Complexity Maps of Railway Operations

QCM technology allows to make very quick risk and resilience assessments of all sorts of systems of processes. All it takes is data. Data may be sampled over time, space or frequency. Consider, for example, the following monthly data (only a small portion is shown) of failure counts of a railway operation. The data simply…

Increasing Cybersecurity. Locally.

A recent blog by CISCO speaks of how QCM – Quantitative Complexity Management – is used in anomaly detection in highly complex systems and contexts. In particular, it speaks of QCM as being able to detect the existence of an anomaly without having seen it before. Such capability goes beyond Machine Learning in that QCM…

Complexity-Based Early-Warnings in Defaulting Companies

The search for early-warning signs is one of the key issues for decision makers. The advantages of knowing in advance the evolution towards critical situations are obvious. Complexity is a new and powerful indicator that quantifies the degree of sophistication and governability of a business and which impacts its Resistance to Shocks[1] (RtS). Both complexity…

How To Save Democracy From Itself

Prologue from “Governing a Liquid Society – How to Save Democracy From Itself”   In the past the Earth was populated by numerous civilizations. The Greeks, the Incas, or the Romans are just a few egregious examples. Because the temporal and spatial correlation between those civilizations was often non-existent, or very limited, if one happened…

Complexity and Revisiting Anomaly Detection

Wikipedia: “In data mining, anomaly detection (also outlier detection) is the identification of rare items, events or observations which raise suspicions by differing significantly from the majority of the data. Typically the anomalous items will translate to some kind of problem such as bank fraud, a structural defect, medical problems or errors in a text.…