As described in the overview page of this site, the “Action Intelligence” methodology which underlies the approach to this initiative aims to construct and visualize the socio-cultural “landscape” around a given initiative. Using a specific social taxonomy to organize data – both quantitative and qualitative, from macro to micro, and structured and unstructured, — this approach allows us to make sense of complex social issues and visualize linkages in order to provide new insights into those issues. In other words, when it comes to adaptation action, if we can better understand the context and details surrounding these actions, we will be better able to analyze and learn from them.
That being said, how do we choose what to capture and what to document in the face of countless contextual details? How do we balance the need to gather “all” the details and what resources would it take to do this? How do we decide what details are needed and where to prioritize our efforts?
One place to start is to identify what is the “need to know” information. Concrete focus questions can help define this set of information, and will guide the approach to the data gathering process. These questions will provide an initial entry point into any social landscape so that the context can be better defined. Action Intelligence, as a method to understand complex social contexts, is an iterative process, which continues to refine and expand the data collection step by step. . So first we need to find a starting point and a way to identify these concrete focus questions.
For this initiative, we are emphasizing two overarching questions that need to be addressed through this initial stage of the work.
- What is the “impact” of climate change adaptation activities on the people, groups and organizations that make up a specific location?
- How can we replicate or scale up successful adaptation activities in a different context?
When it comes to impact, the first question this raises is how do we define “success” of these adaptation actions? Part of defining success will be to identify what people view as “success” and what “indicators” or “data” will assess whether any given action has indeed been successful (more on this specific question in a future post). Once this is determined, we can gather information that would show how these factors of success are changing over time in the specific locations. With Action Intelligence, instead of simply tracking a solitary indicator before and after an intervention (as we often do through results frameworks or M&E structures), we can now look at the contextual details that relate to any specific indicator. Analyzing these indicators and their relationships with other data over time will help to understand the impact of any given activity. The focus here is to discern themes, patterns and trends. While this method does not necessarily focus on showing direct, causal relationships between adaptation action and a success indicator, analyzing changing social patterns and trends that define social contexts will give a good indication of impact and change over time. And all of this can be visualized.
With regards to replication and scaling up, this will take the question of “success” or “impact” a step further. If our objective is to learn from our adaptation experiences, not only do we want to be able to visualize impact or the change over time, but we also want to know which factors led to this impact. This is where we need to go back to the contextual elements, or socio-cultural landscape, surrounding an intervention. If we can analyze the relationships between these contextual elements, and understand what factors may have contributed to success, then we can capture evidence-based lessons learned.
At the same time, this methodology can also allow us to see the potential for replication through different social networks. We would be able to illustrate which people make up any given community and how do those communities regularly interact with other communities. For example, who is involved in developing local or national policies or defining budget allocations. Once we have the concrete evidence of impact, that is, knowing the “who, what, where, when and why” of what works in any given context, we then also know the who, what, where when and why” in order to support replication and scaling up.
These are big questions, and as overarching objectives they will guide the way we approach this work. What are the questions that are specific enough to focus our data gathering and analysis process? How long will the collection of detailed data take to illustrate the full picture? Time will only tell, as we start to assess what data we already have and what still needs to be collected.