Workforce Modeling at the Defense Contract Management Agency Provides Useful Estimates and Can Be Improved

Workforce modeling conducted by the Defense Contract Management Agency (DCMA) provides estimates that can reliably inform staffing and budget decisions, according to a 2025 assessment by RAND researchers. But, as with any modeling effort, it is a work in progress. Continued development to expand the accuracy and capabilities of the models and communicate to stakeholders how the models work and are used should be a priority for future workforce modeling efforts.

DCMA’s Work and Workforce

DCMA is the U.S. Department of War’s (DOW’s) lead organization for contract oversight, administration, and support, from pre-award through closeout.^[1] In executing its contract management mission, DCMA plays three mutually reinforcing roles:

• First, the agency supports DOW warfighter lethality and readiness by enabling the timely delivery of supplies that span the full spectrum of military capabilities. For fiscal year (FY) 2024, DCMA supervised the manufacture and delivery of nearly 400 aircraft, approximately 6,100 combat vehicles, and close to 339,100 missiles and rockets—in addition to more than 300 million items shipped.
• Second, DCMA provides financial oversight for contract execution and delivery, ensuring effective stewardship and efficient use of taxpayer dollars. For FY 2024, the total value of DCMA-overseen items delivered was reportedly $81.4 billion.
• Third, DCMA is uniquely positioned to provide insight into the operation of the defense industrial base for national decisionmakers, providing perspectives “from balance sheet to factory floor,” as DCMA has stated.

Although mission work, funded directly by congressional appropriation, is DCMA’s priority, the agency also provides services on a reimbursable basis to non-DOW agencies (such as NASA) and other DOW functions, such as the foreign military sales program administered by the Defense Security Cooperation Agency. As of March 26, 2025, DCMA reported nearly 10,000 civilian employees—about 1,400 of whom supported reimbursable workload—and slightly more than 500 military personnel located at nearly 900 DCMA locations and serving approximately 17,750 contractor locations worldwide. Approximately 85 percent of personnel are part of DOW’s acquisition workforce and occupy positions coded as such. As of March 26, 2025, DCMA personnel were managing approximately 300,000 active contracts, with a total contract value of approximately $5.9 trillion, and processing $1 billion in contractor payments on an average business day.

The Workforce Models, in Brief

Workforce analysis allows organizations to compare workforce demand with workforce supply and assess whether they have the right number of people. Workload modeling techniques help organizations estimate their manpower requirements or demand.

In fulfillment of its roles, DCMA has been modeling its manpower and workload with growing sophistication over the past ten years, leveraging functional Resource Workload Models (RWMs) to introduce an Integrated Resource Workload Model (IRWM) that captures the agency-wide workload. The models, which are grounded in best practices for manpower analysis and use quality data from authoritative sources, represent a solid foundation for conducting workforce analysis.

These models translate information about DCMA’s workload into an estimate of the required workforce based on the current process of conducting work (see Figure 1). The models are embedded in a dynamic modeling ecosystem influenced by internal factors (e.g., policies and procedures guiding workload acceptance) and external factors (e.g., laws and regulations, policies, resources) that change over time and influence both workload and how the work is performed.

The process of modeling workload and the standards by which it is performed provides increasingly more accurate and more actionable information to support budget requests, manpower allocations, and workload acceptance and assignment decisions.

Results of RAND’s Assessment

In 2024, the Office of the Under Secretary of War (Comptroller) directed DCMA to commission an independent assessment of DCMA’s total workforce. This comprehensive assessment, undertaken by RAND, examined DCMA’s manpower requirements for core functions and the process by which requirement estimates are generated to identify efficiencies and help DCMA optimize workforce management.

RAND’s validation of the accuracy and usefulness of version 2.0 of the IRWM ecosystem models focused on two key questions:

1. Is DCMA accepting the highest-priority mission work, given current funding and staffing levels?
2. Is DCMA doing work efficiently and to the appropriate standard of performance?

The assessment—which examined inputs, assumptions, and outputs of the IRWM ecosystem and the accuracy, relevance, and practical utility of the models—was based on reviews of DCMA artifacts and publicly available information, as well as semistructured interviews with more than 225 DCMA subject-matter experts to learn about the structure, operations, and functions of the IRWM ecosystem.

