Which of the following is an example of prescriptive analytics?

Prescriptive analytics involves recommending actions based on data analysis to optimize outcomes. In this context, optimizing supply chain logistics to minimize costs serves as a prime example of prescriptive analytics because it not only assesses the current state of logistics but also determines the best course of action to achieve cost efficiency. This involves using algorithms, mathematical models, and simulations to analyze various scenarios and suggest the most effective strategies for managing the supply chain.

On the other hand, summarizing past sales data focuses on descriptive analytics, which examines historical data to understand what has happened without suggesting future actions. Identifying customer purchasing trends is an instance of diagnostic or predictive analytics, where the aim is to interpret data to pinpoint what factors influenced past behaviors or forecast future outcomes. Creating visual dashboards of performance metrics showcases descriptive analytics as well, presenting data insights visually for easier comprehension, but it does not recommend specific actions to improve performance. Therefore, optimizing logistics represents the actionable, decision-oriented nature of prescriptive analytics.