ONHS Report: SP4701-26-B-0004

Defense Logistics Information Research (DLIR) BAA

Solicitation ID: SP4701-26-B-0004

Agency: DLA/Research and Development (R&D) Program Office

Type: Combined Synopsis/Solicitation

Deadline: 2031-09-16T17:00:00 ET

Eligibility: Maybe (Unspecified)

Funding: Ceiling of $50 Million over five (5) years

Doc Type: BAA/IDIQ

Clearance: CUI

Program Manager: Latoya.Monroe@dla.mil

Last Updated: 2026-09-18 16:03

Analyzed File: DLIR_BAA_2026_FINAL.pdf

Eligibility Reasoning

Eligibility for a DLIR contract requires prospective offerors to meet the minimum standards of responsibility set forth in Part 9 of the Federal Acquisition Regulation (FAR).

Note: This is an AI-generated summary...

Summary

The Defense Logistics Agency (DLA) seeks innovative Research and Development (R&D) proposals through the Defense Logistics Information Research (DLIR) Broad Agency Announcement (BAA) SP4701-26-B-0004. This is a five-year initiative with a $50 million ceiling, open until September 16, 2031, aiming to strengthen industrial base resilience, improve readiness, and transition DLA to Industry 4.0/5.0 standards. The process starts with an 8-page white paper; if interest is shown, a full technical and cost proposal will be requested for potential award of cost-type IDIQ or definitive contracts. Key technical areas of interest are: 1) Industrial Base Resilience, Surge, and Manufacturing Capability; 2) Public-Private Partnerships for Surge and Sustainment; 3) Circular Economy and Resource Recovery; and 4) Digital Twin of the Organization (DTO) for Enterprise Transformation. All proposals must include a detailed transition plan for operational use within DLA. Evaluation criteria focus on technical feasibility, viability, desirability, and past performance, alongside a cost realism analysis.

Overall Technical Areas

Industrial Base ResilienceAI-Enabled Manufacturing CapacitySupplier Capability MappingAutomated Source QualificationAdvanced ManufacturingPublic-Private Partnership FrameworksSecure Technical Data ExchangeStandardized Data FormatsCircular Economy CapabilitiesAI-Driven Material IdentificationAutomated Material ClassificationDigital Twin Organization (DTO)Mission Process ModelingPredictive AnalyticsHuman-Machine Teaming

Probable LBNL Areas

BSACSAEESAESAETAOperations

Focus Areas

Example Priorities:

Research shall enhance the ability of the national industrial base to meet surge demand and address hard-to-source, and low-volume and high-mix items.
Solutions may include AI-enabled latent manufacturing capacity, supplier capability mapping, automated source qualification, and advanced manufacturing approaches that enable rapid production and alternate sourcing pathways.
Efforts shall integrate capabilities across the Defense Industrial Base (DIB), Organic Industrial Base (OIB), and non-traditional manufacturing sources to expand capacity, reduce acquisition lead time, and improve readiness.

Specific Technical Skills:

Artificial IntelligenceSupply Chain ManagementAdvanced ManufacturingSupplier Capability MappingAutomated Source QualificationIndustrial Base AnalysisSurge Capacity ModelingLogistics ReadinessAcquisition Lead Time Reduction

Potential PIs for this Area:

Name	Score	Organization
Thomas Hendrickson	0.74	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Industrial Base Analysis
Alex Newkirk	0.73	ETA \| Building Tech. & Urban Sys. \| Bldg & Industrial App Dpt · Acquisition Lead Time Reduction
Minok Park	0.72	ETA \| ESDR \| Energy Storage & Dist Dpt · Advanced Manufacturing
Nica Campbell	0.72	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Supplier Capability Mapping
Unique Karki	0.72	ETA \| Building Tech. & Urban Sys. \| Bldg & Industrial App Dpt · Advanced Manufacturing
Anna Giannakou	0.72	CSA \| SciData \| Data Science Applications · Artificial Intelligence
Sam Murthy	0.71	ETA \| Energy Analysis \| Energy Markets & Planning · Surge Capacity Modeling
Satyarth Praveen	0.71	CSA \| SciData \| Data Science Applications · Artificial Intelligence
Cristian Poliziani	0.71	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Logistics Readiness
Koushik Sen	0.70	CSA \| AMCR \| Computer Science · Automated Source Qualification

Example Priorities:

Research shall develop and operationalize public-private partnership (PPP) frameworks to enable rapid activation of commercial manufacturing capability and capacity in support of surge and hard-to-procure requirements.
Efforts may include pre-approved contract templates that speed up manufacturer onboarding, secure ways to share technical drawings and specifications with private-sector partners, faster vendor vetting and registration...
...and standardized data formats so Government and industry systems can exchange information without manual conversion.

