DEFENSE AND SECURITY

National Power (Capacity) Model

STM ThinkTech, based on the inadequacy of handling a complex phenomenon such as national power with a single index value using linear approaches and methods, developed the National Power Model by using the Systems Thinking approach and System Dynamics method.

In the model; human power, military power, economic power, political power, psychosocial power, technological power, and geographical power elements and their parameters (~1500) interacting with each other are dynamically analyzed.

The model provides a holistic and new mental perspective for the phenomenon of National Power, due to the strengths of the approach and method used. This mental model takes National Power as a concept that contains dynamic complexity and reveals the structural and behavioral dimensions that can be used in understanding and analyzing this complexity. The National Power Model, which can be considered as a high-level investment model especially for strategic level managers, provides its users with the opportunity to make dynamic foresights by creating different scenarios.

NATO Aggregated Resilience Decision Support Model

It is a Decision Support Model developed using the Systems Thinking approach and System Dynamics method in order to support NATO's decision-making processes in the face of strategic shocks such as pandemics, electricity blackouts, cyber attacks, and big human movements.

In addition to the effects of strategic shocks and the critical changes they will create, the model also analyzes the possible consequences of these shocks to the civil and military system elements. The model can make scenario-based analysis for the effects of strategic shocks in different areas (energy, transportation, communication, etc.) and possible risks. While the model provides strategic level decision support to NATO, it facilitates the decision-making processes of the authorities in terms of the actions to be taken and the measures they can take.

Morover, live strategic shocks data collected from open sources via Big Data method is transformed into information with Machine Learning algorithms and this information is inserted into the model.