A Generalized Quantitative Framework for Complex Adaptive

A complex adaptive system is composed of interrelated, autonomous parts or agents which dynamically adjust based on internal performance and external environment. Such systems are inherently challenging to characterize and to predict. Quantitative characterization of systems is typically accomplished through a set of systems "metrics" with associated interrelationships. We propose a combination of this traditional practice with the concept of asset-based thinking from community development. This approach suggests characterization of system parts/assets, capabilities, relationships, groups, and needs leading to a diverse group of systems measure types geared toward long-term systems sustainability. In developing this framework, we seek to expand beyond the implicit and often unrecognized Newtonian-Cartesian system view of tradition systems metrics. The proposed framework is inspired by complex adaptive systems both in its structure/taxonomy and in its associated development process. The paper provides examples from literature supporting such integration of metrics and metric processes. Next, we share a community development-based analog that provides the context for creating the quantitative framework. Subsequently, the generalized quantitative framework is described organized according to a novel taxonomy. Example metrics are proposed to be purposefully abstract in order to be conceptually translated and adapted for a given practical context.