Specific Technical Skills:

Public-Private PartnershipsContract ManagementSecure Data ExchangeVendor ManagementData StandardizationIntellectual Property ProtectionDoD LogisticsSupply Chain IntegrationContingency Operations

Potential PIs for this Area:

Name	Score	Organization
Abdelilah Essiari	0.74	CSA \| SciData \| Data Science Applications · Secure Data Exchange
Valerie Skye	0.72	BSA \| DOE Joint Genome Institute \| Data Science & Informatics · Data Standardization
Sean Peisert	0.72	CSA \| SciData \| Data Science Applications · Secure Data Exchange
Laura Crosby	0.71	Operations \| Office of the Chief Finance Officer (OCFO) \| Procurement · Contract Management
Michael Mahoney	0.71	CSA \| SciData \| Data Science Research · Data Standardization
Thomas Hendrickson	0.71	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Supply Chain Integration
Steven Hofmeyr	0.71	CSA \| AMCR \| Computer Science · Intellectual Property Protection
Alex Newkirk	0.70	ETA \| Building Tech. & Urban Sys. \| Bldg & Industrial App Dpt · DoD Logistics
Sean Murphy	0.69	ETA \| Energy Analysis \| Energy Markets & Planning · Public-Private Partnerships
Sunhee Baik	0.69	ETA \| Energy Analysis \| Energy Markets & Planning · Contingency Operations

Example Priorities:

Research shall advance circular economy capabilities to improve recovery, reuse, repurposing, and recycling of materials across the DLA enterprise with the goal of generating revenue from recovered assets and lowering the overall cost of recovery operations.
Efforts may include AI-driven material identification, automated classification and valuation, and digital platforms that support reclamation, recovery, and resupply processes.
Solutions should enhance material traceability, reduce reliance on foreign sources for critical materials, enable the reuse of recovered materials as feedstock for advanced manufacturing and sustainment operations...

Specific Technical Skills:

Circular EconomyAI-Driven Material IdentificationAutomated ClassificationMaterials ScienceResource RecoveryDigital PlatformsMaterial TraceabilityAsset ValuationSustainment Operations

Potential PIs for this Area:

Name	Score	Organization
Francesco Ricci	0.75	ESA \| MSD \| Material Physics · Materials Science
Kristin Persson	0.75	ESA \| MSD \| Material Physics · Material Traceability
Kevin Cruse	0.75	ESA \| MSD \| Material Physics · AI-Driven Material Identification
Alexander Hexemer	0.75	ESA \| ALS \| PS Computing staff · AI-Driven Material Identification
Margaret Busse	0.74	EESA \| EG \| Geochemistry Dept · Resource Recovery
Nihan Karali	0.73	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Circular Economy
Nawa Raj Baral	0.72	BSA \| Biological Systems & Engineering \| Process Engr & Analytics · Resource Recovery
Alex Newkirk	0.72	ETA \| Building Tech. & Urban Sys. \| Bldg & Industrial App Dpt · Digital Platforms
Nica Campbell	0.71	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Sustainment Operations
Talita Perciano Costa Leite	0.71	CSA \| SciData \| Data Science Research · Automated Classification

Example Priorities:

Research shall advance Digital Twin of the Organization (DTO) and mission process modeling solutions that enhance DLA’s digital modernization by simulating the complex interactions among people, processes, systems, and policies.
Extending beyond existing process-mining capabilities, proposed efforts must leverage artificial intelligence, machine learning, predictive analytics, and synthetic data to enable dynamic scenario evaluation, resilience analysis, and real-time decision support for enterprise and supply chain operations.
Crucially, these technical models - which must account for human behavior and organizational dependencies—must be paired with robust workforce readiness, change management, and strategic communication frameworks...

