Which Business Intelligence (BI) processes are correctly applied by a logistics company aiming to reduce fuel costs by improving delivery routes?

To identify the correct application of Business Intelligence (BI) processes for a logistics company aiming to reduce fuel costs by improving delivery routes, let's analyze each action:

• a. Integrating real-time GPS data into a central BI dashboard.

  • This is a fundamental BI process. It involves collecting raw data (GPS data), integrating it into a centralized system, and making it accessible through a dashboard for monitoring and analysis. This allows the company to track routes in real-time and identify potential issues. This is a correct application of BI.

• b. Using data mining to identify route inefficiencies.

  • Data mining is a core analytical technique in BI. It involves sifting through large datasets to discover patterns, anomalies, and correlations. Applying data mining to route data can reveal inefficiencies such as suboptimal paths, frequent detours, or areas with high traffic congestion, which directly helps in improving routes and reducing fuel costs. This is a correct application of BI.

• c. Deciding routes solely based on driver intuition.

  • This approach relies on subjective experience rather than data-driven insights. Business Intelligence aims to move away from intuition-based decisions towards evidence-based ones. Therefore, this is not a correct application of BI.

• d. Applying data visualisation to communicate performance metrics.

  • Data visualization is a crucial component of BI. It involves presenting complex data and analytical findings in an easily understandable graphical format (e.g., maps, charts, dashboards). This helps stakeholders quickly grasp performance metrics related to routes and fuel consumption, facilitating informed decision-making. This is a correct application of BI.

• e. Eliminating predictive analytics to reduce processing complexity.

  • Predictive analytics is an advanced BI capability that uses historical data to forecast future outcomes (e.g., predicting traffic patterns, optimal delivery times). Eliminating it would reduce the sophistication and potential value of the BI system, especially for route optimization which benefits greatly from forecasting. While it might reduce complexity, it goes against leveraging BI for comprehensive decision-making and cost reduction. This is not a correct application of BI for this goal.

Based on the analysis, actions a, b, and d are correct applications of Business Intelligence processes.

The final answer is $\boxed{\text{D}}$