There is a current capability gap in providing leaders with accurate, timely sustainment knowledge to enable combatant commanders’ dominance in endurance, reach, and tempo. Achieving decision dominance with emerging technology is not about replicating legacy processes but reducing human error and extraneous interpretation between a commander and the operation. Sustainment commands must aggressively integrate new technology and enable super intelligence (SI)-driven command and control at corps headquarters, embracing the third offset at the operational level in the Army Reserve.
The Maven Smart Systems (MSS) from Palantir has gained traction across the Department of War (DOW), and recent experience has demonstrated deep adoption at the brigade through corps echelons within Component (COMPO) 1. As the tech stack evolves, we anticipate Palantir’s continued centrality. This provides strong motivation for the Army Reserve to invest in sustainment workflows that leverage MSS. Furthermore, Palantir is strengthening its position in the DOW through network effects as it continues to integrate within an ecosystem of both well-known solutions and emerging players.
As we move to a more connected battlefield under the Joint All-Domain Command and Control (JADC2) and Next Generation Command and Control (NGC2) frameworks, commanders have streamlined access to information and a shorter observe, orient, decide, and act loop. This requires staff and commanders who can confidently master the new technology. Drawing on several corps exercise iterations, this article presents a perspective on challenges facing sustainment staffs as they experience both organization and technological shifts while integrating across COMPO, echelons, and allied partnerships.
Modernization of Legacy Systems
The first approach to address the capability gap is to reconcile modernization initiatives with established legacy systems and processes. Despite access, exposure, and training to new technology, recent experience demonstrates that reserve expeditionary sustainment commands (ESCs) struggle to transition from traditional methods to intelligent tools such as MSS. Large-scale combat operations (LSCO) require dispersed command posts managing supply chain continuity across vast distances and complex dynamics. As the pace of warfare increases, sustainment commands must bridge the tactical-to-strategic level through the integration of new intelligent tools managed by lean command posts across the area of operations. This requires combining sustainment subject matter expertise and analytics savvy to create technically competent leaders who master and incorporate new platforms in the spirit of JADC2, NGC2, and data mesh architecture. As planners master these new technologies, the corps can expect increased sustainment command staff capability to manage the endurance and survivability of critical supply chains in a LSCO environment.
New low-code and SI-code assist tools create an opportunity to expediently develop internal technical talent in tactical units. The sustainment enterprise must develop and integrate data engineering and data analysis competencies into operational planning and execution. NATO and corps-level exercises are ideal opportunities to develop these competencies in tandem with COMPO 1 partners. Proof-of-concept experimentation must inform combat sustainment command (CSC) force structure and doctrine as it sits within its supported corps echelon.
Denied, degraded, intermittent, and limited environments are a persistent challenge and are a legitimate concern for sustainers. However, defense technology companies are aware of the threat and have designed robust modern software and hardware solutions that sustain capability even when cloud or edge computing is disrupted. The Sustainment Center of Excellence and force managers have also weighed this consideration in development of organizational structure and equipment packages.
Tactical Data Governance and Provenance
Effective integration of quality data is the backbone of creating enterprise systems reflective of the organization’s core processes that enable leader decisions. Legacy knowledge management doctrine is useful on many general topics, such as the focus on standards, disciplined staff operations, change management, system thinking, and its emphasis on people, processes, and tools. However, the doctrine falls short of addressing force modernization. As the data mesh framework becomes dominant, a federated system of builders will create knowledge locally on mesh-based ontologies. This locally created knowledge will be amplified and enhanced when exposed to broader ontologies and users outside the originating domain. Where legacy knowledge management focuses on a centralized standard and execution, modern data strategy focuses on governance and data products. The Air Force Data Strategy is an example of a modern approach toward data and knowledge management that recognizes that the trajectory toward decentralization is best managed by the expert implementation of first principles. This strategy recognizes that the mesh creates more data accessibility across geographies, functional areas, and echelons than a knowledge manager can effectively achieve. Operating at scale requires a baseline set of technical skills to permeate a sustainment command staff. Sustainment staff relying on legacy ad hoc tools do not sufficiently scale to a multi-division LSCO maneuver focused environments.
