The key to building a data driven future
ML & AI + MO = Complete Data Science Toolbox
ML makes predictions while prescriptive analytics (aka MO) makes decisions. When your problem involves complex tradeoffs between competing activities and allows for trillions of possible solutions, only MO has the power to find the best or optimal one.
The future Decision Scientist
While ML can enable you to make predictions, mathematical optimization MO empowers you to make decisions. When your problem involves complex tradeoffs among various (and often conflicting) business objectives and has an astronomical number of possible solutions, only MO has the power to find the best or optimal solution – which can be used to make optimal business decisions.
MO and ML are complementary technologies, and more and more companies are developing and deploying applications that combine MO and ML. MO technologies can leverage ML-generated predictions by using them as input for MO-based solutions and decisions. A good example of this is predictive maintenance: ML can enable manufacturers to predict when machine failures are likely to occur, and then MO can use these ML-based predictions to help create optimal maintenance schedules that minimize resource costs and production disruptions. Also, MO-based solutions can be utilized to help shape, retrain, and improve ML models – which can decay over time.