IBM has launched a system designed to help councils to reduce the unintended negative consequences of decisions on citizens and to uncover hidden beneficial relationships among council decisions. The new analytics software is now providing the service to the City of Portland in the US.

The system overcomes the difficulty of councils functioning as silos where decisions in one policy area often have very little interaction the situation elsewhere. This limits the possibility that a decision action in one area having unexpected affect on another area.

The project uses the existing dynamic engine which contains over 3,000 equations from past work with cities. At the beginning of a new project the IBM government experts conduct a series of knowledge-gathering workshops with dozens of people who have expertise about that particular city, including economists, educators, police officers, city planners, demographers, elected officials, business leaders, electric and water utility providers, real estate developers, transportation experts, health care providers, and other community leaders.

Next, the input from council subject matter experts and data is analysed with software specialized for determining how systems evolve over time, incorporating feedback and delay. The resulting system of simultaneous differential equations is calibrated and evaluated against up to 10 years of historic data from the client city.

The result is a model that builds on experiences from past clients but uniquely simulates the dynamics of the client council.