ARMY AL&T
I
n medicine, there is a saying that “time is tissue.” What this means is that when a Soldier falls sick or injured on the battlefield, speed is often a critical factor as to whether they survive and return to the fight. A key part of enabling health care at the speed of war is
predicting what units will need, and then getting the right equipment and supplies in the right place at the right time—without grossly over- estimating or underestimating. Overestimations are unsustainable and wasteful. Underestimations leave units fatally shorthanded.
TeArmy Medical Logistics Command (AMLC), the Army’s life cycle management command for medical materiel, is using data to help leaders plan for the complexity and lethality of large-scale combat operations, predicting what will be needed to sustain critical medical support to warfighters while also reducing resource waste.
DATA SCIENTISTS Tere is a new breed of warriors that have become critical to Army modernization: data scientists. Tese specialists of facts and figures have joined the ranks of most parts of the Army, including AMLC’s Integrated Logistics Support Center, which introduced the 1560 Data Science job series into the organization in 2022. AMLC’s data scien- tists provide analysis and analytics services to AMLC’s organization, which includes teams of medical logisticians and maintainers at more than 25 sites worldwide.
Under the direction of the Integrated Logistics Support Center’s Logis- tics and Technical Support Directorate, they are aligning medical logistics with the whole-of-Army approach to use predictive logistics to deliver precision sustainment—reliable, agile and responsive sustainment capabilities that enhance materiel readiness, lower inventory consistent with the need to reduce demand, and reduce costs.
Predictive logistics refers to the Army’s ability to harness the power of data to forecast units’ needs, and then synchronize production and distribution at every echelon.
It’s not fortune telling. It’s science.
Data analytics provide leaders with real-time situational awareness of their current and future logistics readiness. From this common operat- ing picture, they can predict logistical needs before the demand signal. For example, a demand signal could be a notification from a unit plac- ing an order for more medications. However, the wait for the demand signal could mean the unit may be without critical resources for a period of time. Tis timing is critical in a contested, denied or disconnected environment where supplies may not be readily accessible or replenished.
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