Every year the World Bank publishes its Development Indicators data, which we analyze in order to measure and track the resilience (fragility) and complexity of countries, macro regions and of the world as a system. The goal is to produce strategic systemic information for governments and government agencies especially in the context of management of disasters, crises, social unrest and conflicts, not to mention critical infrastructure protection.
WB data spans economy, energy, transportation, information, education, health, infrastructures, telecommunication, debt, ecology, crime, ethnic and religious aspects, finance, military, etc. A total of over 1400 Development Indicators is provided per country and macro region. The picture one can extract from such data is broad-scope, broad-scale, offering a unique type of new information, knowledge and insight into the intricate dynamics of nations and of the world as a system. Providing one analyzes the data from a particular point of view.
Our analyses of data have little or nothing to do with conventional means or techniques which rely, for example, on statistics, regressions, cluster analysis, neural nets, machine learning, PCA or fuzzy set theory, just to name a few. Our techniques are based on the quantitative analysis of the complexity and its structure, and have been developed starting from a blank sheet.
The reason it is so important to understand how complexity is structured as well as its makeup is because concentrations of complexity within a system, any system, constitute sources of fragility. It is obvious what to do with similar information from a defense as well as aggression points of view.
The analysis we report in this short blog in relative to three countries, namely China, Israel and a country we will call Xanadu (nothing to do with the Xanadu Region on Saturn’s moon Titan, or Kublai Khan’s empire). The analyses, as mentioned, are based on over 1400 parameters provided by the WB. This information is of course public.
Clearly, similar analyses may be performed on data gathered by intelligence agencies and governments. In today’s geopolitical context such analyses can deliver precious information resulting in a strategic advantage.
For each of the countries, the World Bank groups the 1400+ indicators by sectors. These are:
- Economic Policy
- Education
- Environment
- Financial sector
- Gender
- Health
- Infrastructure
- Poverty
- Private Sector
- Public Sector
- Social Protection
Each of the above comprises tens, sometimes hundreds of indicators. We illustrate the contribution of each sector to the overall complexity (fragility) of each country. In addition, we also report the complexity makeup (known as Complexity Profile) of two sectors: Infrastructure and Financial sector. These are probably the two key sectors of any modern state.
China
Israel
Xanadu
An in-depth analysis is not the goal here but we do wish to point out a few interesting issues.
The impact of Infrastructure in China is the greatest of the three countries. No surprise here.
Israel has the smallest impact of Poverty.
Xanadu has the highest impact of Education, more than double that of China. This is quite a surprise.
The impact of Financial sector in China is greater than that in Israel.
The skyline of the Complexity Breakdown of the Infrastructure Sector (bar char on left of each image) in China is much more balanced than that of the other two countries.
In Xanadu the Infrastructure sector impact appears to revolve around 2-3 key variables.
The Financial sector (bar chart on the right of each image) in Xanadu is less articulated than in Israel or China. This is not surprising.
Details regarding the complexity makeup of each sector of each country are not freely available but may be purchased.
An even more futuristic, and perhaps more significant analysis of this sort of data is the analysis of all countries in a single shot. What this reveals is, for example, inter-dependencies between countries, and we’re not just talking of flow of capital but of correlations of activities that are invisible to conventional mainstream techniques such as AI. Moreover, sudden jumps of complexity can be extremely revealing as they generally point to crises or pre-crisis situations.
Artificial Intuition 
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