By creating a computing environment that sets multiple technologies competing against each other, we are able to produce computer forecasts that contain, at a low level forecast error (SKU by customer for example), 25% less error on an absolute basis over any other forecasting engine currently on the market.
This is produced because our proprietary environment includes not only the 'old' technology of statistical/straight line modeling but also a number of technologies that allow for non-linear modeling including genetic algorithms, fuzzy logic, expert systems, and neural nets / artificial intelligence.
Demand Commander is able to learn, improve, and adapt over time as it interacts with large amounts of data. This includes both historical as well of future looking data normally external to an organization such as demographics, marketing pricing, raw material pricing trends, and financial circumstances such as interest rates.