Date: Issue 101 - November 2020
The contract for the third project related to the Resilience Decision Support Model, developed indigenously for NATO by ThinkTech was signed in August 2020. The new model, known as the NATO SHAPE Aggregated Resilience Decision Support Model, is an analysis of the effects of large-scale complex problems that will support decision-makers, and it will be used to make an integrated resilience assessment of eight countries. It is scheduled to be delivered to NATO on 31 December 2020.
The Aggregated Resilience Decision Support Model focuses on the sustainability of aggregated resilience capacity, and analyses the strategic effects of, and the critical changes resulting from, such events as pandemics, electricity blackouts, mass migration and cyber-attacks, and their possible consequences on both civilian and military systems. With the developed model, the effects of different types of strategic shocks in various fields, such as energy, transportation and communication, as well as possible risks, can be evaluated based on specific scenarios. This entire process provides NATO with decision support at a strategic level and facilitates decision-making authorities in determining the steps to be taken and the measures they can take in a given circumstance.
In a Request for Information Document published by NATO Allied Command Transformation (ACT) in August 2018, solution proposals were sought related to the “assessment of NATO’s resilience capacity” problem. The solution approach and methodology provided by STM was accepted by ACT, and after the first contract was signed in October 2019, the first prototype model was completed and delivered to NATO ACT. A second contract was signed with STM in February 2020 for the upgraded version of the first model, which was successfully run in a NATO-wide online workshop on April 21, 2020. For this latest model, to be developed as part of the third project, data collected from open sources regarding strategic shocks will be processed using various machine learning algorithms.