Dan Braha: Applying Complex Systems Theory to Real World Data

Dan Braha By Lynne Weiss
January 29, 2013

Dr. Dan Braha, visiting professor in MIT’s Engineering Systems Division, has spent his career applying complex systems theory to engineering systems, biological systems, financial systems, and product development systems. He will offer his insights in a February 11 SDM Systems Thinking Webinar titled "From Politics and Finance to Power Grids and Products: Addressing Complexity in the Interconnected World."

Braha, a co-faculty of the New England Complex Systems Institute (NECSI) and a full professor at the University of Massachusetts, Dartmouth, began his career in engineering design, operations research, and supply chain management. He has also contributed research to semiconductor manufacturing, data mining, and artificial intelligence. His transition to complex systems research has been continuous and gradual, he said, dating his interest to 1993, when he started exploring statistical physics in the context of large-scale engineering design. The move to complexity theory has shifted the focus of his research from only looking for "the best solution," to trying to "understand how systems behave—whether engineering systems, product development systems, or social networks."

In his webinar, Braha plans to discuss what he said are four basic characteristics of complex systems:

  1. Universality. "You can describe many systems across domains and you will find universal properties. The same underlying principles can describe the evolution of language, the evolution of species, and the evolution of companies."
  2. Coupling and Connectivity. "Systems can be loosely coupled or they can be tightly coupled. In the context of complex engineering systems, you can change the characteristics of highly connected ‘nodes’ which could serve as leverage points for drastically improving the performance of the system. For example, making highly connected components of a piece of software less dependent on each other could dramatically decrease the number of defects in open source software development. In the context of financial networks, regulatory requirements could be set higher for banks that carry the highest risk to the system."
  3. Phased Transition. "The complex systems community looks for signals that a system is about to go into a phase transition. For example, they want to find signals that the economy is on the edge of transition. Think about product development. We can have a state where everything is stable, on time, on budget, but if one element becomes unstable, the whole system goes out of control." Braha said that too much stability is not necessarily ideal. "To increase innovation, you want to be on the border. At the edge of chaos, innovation goes up, but you also expose yourself to vulnerabilities."
  4. Out-of-Equilibrium Dynamics. Braha suggested that a mayor who wants to lower a city’s crime rate has to think about internal influences—among the people committing the crimes—and external influences—for example, the strength of the police force or the health of the educational system. "We have developed mathematical models to describe these dynamics in finance and other systems."

The value of complexity research to industry lies in the potential for prediction, but the accuracy of prediction depends on understanding the underlying principles. People focus on what is going on in their immediate environment, but "If you step back," Braha said, "you see more connections. My goal is to understand the big picture—how all of us are connected and how one person’s behavior can affect someone else down the road."

Dan Braha