How deeper conversations can engage with the complexities of peace
"One good conversation can shift the direction of change forever." Linda Lam
There are many ways to view complex problems such as conflict and peace. The current conflict in Gaza highlights the myriad of competing points of view and ways to tackle the problem. These various angles often steer people toward thinking in silos, where they reaffirm their existing narratives without necessarily understanding their connections to other perspectives. In this article we examine ways to overcome this siloed thinking by adopting a systems analysis approach. We explore ways to harness different perspectives, so that people can have deeper conversations that not only make sense of their own ideas but also how they connect to others.
Building on our previous blog thinking in systems we draw from the lessons learnt applying a systems analysis approach to examine complex problems in Yemen, Myanmar, Syria, and Afghanistan. Through our work collaborating with practitioners and policymakers, we examine the methods we’ve tested to capture these different perspectives and how a process of collaborative discussions can uncover new ways to navigate these intricate problems.
Can systems analysis improve our ability to support peace?
A recent study by the University College London’s Institute for Innovation and Public Purpose (UCL) defines systems analysis as a toolkit portraying the world in systems. These tools aid in mapping out key actors, spotting behaviour patterns, and capturing mental models that decipher systems driving repression and hindering empowerment. For practitioners, system tools provide a lens to scrutinise conflict’s root causes or how power structures respond to violence.
In the context of peace processes, ‘soft systems’ methods are often preferred for their heightened focus on the social aspect of systems and the pivotal role of actors in shaping them. Soft methods, mostly qualitative, stress the importance of merging varied perspectives and forging shared understanding. This approach entails delving into the ‘systemic problem,’ aiming to craft a shared comprehension of system behaviour. These collaborative analysis discussions prove invaluable, not just for deepening the understanding of the problem but also for shifting participants’ perspectives. Gray and Burns[1] stress that a collective system analysis (Systemic Action Research) can pave the way for more enduring outcomes. As participants view the situation from varied angles, they can forge new connections and unearth fresh approaches to navigate the given scenario.
In our collaboration with practitioners, we’ve been examining ways to expand systems analysis and make it more readily available. So far much of work has been at the national level, engaging with policymakers and researchers, yet with an emphasis on connecting to local dynamics and their counterparts. Our aim is to boost peoples’ ability to manage complexity—helping them have more meaningful conversations and identifying who to have them with. These deeper conversations enabling them to articulate clearer pathways for collaboration that will lead to more inclusive peace processes.
[1] Gray, S. and Burns, D. (2021). Local agency, adaptation, and vertical integration of bottom-up peacebuilding: reflecting on systemic action research in Myanmar. Peacebuilding, 9(1), 15-39.
Developing an analysis that reflects different perspectives
To harness different perspectives, we take our partners through a process of collective exploration. During participatory analysis workshops we use visual tools (graph database technology), to connect different parts of the system and to look at the problem from different angles. This ability to map the different perspectives and connect them in different ways helped us to bring structure to their analysis and develop a greater shared understanding.
More importantly the workshops facilitated a process of asking more in depth and detailed questions. To answer these questions, participants would reach out to their counterparts or use a ‘proxy analysis’ approach. This approach collates data from a wide range of pre-existing sources (Qualitative reports i.e., PEAs/Media reports, Descriptive data – ACLED/ACAPS, or Network Data) and connects them to our existing systems analysis.
We found the ‘proxy analysis’ approach allows us to connect a wide variety of data and add information that answered specific questions, without necessarily adding to the complexity. For example, when exploring the incentives driving specific causal loops or identifying the actors steering these incentives, would lead us to investigate existing analyses for precise information on actors’ motivations. Similarly engaging in deeper conversations of who benefited or was damaged by the impact of violence on economic activities would lead us to search descriptive data sources. This helps us understand how different groups were affected in different locations and by different events.
We found this iterative query-led process was valuable in transforming data and information into knowledge and understanding, enhancing peoples’ ability to articulate their analysis. This improved their ability to engage in deeper conversations with wider audiences about their context. Through these discussions our partners could validate their understanding as well as expand the boundaries of their analysis based on its relevance in specific conversations.
How do we develop a query-led approach
Taking a query-led route to enrich our grasp of the context is achievable by developing conceptual frameworks that structure the data. In joint analysis workshops with partners, we naturally immerse ourselves in discussions about the categories of elements our partners aim to portray (actors, institutions, armed groups, locations, events, or incentives) and the diverse ways they want to illustrate their interconnectedness. For instance, whether the focus is on investigating collaboration, competition, or the influence of different actors.
Through these discussions, we are able to create data models. These data models are conceptual representations of the data (See Figure 1 below) and its relationships, that can help the researchers organise and connect their data in a structured way. While distinct from the systems analysis itself, it is important to note that the data model represents a preparatory phase essential for simply structuring the data.
Figure 1 – Illustrative example data model from Myanmar
We are seeing that developing data models are helpful for making the process of collating data more efficient but more importantly for capturing the mental models that help make sense of the system. By structuring information, our partners are better able to synthesise their analysis in ways that make sense for them and their objectives. It is this process of helping them bring greater meaning to their analysis that makes it easier to interact with complexity.
How can deeper conversations support local peace efforts?
Improving our partners’ ability to navigate complexity makes it simpler to guide them through exploration and discovery. It allows them to formulate more precise research questions, spot gaps in their research, create straightforward visuals explaining behaviour patterns, and conduct comparative analysis across different contexts. These elements aid practitioners in engaging in conversations that can pave the way for more inclusive, locally-driven interventions.
We have been supporting practitioners with our systems analysis approach to identify specific local networks that can be reshaped, based on locally specific interests, identities and incentives. Building on a blend of ‘proxy analyses and joint analysis workshops, our partners are linking the national-level dynamics to the specifics in different localities. In a validation process with local actors, we have identified different power structures in Syria, the networks behind these structures, and how these structures influence cause-and-effect relationships within a system. As a consequence, our partners are connecting national dynamics to local governance structures in Syria and to local networks (Figure 2 below).
Figure 2 – Shows ways to connect national level dynamics to local level actors
This iterative process aids them in forming a shared understanding of their problem. It also pinpoints specifics about individual blockers, influencers, or bridges within and between these networks. The combination of deepening their comprehension of systemic challenges and connecting them to the actors driving the problem improves their ability to translate analysis into actionable insights.
As they collaborate and engage with actors closer to the context, they identify leverage points. These are places within the systems where improved collaboration and deeper conversations between key actors could increase the prospects of systemic shifts. The use of visual tools also allows us to create clear visual representations of relevant systems, helping overcome the language and cognitive barriers of systems analysis.
In the next blog, we’ll delve into how we employ systems analysis to test scenarios, design interventions that do no harm, formulate local peacebuilding interventions, develop coordinated national strategies, and facilitate a process of continuous adaptation and learning.