In today’s complex and rapidly changing operational environment, Army sustainment efforts must continue adapting at speed and scale to deliver ready combat power to the joint force on a multidomain battlefield. The Army sustainment enterprise is initiating and expanding capabilities to leverage data analytics and advanced technologies to accomplish this. Data-driven sustainment operations are not only the way of the future; it is how the Army must operate today to enhance its ability to anticipate and address logistics needs efficiently across the spectrum of conflict to sustain an expeditionary global force.
As one of six objectives Secretary of the Army Christine Wormuth shared in her message to the force on Feb. 8, 2022, the intent is “to ensure the Army becomes more data-centric and can conduct operations in contested environments, which will enable our ability to prevail on the future battlefield.” By harnessing the power of data analytics, the Army can synthesize vast amounts of information to gain valuable insights, identify trends, and predict future requirements — at the speed of combat. It must employ predictive logistics for executing precision sustainment capabilities worldwide, allowing for greater control, visibility, and efficiency.
Predictive logistics requires the leveraging of historical data, advanced analytics, and machine learning algorithms to accurately forecast demand for supplies, equipment, and maintenance needs and to optimize transportation and distribution networks. By integrating data from various sources, such as equipment usage, maintenance records, deployment schedules, and weather patterns, sustainers can make informed decisions, proactively identify and address potential supply chain disruptions, allocate resources accordingly, and mitigate risks. This approach helps avoid costly delays, minimize downtime, and maximize operational capabilities. From anticipating demand and optimizing inventory management to improving current and future maintenance practices, predictive logistics ensures troops receive the necessary parts, supplies, and equipment in time when and where needed.
Predictive sustainment at the tactical level enables precision logistics at the operational and strategic levels, enabling leaders to make better-informed decisions and improve overall readiness. But data is only as good as the ability to collect, analyze, and understand how to action it. To fully exploit the power of data-driven sustainment, we must invest in the necessary infrastructure, technology, and training for Soldiers and, where possible, integrate with partners and allies. This requires a collective effort from all stakeholders, including Army leadership, the acquisition community, industry partners, joint and multinational partners, and Soldiers on the ground. We must develop robust data collection systems and ensure interoperability and sharing across different systems and platforms. Additionally, we must prioritize the development of data analytics capabilities and provide comprehensive training to personnel, equipping them with the skills and knowledge necessary to analyze and interpret data effectively.
Data-enabled decisions will decide future battles. The right data at the right time and at the right place enables faster and better decisions at echelon and allows for out-thinking and out-pacing any adversary. The Army is aligning itself as a data-centric organization, and so must its sustainment formations and leaders.
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Gen. Charles R. Hamilton currently serves as the commanding general of Army Materiel Command. In February 1988, he graduated from Officer Candidate School as a Distinguished Military Graduate and was commissioned as a second lieutenant in the Quartermaster Corps. He earned a master’s degree in public administration from Central Michigan University and a master’s degree in military studies from Marine Corps University. He also graduated from a Senior Service College Fellowship — Secretary of Defense Corporate Fellows Program.
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This article is published in the Fall 2023 issue of Army Sustainment.
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