work.
Combining what usually would be called ‘Measurement and Evaluation’, ‘Knowledge Management’ and ‘Research and Development’, our learning ecology framework is designed to enable every team to build on what we had previously learned when designing new projects, identify the key points of investigation, trace the indicators to track how plans translate into reality, identify new, unplanned, emerging outcomes, and distil the learnings into new, actionable knowledge for new iterations.
What drives learning ecology is an application of a systems approach to organisational learning. Learning ecology views the organisation as a system, as well as each project as a system embedded in the larger context of the organisation. It also views the organisation as part of a complex context of different systems like politics, education, or the economy, just to name a few. We consciously hold the complexities within the organisation knowing that they are deeply connected to complexities in the outside world. We identify principles that guide our work on every level, and make sure our projects on the ground are as much aligned to them as possible, - and we learn from the gaps that reveal themselves between ideals and reality.
Learning ecology is an emerging practice still in development. This is the process we came up with so far:
1. Mapping the contexts
No project ever emerges from a vacuum. The first task of learning ecology is to map the contexts that serve as an inspiration or challenge for developing a new approach to the project. This entails such processes as identification of the system they are trying to change, the 2-d, 3-d or 4-d mapping of their system, the identification of leverage points, exploring other actors who do similar work. It may also include the mapping of personal experiences and expertise of the team.
The outputs for this phase include challenge statements, system maps, system descriptions, stakeholder maps and notes from interviews, notes and images from reflection journeys, and reflection papers.
2. Identifying the project
Once the contexts are mapped, it is possible to identify the project as an actor in that particular system. There are different approaches to do this, by analytical methods (the 5R model) or by multi-sensory processes (the presencing part of the Theory U model).
In the social innovation context where collaboratio helvetica operates, where the complexity of the challenges that we work on are significant, we don’t aim for fully developed ideas, rather try to identify practical interventions (prototypes) that can be implemented at low investment costs and within a reasonable time frame. This further underlines the importance of the role of learning ecology, because the learnings from these actions often are more resilient and useful than the actual impact of the experiment. It is crucial for the project to have a learning ecology framework in place to make sure that not only the planned outcomes and impact can be captured, but the unforeseen and the unexpected as well.
3. Theory of Change
The framework we used at collaboratio helvetica is the well-known Theory of Change. While keeping intact the logic framework in the middle of it, which defines a logical connection between outputs, outcomes and impact, we also fully acknowledge that in many situations such a framework actively paralyses the necessary innovation on the ground that would make the project a success. As described above, the main challenge for innovation is to create the context for and capture radically new ideas. In a way, any social innovation project is an open-ended process that starts at one point and adjusts its activities according to the observed outcomes. It is often said that delivering on classic key performance indicators planned years before are a sign of failure in complex contexts, since it almost certainly means that the project missed the real innovation opportunities on the ground, and rammed through its plan instead.
4. Evaluation by discovery
We believe that the logic framework and its identified markers of success (KPIs - Key Points of Investigation) have a function that makes it useful to keep them. While we know that the map is never the territory, we also know that never trying to find identifiable and communicable points of entry to the territory makes the project useless for others. One of the assumptions of the learning ecology concept is that a key task of innovative projects is to be able to share their learnings with others.
It is also important to note that social innovation is mostly funded rather than operating on a business plan, and reporting to the funders is also a key part of the learning ecology framework.
5. Story as an explanatory device
It can be easily imagined how much data we end up with at the end of such a learning ecology data collection process. Traditional report writing is organised around the structure of the Theory of Change framework (input-output-outcome-impact) and pre-identified KPIs, and we definitely produce such reports as they are essential for continuing to receive funding. However, we also experimented with alternative ways of sense-making based on the qualitative and quantitative data we collected. We have tried two methods so far. One is to look at the data through a specific scientific framework that is strongly related to the essential purpose of the project. In the case of the Catalyst Lab, which aspires to train catalysts for systemic change, we selected Donella Meadows’s famous paper Dancing With Systems, and took the list of key elements as points of inquiry. Another experimental reporting format is by identifying a classic story or myth that captures the essence of the project, and walking through the story of the project, trying to identify if certain elements of the story can be found there, and if it offers any new insight about what actually happened.
6. Learning loop
The learning ecology framework doesn’t stop with ‘harvesting’ - that is, by writing up what happened from different perspectives and in different formats. At collaboratio helvetica we tried to implement all the 4 modes of knowledge conversion as identified by Nonaka and Takeuchi.
a. BA - (the word space/time in Japanese) - Learning spaces. Since knowledge is intangible, unbounded and dynamic and cannot be stocked, BA works as the platform of knowledge creation by collecting the applied knowledge of the area into a certain time and space and integrating it.
b. Four modes of knowledge conversion:
PARTICIPATION - Socialisation: all team members were invited to participate in the events around the program.
WRITING/HARVESTING: Externalisation - all participants and facilitators as well as the learning ecology team write several shorter or longer texts that capture their experiences.
REPORTS - Combination: the various reports produced by the Learning Ecology team were ‘combinations’ of the various writings by everyone.
REFLECTIONS SPACES - Internalisation: organisation and team spaces for sense-making, exploration and emergent new knowledge.
The Learning Ecology cycle
Organisational learning is a cyclical process, without clear beginnings and ends. We identified 5 parts to a full cycle for organisational learning management:
Conceptualisation (capturing the explicit and implicit insights and assumptions for the project)
Planning (identifying Key Points of Investigation, and respective indicators, and set up a system to capture and monitor what is actually happening, as well as checking is what we planned to happen actually does unfold.)
Collection (actually running the data collection, including surveys, interviews, videos, storytelling, blogposts, observations, emerging unexpected events and serendipitous encounters)
Processing (looking at the data, writing, analysing, finding correlations, identifying learning points, crystallising what actually happened)
Reflection (asking the question, what does it all mean, and what are the next steps)
While it is of the utmost importance to trace the evolution of the organisation’s work from ideas and insights through delivery all the way to reflection, we also keep in mind that innovation will never be a run-of-the-mill, predictable process, and that systems change happens in often unexpected and unforeseeable ways. We welcome being lost, perplexed and accept ‘not knowing’, while we strive to make sense and follow through, as contradictory as these processes may seem.
"If you know where you are going, if you are clear on the destination and how to get there, it may be that your clarity has fooled you into thinking you have traversed worlds when you have merely substituted familiarity and intelligibility for the uncomfortable yet transformative potential of bewilderment."
- Bayo Akomolafe
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).