Systems and Strategy: Causal Maps, Complexity, and Strategic Competition

In developing and implementing an effective "whole of nation" (WON) response to WON challenges in the modern world such as China's full-spectrum competitive strategy, it is essential to provide U.S. and other Western leaders with holistic situational awareness, "systems"-informed analysis, and cross-jurisdictional policy coordination. China's efforts to establish a "leverage web" of mutually reinforcing power and influence present U.S. policymakers with a long-term competitive strategy challenge, which the U.S. government is not yet well-organized to meet. This paper aims to explain one of the methodological tools available to help facilitate the systematic integration of subject matter expertise and systems analysis into policymaking.

Our leaders need more sophisticated ways to assess and describe their strategic environment, to understand key patterns and dynamics that affect U.S. interests (including systemic patterns generated by complex systems), to evaluate possible courses of action (COAs) in response to developments, to identify ways to wield coordinated levers of national power in response to strategic challenges, and to monitor and assess the impact of policy interventions. These tasks are particularly challenging given that the nature of complex systems—such as the global security environment—undermines the linear assumptions of traditional policymaking (i.e., that by devising the right policy input, one can reliably drive the system to the desired outcome). Complexity thus means that national leaders cannot predictably "direct" outcomes.  Nevertheless, policymakers may still be able to influence events constructively if their decision-making is informed by "systems"-based analyses that help them direct efforts at those elements of and linkages within the complex system where intervention is likely to have the most impact.

The MITRE Corporation's Center for Strategic Competition has developed and refined methodologies to: (1) aggregate the input of multiple subject matter experts (SMEs) in a scalable way through the preparation of causal maps that capture and display salient features of a complex environment; and (2) understand such causal maps in ways that identify characteristic patterns that can help identify effective interventions designed to break, impede, or limit competition. This approach allows SME input to be harvested and aggregated in a methodologically rigorous way, and at scale, creating highly sophisticated graphic understandings of the environment that can also be “unpacked” so as clearly to explain the reasoning behind recommendations. This permits leaders to assess its plausibility, identify and interrogate underlying assumptions, spot areas of relative consensus or contestation, test counterfactuals against received wisdoms, and evaluate policy alternatives. 

Causally mapping an adversary's strategy and analyzing it from a complex systems perspective, therefore, can help identify: (a) where the adversary's activities present the greatest threat; (b) where one's own policy interventions may have the greatest chance of affecting that adversary's success or advancing one’s own; and (c) how to respond by identifying policy interventions that add new causal connections among key actors, impede, delay, or alter positive feedback dynamics, and introduce negative feedbacks that dampen "runaway system" dynamics.  Using such tools, it may be possible to discover and depict sub-system interrelationships even in a complex policy problem such as China’s global strategy.