Predictive Analytics
Predictive analytics is the use of statistical algorithms, machine learning, and data analysis to find patterns in historical data and forecast future events or outcomes. It helps organizations make informed decisions, optimize strategies, and reduce risk based on what is likely to happen rather than only what already happened.
A predictive model is trained on historical records where the outcome is known, such as past sensor readings paired with whether the machine later failed. Once trained, it scores new data and outputs a probability or forecast, which is updated as new data arrives.
In manufacturing, predictive analytics can forecast which machines are likely to fail soon based on vibration, temperature, and run-time data, so maintenance is scheduled before a breakdown. It can also forecast demand or flag batches at risk of quality problems.
Predictive analytics differs from descriptive analytics, which reports what happened, and from prescriptive analytics, which recommends what to do about it.