Explain predictive modeling.

Predictive modeling is a statistical technique used to forecast future outcomes based on existing historical data. This method typically involves analyzing patterns and trends within the data to create a mathematical model that represents these relationships. By leveraging algorithms, predictive modeling can inform decisions by providing insights into potential future events, behaviors, or conditions related to various fields such as marketing, finance, healthcare, and more.

For instance, businesses might analyze past purchasing behavior to predict future sales or determine customer churn by interpreting past loyalty data. The strength of predictive modeling lies in its ability to aid organizations in making informed decisions that can lead to more effective strategies and outcomes.

The other options focus on specific applications or areas of business that do not encompass the broader concept of making predictions based on data. While assessing employee performance, improving customer relationships, and managing supply chain logistics might involve elements of data analysis, they do not directly define the core principle of predictive modeling.