Constructing Leading-Indicator Sustainability Metrics for a Corporate Complex Adaptive System Using Graph Algorithms

摘要

Complex Adaptive Systems are emerging as a viable framework for developing sustainable organizations. Yet the sustainability-focused KPIs that provide insight into baseline realities and needed development efforts that would increase the likelihood of longer-term organizational sustainability, remains relatively immature at best. In this paper, we suggest a composite-KPI model to determine the likelihood of organizational sustainability based on observations of the four-fold foundation of sustainable physical, chemical, biological, and more complex behavioral systems. KPIs along each of the four dimensions of system-harmony, system-knowledge, system-energy, and system-service, pillars of sustainable physical, chemical, biological, and complex behavioral systems, leverage Closeness, Page Rank, Betweenness, and Article Rank algorithms – all Centrality measures respectively. These KPIs are leading as opposed to more common business and fmancial-based lagging indicators, and they were generated using Zappos-inspired datasets focused on intra-organizational activity. Values for generated graphs and histograms and their associated statistical metrics were compared to metrics generated from idealized graphs and histograms using a Watts-Strogatz model. The delta between the sets of generated metrics generates the respective KPIs. The organization size was estimated at approximately 600 teams.