Maintenance for Air Force materiel has traditionally been divided into two categories: forensic maintenance, which investigates problems that have already occurred; and preventive maintenance, which requires regular, comprehensive inspections. The former occurs too late to prevent failure; the latter often occurs too early. The desired outcome is neither forensic nor preventive, but rather predictive maintenance: knowing when failure is imminent and averting it. In February of 2019, the Department of Defense’s Joint Artificial Intelligence Center made predictive maintenance a reality, working with SOCOM to train machine learning algorithms on the performance history of 160th Special Operations Aviation Regiment Aircraft. “Fix it before it breaks.”
Now imagine predictive maintenance for the Pentagon’s most valuable asset, people. JAIC is already looking to AI to reduce operational costs and to limit casualties and collateral damage by enhancing mission precision. In the sprawling landscape of AI-enabled innovation, Orchestra pursues a very specific application: enhancing the value and the accuracy of personnel assessments to predict future health and performance. In our belief that organizations can only lastingly build what they can effectively measure, Orchestra regards intelligent measurement as instrumental to the Air Force 30-year strategic goal of an agile and inclusive Force with courageous and resilient leadership during times of transformation. A strong Air Force will attract and retain top talent and keep that talent deployable by becoming a global leader in predictive personnel assessment.
American servicemen and servicewomen are assessed constantly, both before and throughout their service careers. All of these results get recorded — most of the time, manually, requiring re-entry and sometimes reformatting, adding unnecessarily to operational overhead (time and cost). The absence of a flexible but integrated digital collection interface means that opportunities for analytical insight are being squandered at both the point of performance, and at the level of strategic oversight. Orchestra mitigates this data dilemma.