DoD's $90M R&D contract for ML models awarded to ECS Federal, LLC, with 999 task orders

Contract Overview

Contract Amount: $89,793,875 ($89.8M)

Contractor: ECS Federal, LLC

Awarding Agency: Department of Defense

Start Date: 2017-09-29

End Date: 2020-03-27

Contract Duration: 910 days

Daily Burn Rate: $98.7K/day

Competition Type: FULL AND OPEN COMPETITION

Number of Offers Received: 999

Pricing Type: COST PLUS FIXED FEE

Sector: R&D

Official Description: IGF::OT::IGF DEVELOPMENT, DESIGN, AND IMPLEMENTATION SERVICES FOR PROTOTYPE MACHINE LEARNING MODELS UNDER BROAD AGENGY ANNOUNCEMENT (BAA) SOLICITATION NUMBER W911NF-17-S-0003

Place of Performance

Location: FAIRFAX, FAIRFAX County, VIRGINIA, 22031

State: Virginia Government Spending

Plain-Language Summary

Department of Defense obligated $89.8 million to ECS FEDERAL, LLC for work described as: IGF::OT::IGF DEVELOPMENT, DESIGN, AND IMPLEMENTATION SERVICES FOR PROTOTYPE MACHINE LEARNING MODELS UNDER BROAD AGENGY ANNOUNCEMENT (BAA) SOLICITATION NUMBER W911NF-17-S-0003 Key points: 1. Contract awarded for prototype machine learning models, indicating investment in advanced AI capabilities. 2. The contract's duration of 910 days suggests a substantial development and testing phase. 3. Awarded under a Broad Agency Announcement (BAA), typically used for basic and applied research. 4. The definitive contract type implies a commitment to a specific scope of work. 5. The high number of task orders (999) suggests a flexible and adaptable approach to research needs. 6. The contract's value of approximately $90 million represents a significant investment in R&D.

Value Assessment

Rating: fair

The contract value of $89.8 million over 910 days for R&D services is difficult to benchmark without specific details on the deliverables and complexity of the machine learning models. However, the Cost Plus Fixed Fee (CPFF) pricing structure can sometimes lead to higher costs if not managed tightly, as the contractor is reimbursed for allowable costs plus a fixed fee. Comparing this to similar R&D contracts for AI/ML prototypes would require access to more granular data on scope and outcomes.

Cost Per Unit: N/A

Competition Analysis

Competition Level: full-and-open

The contract was awarded under a full and open competition, indicating that all eligible responsible sources were permitted to submit offers. This approach is generally favored for ensuring the best value is obtained through a competitive process. The specific number of bidders is not provided, but full and open competition suggests a robust market engagement.

Taxpayer Impact: A full and open competition is beneficial for taxpayers as it maximizes the potential for competitive pricing and encourages a wider range of innovative solutions, potentially leading to better value for the government.

Public Impact

The Department of Defense benefits from advancements in machine learning for potential applications in intelligence, surveillance, and reconnaissance. Services delivered include the design and implementation of prototype machine learning models. The geographic impact is primarily within the Department of Defense's research and development ecosystem. Workforce implications include the employment of researchers, data scientists, and engineers specializing in AI and machine learning.

Waste & Efficiency Indicators

Waste Risk Score: 50 / 10

Warning Flags

Potential for cost overruns with CPFF contract type if not closely monitored.
Complexity of R&D may lead to scope creep or unmet performance expectations.
Dependence on a single contractor for a significant R&D initiative.

Positive Signals

Awarded through full and open competition, suggesting a competitive process.
Focus on advanced technologies like machine learning aligns with modernization goals.
The use of a BAA is appropriate for exploratory and developmental research.

Sector Analysis

This contract falls within the Research and Development sector, specifically focusing on physical, engineering, and life sciences (excluding biotechnology). The market for AI and machine learning R&D is rapidly growing, with significant government investment driven by national security and technological advancement priorities. Comparable spending benchmarks would involve other DoD contracts for advanced technology prototypes and AI research initiatives.

Small Business Impact

The contract data indicates that small business participation (ss: false, sb: false) was not a primary set-aside consideration for this specific award. While the prime contractor is ECS Federal, LLC, the absence of explicit small business set-aside or subcontracting goals in the provided data suggests that opportunities for small businesses may be limited unless they are part of the supply chain or subcontracted by the prime. Further analysis would be needed to determine if subcontracting plans were in place.

Oversight & Accountability

Oversight for this contract would typically be managed by the Defense Contract Management Agency (DCMA), which is responsible for ensuring contractor performance and compliance. The definitive contract structure and the presence of numerous task orders imply ongoing monitoring of deliverables and expenditures. Transparency is facilitated through contract awards databases, but detailed programmatic oversight information is often internal to the agency.

Related Government Programs

Department of Defense Research and Development Programs
Artificial Intelligence and Machine Learning Initiatives
Broad Agency Announcements (BAA) Solicitations
Prototype Development Contracts

Risk Flags

Cost Plus Fixed Fee contract type can lead to higher costs if not managed effectively.
Research and Development projects inherently carry technical and schedule risks.
Limited information on specific deliverables and performance metrics makes value assessment challenging.