The research team found that the IRWM is a comprehensive and serious modeling effort. The functional RWMs are the centerpiece of the IRWM and focus on DCMA’s core operational output-oriented functions. IRWM version 2.0 generated a workforce estimate of about 12,795 personnel for FY 2024. Workload associated with 77 percent of these positions was formally modeled or accounted for through the functional RWMs.

DCMA tracks not only its functional workload but also the workload associated with the remaining 23 percent of positions, which are supervisory or general administrative in nature, including the 9.7 percent of positions related to headquarters functions and enabling components. Those estimates are derived from current operating practices and are below estimates from comparable industries. An analysis of data from the U.S. Bureau of Labor Statistics suggests that approximately 40 percent of employees working in a comparable industry are classified as performing overhead or administrative activities.

DCMA iteratively improves RWMs and the IRWM over time to address shortfalls. At the same time, interviewed stakeholders shared their views about the limitations of the model’s development and use. Considering these assessment findings, the research team arrived at three principal conclusions.

The IRWM and its component RWMs have short-term and longer-term benefits. The IRWM generates a solid point-in-time estimate of the number of DCMA personnel required to support a given contract management workload for the enterprise as a whole and for key workforce segments. The estimates are useful for planning and organizational decisionmaking. But the benefits of the IRWM go well beyond its ability to generate an estimate of workforce requirements at any point in time based on existing internal and external factors. The modeling effort surfaces insights and prompts conversations, choices, and decisions that drive changes to workload distribution, DCMA policy and standard operating procedures, and organizational structures that have the potential to enhance efficiency and process improvement. Insights derived from the modeling effort can influence external factors, such as memorandums of agreement with customers. Another value of the IRWM is that it provides a road map to help DCMA understand the implications of changes to key factors for its workforce needs—changes to budget and authorized personnel levels, statute and regulations, DOW policy and missions, and customer demands.

Although it is continuously working to improve its modeling effort, DCMA lacks a clear structure for prioritizing model improvement efforts. The model does not aim to achieve universal predictive accuracy with its estimates, but there may be circumstances in which enhanced accuracy is desired. Improvements to model accuracy require additional personnel and budget beyond what is allocated to maintain the status quo. Existing staffing levels dedicated to this effort in DCMA headquarters are insufficient to maintain routine model validation and maintenance while incorporating adjustments to keep pace with significant changes in DCMA’s external and internal operating conditions. Formal documentation and standard operating procedures are not as robust as would be useful to those using the model. In the face of heightened demands and constrained staffing, it is important to have a rigorous framework for prioritizing and sequencing the work that can be accomplished based on a deliberate cost-benefit analysis. A repeatable, institutionalized process will ensure that model maintenance and improvement efforts continue at the speed and quality required for DCMA operations.

Enhanced communication could improve transparency, trust, and accuracy. Internal and external communication about the model effort, its assumptions, and the analytical capabilities it facilitates have not been prioritized in the face of resource constraints. The lack of effective communication, particularly between the DCMA headquarters modeling team and functional model experts in the field, has created some degree of confusion and compromised trust. Moreover, existing feedback mechanisms are largely reliant on personal relationships and are insufficient to ensure collaboration among stakeholders throughout the IRWM ecosystem. Finally, better communication about model inputs and how they are used could help standardize the use of systems of record at the field level, driving better accuracy.

Next Steps for DCMA

No model is a perfect representation of what is being modeled. However, continued improvement and expanded use of the models in the IRWM ecosystem will enable more–data-driven decisionmaking within DCMA, improve collaboration between headquarters and field elements, and help focus resources devoted to model and system enhancements where they can be the most beneficial. Toward those ends, the research team recommends two broad directions for DCMA. The first is to focus on the model itself, making improvements in documentation, in the procedures for and prioritization of further model development, and in communicating model enhancements and the use of model outputs to the organization’s stakeholders. The second is to capitalize on the investment DCMA has made in the IRWM by leveraging it more widely to support decisionmaking.

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