With the recent conclusion of the wars in Iraq and Afghanistan, the Army is at an inflection point. Multiple efforts, led in part by Army Futures Command, look to modernize how we fight. Gen. James C. McConville highlights efforts in his Chief of Staff of the Army Papers, stating that the future fight will be multi-domain, fast-paced, and technology-driven. One of many key components to this transition will be how the sustainment community adapts to new technologies, challenges problem sets, and rapidly incorporates these concepts into our professional military education (PME). The general officers and command sergeants major of 2035 are currently in the pipeline and must have the ability to wield these critical concepts and capabilities that maximize the use of developing artificial intelligence platforms and other advanced data analytics to make rapid decisions on theater resource allocations in support of their geographic combatant commander. That training and understanding must begin now. While many of the technologies of 2035 are still in development, there is plenty that the sustainment community can focus on now to build a bedrock of understanding as we continue to transform and incorporate data-driven concepts into our training and doctrine.
Importance of Data
Data is only as good as the source. Currently, most of our data points are manually input by supply or maintenance clerks, copied and pasted from logistics status (LOGSTAT) reports, or based on historical estimates. We essentially are an analog logistics community, and this lowest echelon of data is the most critical. We rely upon our most junior leaders to serve as the quality control of information used to make countless decisions.
Lieutenants and sergeants are critical to minimizing manual data entry errors. Their understanding of the importance of clean and accurate data is a vital step in our transformation to an Army soon to be more data reliant than ever. Thus, sustainers at the platoon level will need to serve as filters, monitoring their Soldiers’ data collection and input. These platoon-level leaders will need to ensure systems and processes that result in sufficiently clean data gathered in LOGSTATS and the use of systems of record such as Global Combat Support System-Army (GCSS-A). This data will enable the cutting-edge data analytics technology of 2035 to make accurate predictions which will in turn aid in gaining an advantage in unified land operations over near-peer competitors in large-scale combat operations.
Leaders Are the Impact on Logistics
Artificial intelligence (AI) offers the prospect of analyzing trends and predicting needs faster and more accurately than the human element. AI promises to take over mundane tasks and free up humans to develop insights and drive decision-making. Predictive maintenance systems being fielded in new and emerging equipment aim to increase the quantity and quality of data in reporting. Implementing human-machine teaming decision-making structures in the commercial sector has shown significant increases in demand forecasting and inventory accuracy that Army logisticians need to be prepared to incorporate into daily planning and operations effectively.
We will need to go beyond the traditional construct of the stationary concept of supports and planning and learn to rapidly incorporate and adapt to growing changes on the battlefield in real-time. The data inputs will increase as we continue to modernize, but the first and last meter of logistics will remain a human element. From preventive maintenance checks and services, parts requisition, or input validation in LOGSTAT, the first meter will remain a human element: a Soldier inputting data into GCSS-A or the LOGSTAT. At the last meter, the human element is a leader reviewing a recommended decision generated with the power of AI and mediated with human intuition. We must start setting conditions for this process now.
Our combat training centers (CTC) could be key to rapidly transform how we get leaders to think about data and its incorporation into the decision-making process on a grander scale. The National Training Center (NTC) at Fort Irwin, California, is uniquely postured to collect, capture, and analyze multiple data sets in a short amount of time using the Training Analysis Feedback Facility. These dedicated sections within the operations group hold a vast repository of data. With deliberate guidance, they could adjust when and how they collect data in conjunction with the observer/controller on the ground with the rotational training unit.
Deliberate injects based on data collected during the force-on-force portion of the rotation can instill awareness, incorporating deliberate training during a unit’s leader training program, usually six months before the rotation, to get organizations thinking about the critical data points needed to make decisions at echelon. This would serve as a rudimentary introduction to the data handling requirements on the horizon.
Units at the NTC have historically been poor at reporting, resulting in poor situational awareness at higher echelons, leading to inaccurate synchronization matrix, poorly tailored logistical package convoys, and supported battalions culminating early due to lack of critical commodities. Deliberate after-action reviews that incorporate data-informed factors will force leaders at company, battalion, and brigade levels to increase their understanding of data usage and incorporate it into the formal planning process.
Importance of Commercial Data Analytics Education
With recent supply chain woes headlining in the media, civilian logistics professionals find themselves in the spotlight. Historical concepts focused on lean systems or “just in time” logistics are faltering, succumbing to a lack of supply chain resiliency and critical shortages in materials. The importance of trained supply chain professionals has rarely been more important.
As the Army finds itself in our next interwar period, we must look to maximize the lessons of our civilian counterparts and integrate applicable lessons into our PME. A select cohort of company grade and junior field grade officers currently attends the Virginia Commonwealth University’s Supply Chain Master’s Program each year. Additionally, three officers selected for the Army War College attend the Massachusetts Institute of Technology’s Center for Transportation and Logistics (MIT CTL) as a military fellow. This education provides insight into critical real-world applications to challenging problem sets and the tools to solve them. For example, at the Computational and Visual Education Lab at MIT CTL, students use interactive visualization to improve data visibility, data analysis, and decision making for supply chain and logistics challenges.
While these programs are exceptional, they are limited in size and scope. To prepare for the requirements of future systems and the data-heavy information they provide, sustainers must integrate this type of learning much earlier into their PME lifecycle. Understanding data cleansing concepts, different components of AI principles, and the means to analyze that data and provide recommendations for decisions to leaders is critical. Revamping PME at the entry level for officers and NCOs to fully immerse themselves into the capabilities of GCSS-A will more greatly enable their ability to take commercial concepts and put them into practice throughout their careers.
To be that general officer in 2035 who makes the right call with the advanced analytic tools of that time, lieutenants of today must build their skills now by learning how to build systems and processes within their platoons to ensure that clean data is being entered into reporting systems of record. Because clean data also is crucial for human-mediated logistics decision-making today, lieutenants who focus on skills to provide clean data to their high echelons (platoons to companies, companies to battalions) will also be improving the logistics agility of their organization today. However, as data analytics software advances, it will be crucial as these leaders rise through the ranks to have been data natives during their formative years.
Lieutenants will likely work with early predictive AI enablers in their senior company-grade and junior field grade years within support operations (SPO). This transition will need a full doctrine, organization, training, materiel, leadership, personnel, facilities, and policy relook, however in the near term, deliberately integrating training and conditioning opportunities at our CTCs and maximizing the use of civilian supply chain education can serve as an intermediary. By the time, the lieutenants of today are general officers leading sustainment organizations, AI enablers will likely be mature technologies. These lieutenants will benefit from spending decades working closely with data integrating it into decision-making processes. Preparing these leaders for the future starts now.
Col. William J. Parker III is currently attending the Massachusetts Institute of Technology’s Center for Transportation and Logistics as an Army War College Fellow. He commanded the 11th Armored Cavalry’s Regimental Support Squadron and most recently served as the Senior Sustainment Trainer at the National Training Center. He has a Bachelor of Arts in Communications from Wake Forest University, a Master of Arts from Webster University in Procurement and Acquisition Management, and a master’s degree in Military Art and Science in Operational Art and Sciences CGSC’s School of Advanced Military Studies.
Capt. Eli D. Rothblatt leads data analytics and visualization for the reallocation of more than 100,000 excess items for 1st Armored Division as the Division Sustainment Brigade’s Divestiture Officer. He has a bachelor's degree from Johns Hopkins University and a Juris Doctor degree from New York University School of Law.
This article was published in the Winter 2022 issue of Army Sustainment.