Battlefield Algorithm

Leveraging Predictive Analytics in Contested Environments

By SGM Noel DeJesus

Article published on: December 1, 2024 in the Army Sustainment Winter 2025 Issue

Read Time: < 8 mins

As the Army prepares for large-scale combat operations (LSCO), the importance of effective logistics has never been greater. In contested environments, where supply chains are vulnerable to disruption, the military must find new ways to ensure critical resources reach the front lines. One key solution is adopting corporate predictive analytics practices. Corporations have long used predictive analytics to anticipate market trends and optimize their supply chains, allowing them to remain competitive in ever-changing environments. The military can benefit from these same practices to enhance logistical efficiency, making predictive analytics a critical tool for success on tomorrow’s battlefields.

This article examines how the military can adopt corporate predictive analytics to overcome logistical challenges in contested environments. By understanding how corporate models work and applying them to military logistics, forces can enhance operational readiness and sustainment in the face of adversarial threats. This adaptation is crucial when preparing for LSCO in a global environment that is interconnected.

Predictive Analytics

Corporate sectors leverage predictive analytics to improve customer loyalty, forecast demand fluctuations, and optimize supply chains. By analyzing historical data, businesses can anticipate customer needs and adjust their operations accordingly, thereby reducing operational costs. This enables companies to remain competitive even when market conditions fluctuate unexpectedly. Similarly, military logisticians can use predictive analytics to forecast future requirements based on data from past missions, environmental conditions, and resource consumption. In contested environments, where logistics face disruptions from enemy actions or challenging terrain, predictive analytics provide military planners with the foresight needed to mitigate these risks. This strategic advantage of predictive analytics, especially in regions like the Indo-Pacific, provides an added layer of readiness. By anticipating disruptions, logistics teams can adjust supply lines preemptively, ensuring the timely delivery of essential supplies such as ammunition, fuel, and medical equipment.

Enhancing Decision Making

The military’s adoption of corporate predictive models hinges on its ability to harness vast amounts of data, similar to how corporations predict market trends and optimize their operations. In military logistics, real-time data from drones, sensors, and satellite imagery can be combined with historical data to anticipate supply chain disruptions. This data fusion allows military planners to develop robust contingency plans and respond swiftly to dynamic battlefield conditions.

Predictive analytics improves the military decision-making process (MDMP) by modeling potential outcomes based on current data. In contested environments, these models enable military planners to identify alternative routes or suggest optimal supply drops to ensure essential resources reach their destinations. This agility in the planning and execution phases is critical for maintaining operational readiness in volatile settings. The ability to predict and plan ensures that military forces are always one step ahead of potential challenges.

The use of predictive analytics to create customized simulations offers data-driven insights into future risks and opportunities. In the corporate world, these tools help businesses forecast market trends and adjust strategies accordingly. This adaptability ensures that companies can not only adapt but thrive amid changing market conditions.

Similarly, military logistics planners can use artificial intelligence (AI) and machine learning (ML) algorithms to simulate various logistical scenarios and prepare for potential challenges, improving the MDMP at both the strategic and tactical levels. These algorithms can process vast amounts of data from past missions, environmental conditions, and resource consumption to predict future requirements and plan supply routes. In contested logistics environments, predictive analytics allows military planners to allocate resources more effectively and develop real-time contingency plans. This data-driven approach reduces uncertainty and enhances the military’s ability to respond swiftly to battlefield conditions. In LSCO, where anti-access/area denial (A2/AD) capabilities present logistical challenges, predictive analytics becomes a critical enabler of operational success.

Joint training exercises and multinational cooperation are also critical to ensuring the efciency of RSOI processes.

Leveraging AI and Predictive Logistics in LSCO

In LSCO, logistics often face continuous threats from adversaries. AI and ML algorithms have emerged as powerful tools for transforming sustainment operations by enabling predictive logistics.

These technologies aggregate and analyze vast amounts of battlefield data to forecast supply needs and optimize supply chains in real time. The proactive nature of these AI driven models, which can anticipate maintenance needs, ensure proactive repairs and minimizes downtime, making their users feel prepared and in control of potential challenges.

This proactive approach helps keep critical equipment operational. Additionally, systems powered by AI, such as drones and autonomous vehicles, enable the transportation of supplies through contested areas without risking personnel. These systems can operate in high threat environments and provide the military with operational flexibility, allowing for the rapid and safe transportation of supplies.

Strategic Sustainment and Prepositioned Stock

Prepositioned stock plays a key role in the military’s ability to sustain operations in contested environments, particularly in theaters like the Indo-Pacific, where near-peer threats such as China pose significant logistical challenges. Prepositioned stock enables the rapid deployment of critical resources, enhancing operational reach and providing a buffer against adversarial disruptions. The Army’s prepositioned stock afloat ensures that critical combat equipment and supplies are available for rapid deployment, even in contested environments.

Strategic sustainment organizations such as Army Materiel Command and the Defense Logistics Agency are essential to maintaining prepositioned stock and ensuring timely transport to where it is needed most. These organizations coordinate complex supply chains, ensuring that resources are positioned for maximum effectiveness. They play a crucial role in managing and distributing prepositioned stock. Additionally, operational contract support (OCS) integrates civilian contractors into military logistics, ensuring that essential sustainment operations continue even in high threat environments. This integration increases the military’s logistical resilience in contested zones.

Overcoming A2/AD Challenges

A2/AD environments present significant logistical challenges, because adversaries use long-range precision weapons, electronic warfare, and cyber-attacks to disrupt supply lines. Combined with AI, predictive analytics allows military planners to adjust operations in real time, rerouting supplies and mitigating disruptions. The integration of AI with predictive analytics adds a layer of responsiveness that is essential in modern warfare. Prepositioned stock further supports rapid deployment and sustainment under A2/AD conditions, particularly in areas like the Indo-Pacific. By using prepositioned stock and predictive analytics, the U.S. military can ensure its ability to project power and sustain operations, even when supply chains are constantly threatened. For example, the Army’s Sagami General Depot in Japan holds critical medical supplies and equipment ready for rapid deployment. These logistical hubs are essential in sustaining forces in hostile environments.

Enhancing RSOI Processes with AI and OCS

Reception, staging, onward movement, and integration (RSOI) processes are essential to deploying forces in contested environments. AI-driven systems can optimize these processes by integrating logistics data from various platforms, providing a comprehensive picture that enhances decision making and resource allocation. This integrated approach allows logistics planners to be proactive rather than reactive in contested environments. OCS further supplements these efforts by integrating civilian resources into the logistics framework. This ensures that military forces remain flexible and responsive, even when traditional supply routes are compromised. Joint training exercises and multinational cooperation are also critical to ensuring the efficiency of RSOI processes. Allied forces must work together to overcome logistical and language barriers, fostering trust and improving the efficiency of joint operations. This collaboration enhances the military’s ability to sustain operations in contested environments.

Conclusion

As the nature of warfare evolves, so too must military logistics. Predictive analytics and autonomous systems powered by AI and ML provide the tools needed to maintain operational agility, improve decision making, and sustain forces in contested environments. By integrating established and proven corporate strategies and technologies into military logistics operations, the U.S. military can overcome the logistical challenges posed by LSCO and A2/ AD threats. The time to act is now. Embracing these innovations will ensure that the military remains ready and resilient, and capable of sustaining operations in even the most contested environments. The ability to predict and adapt will define the future of military logistics, and therefore the future of military logistics will define the outcome of future wars.