Implementing Analytics Using the Four-Stage Maturity Model

IoT technology has ushered in a new age of sensing, interpreting, and acting on the world around us. However, analyzing the influx of data has proved challenging for organizations. This data can provide valuable insight that businesses can utilize to improve their operations, but in order to do so effectively, they need a robust plan for implementation. This raises the question: where should companies start in the process of implementing analytics?

The Power of Prediction

Join us on September 27, 2018 to find out how to implement analytics using the four-stage maturity model to improve decision-making by leveraging massive amounts of data. Register using the link below.

In this webinar we’ll cover key capabilities that transition from a fully manual-oriented data collection and interpretation regime into intelligent business processes that prevent problems before they occur, monitor the outcomes of decisions to learn what is effective, and continually update interpretations and actions in response to an ever-changing world.

The Four-Stage Analytics Maturity Model

In order to use data to prevent problems before they occur, organizations must adhere to some version of the four-stage analytics maturity model: automating data collection, implementing descriptive analytics, evolving to predictive analytics, and leveraging machine learning for prescriptive analytics.

Register now to find out how to implement analytics using the four-stage maturity model.