The first week of July is traditionally the week of the Mesopartner Summer Academy. This year, the 11th Summer Academy took place in Berlin – the 4th in the German capital. Systemic Insight was again a central pillar of this year’s Academy. We introduced it in a whole day session as a process of discovery in situations where solutions are not obvious.
A process guided by Systemic Insight enables organisations and networks of stakeholders to search for solutions to improve the performance of complex systems or emergent networks. This instrument draws on cognitive science and complexity thinking as well as experiences in the design of participatory social and economic change initiatives such as social labs or cluster platforms. At the same time, Systemic Insight was designed to allow stakeholders to work within complex issues without having to know the theories and understand abstract complexity thinking.
Systemic Insight is an iterative process where stakeholders explore the boundaries and constraints of a system in which the possibilities or solutions are unknown or uncertain. The format of collaboration, be it a multi-stakeholder platform or forum or purely bilateral interaction with the involved actors, is thereby not fixed but depends on the circumstance and can change over time. A high level of self-selection of participants into the process is encouraged. Self-selection means that local actors take ownership of the process by actively opting in, contributing to, investing in, and incorporating change in their own operations based on their interest to solve a problem or their identification with an issue.
In Systemic Insight meso level organisations are seen as central actors of change. Systemic Insight helps them to become more effective in managing change and resilient while assisting firms and networks to adapt to change in the environment. It shifts the focus of actors from responding to change towards actively testing ways to anticipate and actively create change.
The process enables stakeholders to challenge their own assumptions, discover and better understand the system and make sense of the constraints and possible opportunities. It guides them to intervene through portfolios of quick win activities or safe-to-fail experiments. Continuous learning and adjustment ensures an iterative and adaptive approach that is appropriate to tackle complex issues. In order to put learning and adjustment in the centre of the change initiative, monitoring and management functions need to be integrated to allow for decision making that is based on facts and current realities and needs.
As part of the Mesopartner research theme on complexity in development, we will continue to apply and further develop this approach. We seek to work with projects that are stuck and need a fresh approach to infuse the situation with discovery and innovative ideas.