Army Techniques Publication 6-01.1, Knowledge Management, states that the Signal Corps is responsible for providing software developers. This perspective is out of step with recent developments in defense technology. Sustainment Soldiers with functional expertise can now build applications and data products. The doctrine also assigns the chief of staff as the senior knowledge management officer. While this chief framework is well suited for many military contexts that demand a single point of accountability, it is not suited for modern data management. When data originating locally is accessible at the enterprise as a product, automation is required to manage standards. Trust is achieved not through faith in a knowledge management officer in another organization, but through viewable lineages and automated pipelines, which ensure transparency and enforce governance principles.
A recent case study, “Dirty Data: Vantage is Not Enough” by CPT Gage Callahan et al., published on army.mil, demonstrates the low value of recorded vehicle utility data. The authors identify misaligned incentives as the root cause. Overtaxed Soldiers perceive no immediate benefit and fail to create quality data. This is a great example of legacy workflows lacking governance guardrails required to manage modern sustainment data products on scale. This insight draws an important connection between the technical and behavioral aspects of data and knowledge management.
The same frictions around data quality occurred in a recent large-scale multi-national exercise. A small cohort of officers created several workable applications hamstrung largely by dysfunctional integration with source systems. The poor integration caused debate over data governance that may prove useful in doctrine development. One side argued for an initial ingestion of sustainment data into Foundry software ontologies, with all subsequent changes occurring through ontology actions. The other side argued for periodic ingestion from the source system, with continuous overwrites of the ontology through the pipeline.
Through necessity, the group landed on the latter for two reasons. First, the source system did not allow write-back from Foundry. Second, the user interfaces were not sufficiently developed or rehearsed to allow for inputs from the consumer directly through the ontology. When the systems did not integrate and sustainment reporting was not standardized, consumers followed the local path of greatest familiarity. Numerous formats and pathways for sustainment data were developed at each echelon. Data lineages were practically untraceable, provenance was unvalidated, and reports lacked consistent definitions and formats. The result was reflexive non-data-backed decisions and untimely delivery of sustainment. The Palantir ontology framework, with its write-back capabilities, user-facing actions for ontology edits, and governance tools, arms sustainment managers with scalable capabilities absent from legacy models.
Workflow Management
An integrated data system within the sustainment command is only as good as how it integrates into the workflow of its customer organization. When a corps is configured from typically unaligned divisions, the emergent system defaults to incongruity and time-consuming standardization. Staffs spend cognitive effort decoding various reports and data structures for information in motion. A re-occurring scenario entails consumers submitting sustainment requests with SOPs on ad hoc forms and non-standard structures.
Observations at a corps exercise highlighted an unmanageable collage of locally tacit knowledge attempting to force expedite a semi-formal process. While the level of problem solving is impressive, the overall outcome is sub-optimal as sustainment staffs are overwhelmed solving the data problem, forcing a delay in the operational problem. This is compounded when intermittent attempts to reconcile manually managed data with a digital source system falls short, and the developing tactical situation outpaces the operational pace of the headquarters staff.
In tactical situations time has a premium. The corps can buy time by building and converging on ontology-based sustainment workflows before the tactical engagement. An exercise is a perfect time to resolve write-back file processes, and experiment with new workflows under stress. An ideal outcome of experimentation is an ontology-based source system that keeps pace with the speed of the fight. Reconciliation with enterprise systems can come later. This requires leadership engagement at all levels of product development. The product design must enable data creation at the company through division level, which feeds into the corps sustainment cycle.
Force management planners can support these efforts with personnel and resources mapped to these workflow requirements. A modern communications exercise (COMEX) may serve as the culminating mission rehearsal for sustainment data operations. This modern COMEX and emerging architecture are an opportunity to modernize the traditional operation order to accommodate data operations.
