Avoid Bad Decisions – Simulate Your Process - Predict Future Outcomes
Predict Future Outcomes Using Simulation in the Public Sector
Simulation in the Public Sector
Simulation in the public sector allows leaders to capture and analyze complex systems so that they can increase performance, reduce risk, and operate with a smaller budget. Leaders must find a way to achieve their goals in an increasingly complex environment.
Government and Department of Defense agencies are held accountable for maintaining readiness while facing budget cuts. New technologies, policy changes, and objectives make it difficult to make strategic and operational decisions that get us closer to our goals.
Simulation modeling and software are extremely crucial in the government sector as engineers, program managers, analysts are able to use simulation modeling to understand and evaluate ‘what-if’ scenarios to impact change. Simulation is vital in situations when changes to systems are either difficult to implement, involve high costs and inherently complex systems, and deal with large amounts of data and variables.
Some examples of computer simulation modeling in the public sector are the fields of: defense (stability and reconstruction projects, optimize the planning of military operations, capabilities planning, resource management, non-traditional warfare strategies), biosciences (models of biological systems), health care (health care delivery systems), ecology and environment (evaluating renewable energy resources, weather forecasting, climate change, wildfire prevention), airports (air traffic control, reducing delays, airport infrastructure projects, flight simulators used for training pilots, evacuation planning), public transportations (buses, rail, metro, car traffic, car crash modeling, public infrastructure projects), sociology and behavioral sciences ( crowd planning for public safety, evaluating social norms, social influence, modeling human behavior and command decision making), economics and business analysis (economic impacts of preventative programs, policy interventions, agent-based modeling to evaluate economic aspects of adaptive management of natural resources).