Resilience

Resilience denotes the capacity of a system to withstand shocks and the ability to recover from them. Hence, it combines two different concepts: Robustness captures the structural and adaptivity the dynamic dimension of resilience.

Conversely, resilience cannot be reduced to notions of robustness or stability. Rigid systems in engineering or society can be quite robust against shocks, but once they fail, they never recover. Resilience addresses the recovery, i.e. the response after shock.

Resilience should also not be confused with performance. Quite often, performance is maximized at the cost of lowering of resilience. The burn-out of high-profile managers or the breakdown of just-in-time production illustrate the difference. Eventually, resilience is also different from flexibility. Agile response to trends and FOMO, the fear of missing out, can quickly lead to a loss of focus for our core business or our social values.

We want to understand how the two dimensions robustness and adaptivity play to together to constitute resilience as a systemic property. Our research is targeted at social and economic systems, the most challenging ones because of their very volatile dynamics. Examples include social organizations, collectives and project teams in companies. Differently from engineered or ecological systems, a resilient reference state cannot be defined because individuals join or leave and financial or supply relations change quickly.

To model such systems, we combine agent-based modeling and multi-layer network approaches. They allow to quantify the impact of agents and their relations, using massive data about the collaboration and communication of indiviudals or distribution relations between firms. Based on these information, we model the robustness and the adaptivity of socio-economic systems and propose a novel resilience measure combining these two dimensions.

Frank Schweitzer