A key challenge is that a reserve CSC may not be permanently aligned with a corps. This raises the question of who spearheads and leads development of sustainment workflows, and product development. If the CSC leads development, there is a risk that the pipelines, reference data, and meta data will not transition well from one corps to another. Corps-led development risks the CSC not being equipped to manage the pipelines and workflows, degrading its initial support capability to the corps. Several potential solutions exist.
- Centralized Workflow Development: Sustainment workflows are built for battalion through corps echelons with approved variations at an enterprise level. CSC trains on maintaining workflows. Corps can expect seamless transition when operational integration occurs. Centralized solutions may not meet local commanders’ information needs or staff styles.
- Early Alignment: Corps and CSC are aligned six to 12 months in advance of the mission and co-develop and train on workflows. Ideal from a development standpoint but may be impractical to establish alignment with certainty so far in advance.
- Baseline Standards: Corps develop and document workflows within the scope of established standards. When alignment occurs within six months, the reserve ESC/CSC can onboard to these workflows relatively quickly, given knowledge of the standards and where the variations occur.
Regardless of the approach, there are two main takeaways. First, dispense with antiquated reporting formats and rhythms. In the next war, multiple sustainment commands simultaneously supporting multiple corps will do so with staff sizes far below the modified table of organization and equipment, and antiquated systems will quickly stress diminished staff to a breaking point. Second, treat sustainment information like its own planning activity. Data and reporting information moves through physical networks and cognitive layers from the point of consumption to a general officer-led target board. Lone engineers or analysts developing in a vacuum cannot be the norm. Data operations must be rehearsed in the same fashion as a combined arms rehearsal. It is critical for the commander to be personally invested and committed to test-fix-test through the exercise cadence to ensure the system adapts to the dynamic environment.
Measuring effectiveness
As ESC transitions to CSC, new mission essential task and performance measures are required regarding data workflow management at individual, supporting, and collective levels. However, the Army might consider introducing a layer of complexity to the training and evaluation outline to evaluate an organization’s ability to leverage technology to move up the cognitive hierarchy. This is similar to the maturity model used in legacy knowledge management doctrine. A visualization that shows the current state of sustainment might represent the lowest level. A visualization that incorporates analytics to project sustainment conditions might be intermediate level. An application that uses information generated by other warfighting functions to project sustainment conditions and generate analysis and decisions might be expert level. Articulating and assessing an organizations’ position on this trajectory will serve as a north star and maintain momentum. The Army may consider additional data and technology related dimensions to an officer evaluation.
While data governance must be integrated into planning, commanders must not neglect to monitor the growth of the technical experts executing data operations at scale. A small team of integrated data engineers can construct meaningful ontologies during the planning process leading to a mission with data analysts implementing MSS decision support templates. Reserve Soldiers, properly managed and trained, can achieve modest results with a five-month lead time, the equivalent of a 10-day Agile sprint adjusted for troop program unit availability. Strong commands will track data product development alongside other warfighting functions.
Conclusion
The successful establishment of capability requires both immediate and iterative changes to how data processes into knowledge internally in the sustainment command and how it interfaces to external partners. The new system must be informed by what is effective from legacy lessons but transformed to meet the realities of modern warfare.
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LTC Domenico C. Amodeo currently serves as the operations officer for the 55th Sustainment Brigade. Previously he commanded the 1185th Deployment and Distribution Support Battalion in Lancaster, Pennsylvania. His professional credentials include designation as an APICS Certified Supply Chain Professional, alongside technical certifications in Azure, artificial intelligence, and NVIDIA. His education includes a Ph.D. in systems engineering from George Washington University.
MAJ Rich Galila currently serves as the force development officer for the 310th Expeditionary Sustainment Command. He previously served as the S-4 of the 63rd Mission Command Support Group. His education includes a Master of Business Administration with a supply chain focus from Syracuse University.
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This article was published in the fall 2026 edition of Army Sustainment Professional Bulletin.
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