Frequently Asked Questions

What is this federal contract paying for?

Department of Defense awarded $89.8 million to ECS FEDERAL, LLC. IGF::OT::IGF DEVELOPMENT, DESIGN, AND IMPLEMENTATION SERVICES FOR PROTOTYPE MACHINE LEARNING MODELS UNDER BROAD AGENGY ANNOUNCEMENT (BAA) SOLICITATION NUMBER W911NF-17-S-0003

Who is the contractor on this award?

The obligated recipient is ECS FEDERAL, LLC.

Which agency awarded this contract?

Awarding agency: Department of Defense (Defense Contract Management Agency).

What is the total obligated amount?

The obligated amount is $89.8 million.

What is the period of performance?

Start: 2017-09-29. End: 2020-03-27.

What is the track record of ECS Federal, LLC in delivering similar R&D projects for the Department of Defense?

ECS Federal, LLC has a history of performing various IT and R&D services for the Department of Defense and other federal agencies. While specific details on past machine learning prototype projects are not immediately available from this data alone, their portfolio often includes complex technical solutions. A deeper dive into their contract history, past performance evaluations, and specific project outcomes would be necessary to fully assess their track record in delivering advanced AI/ML prototypes. This would involve reviewing contract databases for awards, task orders, and any associated performance metrics or CPARS reports to understand their success rate and capabilities in this specialized R&D area.

How does the value of this contract compare to other DoD investments in AI/ML R&D?

The $89.8 million awarded to ECS Federal, LLC for prototype machine learning models is a significant investment, but its relative scale within the broader DoD AI/ML R&D landscape requires context. The DoD has allocated billions of dollars towards artificial intelligence research and development across various initiatives and programs, including those managed by DARPA, AFRL, and ONR. This contract, awarded under a BAA, likely represents a specific research effort. To compare effectively, one would need to aggregate spending across similar BAA solicitations, specific AI/ML research programs, and other contracts focused on developing foundational AI capabilities or specific applications. The total DoD AI budget and the distribution of funds across different research areas would provide a clearer picture of where this $90 million contract fits.

What are the primary risks associated with this R&D contract, and how are they being mitigated?

Key risks for this R&D contract include technical feasibility (developing effective ML models), scope creep (expanding research beyond initial objectives), schedule delays (protracted development cycles), and potential cost overruns, especially given the Cost Plus Fixed Fee (CPFF) structure. Mitigation strategies would typically involve rigorous project management, clear definition of milestones and deliverables, regular technical reviews, and close financial oversight by the contracting agency (DCMA). The use of a BAA allows for flexibility, but this also necessitates strong governance to keep the research focused. The contractor's expertise and past performance are also critical risk mitigation factors.

How effective is the Broad Agency Announcement (BAA) solicitation mechanism for procuring advanced R&D like this?

The Broad Agency Announcement (BAA) mechanism is generally considered highly effective for procuring advanced, exploratory, and basic research where the specific outcomes are not fully defined at the outset. It allows agencies to solicit innovative proposals from a wide range of sources, fostering competition and encouraging cutting-edge solutions. For R&D in fields like machine learning, where the technology is rapidly evolving, the BAA's flexibility is crucial. It enables the government to tap into the latest scientific advancements and adapt research directions as new discoveries emerge. The process typically involves a two-step approach: initial proposals followed by specific solicitations for promising concepts, ensuring that funding is directed towards high-potential research.

What is the historical spending pattern for R&D contracts under BAA W911NF-17-S-0003?

The provided data pertains to a single contract awarded under BAA W911NF-17-S-0003. To analyze historical spending patterns for this specific BAA, one would need to access contract award databases to identify all contracts issued against it. This would involve looking for other awards, their values, durations, contractors, and task order counts. Without access to that broader dataset, it's impossible to determine trends, average contract values, or the typical number of awards made under this solicitation. The $89.8 million contract with ECS Federal represents one data point, and a comprehensive analysis would require examining all associated awards to identify patterns in spending, research areas funded, and contractor participation.

Industry Classification

NAICS: Professional, Scientific, and Technical Services › Scientific Research and Development Services › Research and Development in the Physical, Engineering, and Life Sciences (except Biotechnology)

Product/Service Code: RESEARCH AND DEVELOPMENT › DEFENSE (OTHER) R&D

Competition & Pricing

Extent Competed: FULL AND OPEN COMPETITION

Solicitation Procedures: BASIC RESEARCH

Solicitation ID: W911NF17S0003

Offers Received: 999

Pricing Type: COST PLUS FIXED FEE (U)

Evaluated Preference: NONE

Contractor Details

Address: 2750 PROSPERITY AVE STE 600, FAIRFAX, VA, 22031

Business Categories: Category Business, Not Designated a Small Business, Partnership or Limited Liability Partnership, Special Designations, U.S.-Owned Business

Financial Breakdown

Contract Ceiling: $94,431,921

Exercised Options: $89,974,455

Current Obligation: $89,793,875

Contract Characteristics

Commercial Item: COMMERCIAL PRODUCTS/SERVICES PROCEDURES NOT USED

Cost or Pricing Data: YES

Timeline