Behavioral Business Intelligence
Behavioral Business Intelligence (BBI) takes you beyond traditional business intelligence of basic data analysis and dash boards. BBI is predictive analysis that incorporates the "human element" - to better understand and forecast what matters most to your business - people.
BBI requires the integration of different types of complex and dynamic data and human behaviors (or decision making), and more sophisticated predictive analysis approaches, such as modeling and simulation to manage the complexity of the real world.
Whether you are looking at the people within your organization, or externally at your customers, BBI is the next generation of forecasting that can assist your business in achieving its strategies objectives.
Simulation involves modeling, executing and studying a physical or social system to gain insight into the system’s functioning and outcomes. Simulation software allows you to test and observe “what-if” scenarios, and fine-tune proposed options, in a virtual environment before making large investments in the real world. This can result in better strategic decisions.
SimulAIt Micro-Simulation Platform
Our SimulAIt award-winning forecasting platform assimilates a vast quantity of data, knowledge, information, and business rules to create an accurate virtual simulation of a behavioral system to a high level of detail. The ability to integrate social, economic, political, and environmental behaviors of a system enables highly accurate models to be created. These models enable better predictions to be made through a greater understanding of how people behave and respond to change, and to ultimately ascertain the impacts of various influences (i.e. marketing, prices, etc.) in driving decisions and behavior change. The power of SimulAIt is in its ability to not only predict future outcomes, but explore options that can influence future outcomes.
SimulAIt’s underlying technology is based on artificial intelligence, namely agent-based modeling.
Agent Based Modeling
The theory behind agent-based modeling can be described using ant behavior as an example.
Ants exhibit what appears to be efficient, coordinated, and adaptable behavior when collecting food – working together to feed the colony. One would assume there is a central manager coordinating this complex task. However, this is not the case, and this complex behavior is driven by each individual ant following three simple rules: if you see food pick it up; release a chemical signal; and follow any chemical trails you come across. Ants’ sophisticated behavior for collecting food is there the emergent behavior of these three rules.
Human (e.g. consumer) behavior can also be described by rules which are driven by their demographic characteristics, situation, and preferences. Organizational or mass-consumer behavior can be predicted by observing the emergent behavior of millions of individual people.
SimulAIt uses agent-based modeling to help you understand and predict human behavior of mass-consumers or organizations.
Agents are autonomous software programs that are based on the human cognitive model, and thus can mimic human behaviors and decision making. Using prescribed rules, each agent can mimic the complex behavior of a broad range of individual people. Rules are constructed by integrating different types of data to better understand how different people make decisions under different circumstances. Many agents can be used to mimic millions of people in the real world to simulate a population or organization. The simulation can be used to observe the emergent behavior of the system (i.e. the forecasts), as well as the specific behaviors of individual people (i.e. the “why” behind the forecasts).