Specific Technical Skills:

Digital Twin TechnologyMission Process ModelingPredictive AnalyticsMachine LearningSynthetic Data GenerationEnterprise SimulationResilience AnalysisReal-Time Decision SupportHuman-Centered DesignChange Management

Potential PIs for this Area:

Name	Score	Organization
Thomas Hendrickson	0.73	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Resilience Analysis
Talita Perciano Costa Leite	0.73	CSA \| SciData \| Data Science Research · Machine Learning
Michael Mahoney	0.73	CSA \| SciData \| Data Science Research · Predictive Analytics
Satyarth Praveen	0.73	CSA \| SciData \| Data Science Applications · Synthetic Data Generation
Hannah Cohoon	0.72	CSA \| SciData \| Data Science Applications · Human-Centered Design
Anna Giannakou	0.72	CSA \| SciData \| Data Science Applications · Real-Time Decision Support
Samuel Fernandes	0.71	ETA \| Building Tech. & Urban Sys. \| Whole Building Sys Dept · Digital Twin Technology
Alexander Sim	0.70	CSA \| SciData \| Data Science Research · Enterprise Simulation
Heidi Fuchs	0.70	ETA \| Building Tech. & Urban Sys. \| Bldg & Industrial App Dpt · Change Management
Gregory Lemieux	0.69	EESA \| CESD \| Earth System Sciences · Mission Process Modeling

Potential LBNL PIs (Overall)

Note on PI Matching: These suggestions are generated through an AI-driven semantic analysis of LBNL staff profiles.

Name	Score	Organization
Thomas Hendrickson	0.78	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Industrial Base Resilience
Kevin Cruse	0.77	ESA \| MSD \| Material Physics · AI-Driven Material Identification
Tanny Andrea Chavez Esparza	0.75	ESA \| ALS \| PS Computing staff · Predictive Analytics
Galina Ovchinnikova	0.75	BSA \| DOE Joint Genome Institute \| JGI Science Dept · Standardized Data Formats
Minok Park	0.75	ETA \| ESDR \| Energy Storage & Dist Dpt · Advanced Manufacturing
Seth Carbon	0.74	BSA \| Env. Genomics & Sys. Biology \| BioSystems Data Science · Automated Source Qualification
Prakash Rao	0.74	ETA \| Building Tech. & Urban Sys. \| Bldg & Industrial App Dpt · AI-Enabled Manufacturing Capacity
Nihan Karali	0.74	ETA \| Energy Analysis \| Systems & Energy Tech Analysis · Circular Economy Capabilities
Jeetika Malik	0.74	ETA \| Building Tech. & Urban Sys. \| Bldg Technologies Dept · Human-Machine Teaming
Abdelilah Essiari	0.74	CSA \| SciData \| Data Science Applications · Secure Technical Data Exchange

Fundamental Research Exemption (FRE)

Critical technology means— (1) Defense articles or defense services included on the United States Munitions List set forth in the International Traffic in Arms Regulations under subchapter M of chapter I of title 22, Code of Federal Regulations; (2) Items included on the Commerce Control List set forth in Supplement No. 1 to part 774 of the Export Administration Regulations under subchapter C of chapter VII of title 15, Code of Federal Regulations, and controlled— (i) Pursuant to multilateral regimes, including for reasons relating to national security, chemical and biological weapons proliferation, nuclear nonproliferation, or missile technology; or (ii) For reasons relating to regional stability or surreptitious listening; (3) Specially designed and prepared nuclear equipment, parts and components, materials, software, and technology covered by part 810 of title 10, Code of Federal Regulations (relating to assistance to foreign atomic energy activities); (4) Nuclear facilities, equipment, and material covered by part 110 of title 10, Code of Federal Regulations (relating to export and import of nuclear equipment and material); (5) Select agents and toxins covered by part 331 of title 7, Code of Federal Regulations, part 121 of title 9 of such Code, or part 73 of title 42 of such Code; or (6) Emerging and foundational technologies controlled pursuant to section 1758 of the Export Control Reform Act of 2018 (50 U.S.C. 4817).