Why is data integrity crucial in ARM analytics?

• A. It has no impact on decision making.
• B. Data that is incomplete can still support good decisions.
• C. Poor data can lead to wrong decisions in ARM analytics.
• D. It only affects storage costs.

Answer: (C)

In ARM analytics, the quality of the inputs drives the reliability of every conclusion you reach. When data is accurate, complete, and consistent, you can trust the outputs to reflect real conditions—like crew availability, training readiness, flight schedules, and fatigue indicators. That trust is essential because decisions about staffing, tasking, and risk management hinge on what the data says. If the data is poor, wrong, or incomplete, the analytics can point you toward unsafe or inefficient choices, such as overloading crews, misallocating resources, or missing emerging fatigue trends.

This is why the statement that poor data can lead to wrong decisions in ARM analytics is the best answer. The others miss a core reality: data quality directly impacts decision making, incomplete data generally undermines, not supports, good decisions, and data quality issues affect more than storage costs— they affect safety, compliance, and operational effectiveness.