Predictive Analytics
Predictive analytics is the prediction of future events based on historical data. With the help of statistical algorithms and machine learning, it is possible to predict future outcomes. For this, a special knowledge of the influencing factors of the events is of great importance. If predictive analytics is operated correctly, production downtimes due to missing materials can be avoided, machine downtimes due to unplanned failures can be reduced and production output can be precisely matched to predicted consumer behaviour. Predictive analytics thus brings operational improvements and risk reduction.
Predictive Analytics© https://www.pexels.com/de-de/foto/kaffee-tasse-smartphone-schreibtisch-106344/
Requirements for use
Data collection
The basis of predictive analytics is data. This data must be collected in order to make predictions for the future. In order for this data to be collected at all, machines or systems must be upgraded or replaced.
Data analytics
Data collection alone is not enough to do predictive analytics. For this, the collected data must be properly analysed. The knowledge about influencing factors of future events is in the foreground here.