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Pentagon lacks performance metrics for F-35's ALIS logistics system

The Pentagon is unable to judge the overall performance of the Lockheed Martin F-35 Lightning II Joint Strike Fighter’s (JSF’s) Autonomic Logistics Information System (ALIS) because it has not developed the performance metrics to do so, according to a US congressional watchdog.

The US Government Accountability Office (GAO) said in a report released on 16 March that testing ofindividual ALIS software version releases focuses primarily on whether the new ALIS version is performing “better” than the previous version. Specifically, ALIS testers have developed criteria to determine if the newest version of ALIS is functioning more efficiently than the previous version by comparing such tasks as screen download times.

The Pentagon still does have performance metrics for the F-35’s Autonomic Logistics Information System (ALIS), six years after the Government Accountability Office recommended it do so. (US Air National Guard)

The Pentagon still does have performance metrics for the F-35’s Autonomic Logistics Information System (ALIS), six years after the Government Accountability Office recommended it do so. (US Air National Guard)

However, these tests do not determine if ALIS is performing to a specified standard because the Pentagon has not defined that standard. The GAO recommended in 2014 that the Pentagon develop a performance-measurement process for ALIS that includes, but is not limited to, performance metrics and targets that are based on the intended behaviour of the system in actual operations. The Pentagon was also recommended to tie system performance to user requirements. After five years and with more than 400 F-35s fielded, the Pentagon has not yet established a performance-measurement process for the F-35.

Programme officials said in September 2019 that the Pentagon remains in the process of developing these metrics and has no set timeline for their completion. Such information could help address current and future ALIS performance issues and systematically measure ALIS functionality compared to intended performance.

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