Predictive Analytics

In the future, the competitiveness of your company will only be maintained if your decision makers can predict important business opportunities and events, and thus be able to respond to them quickly. Big Data Analytics will continue to help with this, as well-targeted data analysis using statistical models will enable the realistic prediction of potentials and events that will benefit your planning security.

Predictive Analytics enables predictions through stochastic analysis based on internal company data (e.g. from the ERP system) and external data (eg price data, weather data or traffic flow data). Social media also plays an important role in many applications as a data source, especially when it comes to customer opinions and the prediction of customer behavior. Predictive analytics is particularly powerful when it comes to including a lot of data from different data sources, where stochastic algorithms and machine learning are used.

Predictive Analytics is already being used today in the field of weather forecasting. Also, the prediction of credit defaults or credit checks (credit scoring) is a widespread field of application. Especially the rating of the creditworthiness is not an area of application, which is limited only to banks, because also many other enterprises must be able to judge their (potential) customers with regard to their creditworthiness. Further typical fields of application:

  • Sourcing and storage optimization through improved forecasting
  • Increase in sales through customized offers and cross-selling
  • Risk analysis, e.g. churn prediction (prediction of customers’ leave)
  • Purchase optimization of raw materials at best time
  • Logistics optimization by finding the fastest transport route
  • Production optimization through forecast / avoidance of machine failures (predictive maintenance)
  • Predictive Modelling

    Unsere Algorithmen decken nicht nur deskriptive Statistikmodelle ab, mit denen sich Gruppenverhalten vorhersagen lässt, sondern auch Predictive und Decision Modelling. Somit kann die umgebungsfaktorenabhängige Wahrscheinlichkeit von Verhalten und Ereignissen einzelner Prozesse oder Individuen berechnet werden.

  • Social Media Data

    Predictive analytics is particularly powerful with the inclusion of data from social media or other internet platforms. We enable the connection of such unstructured data, for example for a customer loyalty analysis (churn prediction).

  • Automation

    Our decision modeling can also be automated, for example, for predictive and automated maintenance (predictive maintenance) or purchasing planning (predictive order analytics).