In which of the following situations would data analytics be most efficient and practical?

Data analytics can enhance decision-making and operational efficiency in various situations. In the case of a farm equipment manufacturer coordinating production across plants, data analytics can efficiently manage inventory levels, monitor production processes, analyze demand fluctuations, and optimize supply chain operations. By utilizing data analytics, the manufacturer can streamline operations across multiple locations, leading to reduced costs and improved productivity.

Similarly, in a healthcare network deciding on treatment options after FDA approvals, data analytics is vital for evaluating clinical outcomes, analyzing patient data, and determining the most effective treatment protocols. It allows healthcare providers to leverage large datasets to discern patterns, identify successful treatment pathways, and enhance patient care decisions.

Both scenarios indicate contexts where data analytics can be effectively employed. The integration of data analytics in production coordination and healthcare decision-making highlights its versatility and importance in various sectors, making it the most efficient and practical choice.