Our Science

According to the Santa Fe Institute, Complexity Science is premised on the assumption that seemingly disparate phenomena, both natural and social, evolved and constructed, can be understood using a common conceptual framework.  The goal of the science is to better understand complex adaptive systems (CAS).  A CAS is a heterogeneous collection of interacting agents that evolves over time at the macroscopic system scale.  Any agent in the system interacts with one or more other agents in any "move" of the system according to the rules.  Some or all of the agents in the system also base their decisions about what to do in the next move based on the macroscopic state (macro state) of the system or on conditions exogenous to the system having some impact on it.  In short, a CAS is a setting where behavior is hard to predict, outcomes are not foregone conclusions and participants evolve and adapt to circumstances, influences and to each other.  Examples of complex adaptive systems include standing ovations, the stock market, ant colonies and yes, the consumer marketplace.  Once a CAS is modeled and understood, it can be "tinkered" with and emerging behavior and outcomes can be observed.  Many times, unprecedented results occur that historical analysis cannot explain.  Examples of such phenomena in the consumer marketplace include the emergence of bottled water and sweet tea.

Agent-based modeling (ABM) is a simulation technique that is being applied by ThinkVine to solve business problems. At a high level, an ABM model is made up of agents (independent, decision-making entities) and the behavioral rules that they operate against. In the ThinkVine model, consumers and media both represent agents that interact with each other in a simulated environment. Unlike traditional top-down approaches that focus exclusively on historical results, ABM models employ a bottom-up approach that gets to the "why" historical results occurred. In ThinkVine's case, what consumer traits, marketplace dynamics, behavioral rules and media interactions led to consumers behaving the way that they did. Just like consumers, ABM models can adapt and evolve, giving them emergent properties.