OPNAV N80 INDUSTRY DAY PROBLEM STATEMENTS.pdf

LOE Name: Planning: N80

Problem Statement Title: Planning Document Generation and Scorecards

Description: OPNAV needs to routinely evaluate the importance of programs that are funded, and receives input for issues that need to be funded, and seeks a system that provides the ability to do an end-to-end evaluation. We require a solution that helps the organization review funded programs; take inputs for issues; ensure the input is correct and complete; add details about the programs issues the prioritization and risk; perform analysis understand the impacts of changes; track the reason for the changes; and output to the formats needed for presentation and upload to next level data bases.

OPNAV is looking for a solution that can automate and streamline our Programming process using AI where applicable to:

- Pull information from online databases for programmed funding, execution, requirements, Total Ownership cost, IOC/FOC, Congressional actions and other details and combine it; allow users to see the full information about programs; and for that information to be combined into higher level groups or decomposed into more detailed programs; allow generation of Powerpoint / word / excel summaries of the programs at any level selected

- Take inputs for new issues that will be added from Program Offices/PAE/others with an automated validation of data

- Allow option for information from previous POM cycles to be used as a source of new issues

- Combine new issues with existing program data or when needed generate a new program

- Perform automated validation and error checking of the combined data with the ability to see underlying information

- Provide option to review current issues and/or programs and summarize total ownership cost, execution data, future requirements, and any other useful information collected

- Allow ability to see program-level information over the life cycle to include program status during acquisition, current and projected sustainment cost, projected requirement and current funding level

- Allow view / edit / update of issue data from process owners and stakeholders

- Display and store recommended changes to Program information that can be compared or passed to other data sources for update

- Allow addition of weights / values /prioritization to programs and issues

- Allow information for program and issue funding or details and weights/values/prioritization to be imported from databases uploads, or individually prepared datasheets

- Provide an advanced analytical tool that models funding scenarios, calculates the impact of changes, and helps decision-makers evaluate options

- Track decisions made and reasons for those decisions

- Display results with option to output into excel / word / Powerpoint for discussion and presentation

- Provide option to format output so that it can be ingested into database such as PBIS/RCP

The process could be accomplished with different modules but a solution including AI that could automate the end-to end process is needed

Data / Access

- Assumption: Solution needs to operate on US Navy NMCI system (NIPR and SIPR)

- Data being processed is a combination of classified and unclassified;

classified prioritization and attributes could be added for issue evaluation and then once decisions are made, removed to continue processing in an unclass environment

- Data is a combination of structured and unstructured

- Some data resides in online databases and needs to be combined with proposed issues. Ideal solution will be able to pull and combine information from data sources like PBIS, ERP, RDAIS (information could be available in ADVANA, Jupiter or foundry) with automated error checking

- Solution needs to be able to import from online databases or individually prepared data sheets

- Solution should combine inputs into larger data set

- Data will need to be validated after it is combined or compiled, with notification of errors and option to see underlying input data

- Throughout the process, provide ability to export to Excel, PowerPoint or word, with option to format output so that it can be ingested into other databases

- Limitation: Ensure data sharing is structured to support multi-level security domain requirements.

Constraints / Guardrails

- Solution will need to support many users at different levels of the Navy (Program Office, PAE, Fleet, OPNAV)

- Solution will need to be able to show information across different POM cycles

- Solution will need to be fast enough to provide updates in seconds/real time

- Solution will need access controls for which groups of users can see certain information and who can make changes

- Solution should fit within existing process to maximum extent possible and not require re-engineering of processes

- Solution will need to operate on Navy NIPRNET and SIPRNET (NMCI)

LOE Name: Planning: N80

Problem Statement Title: Strategic Planning and Scorecards

Description: OPNAV needs to integrate guidance from higher level organizations understand what is common, different and how it changed from previous years; create unique nested guidance for the Navy; create scorecards to track compliance with guidance; and grade decisions against that guidance.

OPNAV is looking for a solution that can use AI where applicable to:

- Import and analyze guidance from different organizations over different years to highlight, display and understand the overlaps, differences and trends

- Pull information from online databases for programmed funding, execution, requirements, Total Ownership cost and other details and combine it; allow users to see the full information about programs;

allow the information to be combined into higher level groups or decomposed into more detailed programs; then allow generation of Powerpoint / word / excel summaries at any level selected

- Use automation to fill in how the programs fit into different guidance and change in prioritization

- Provide option to visualize how existing funded programs add up within categories specified in guidance and provide option to output information to excel or powerpoint

- Use automation to generate new draft guidance for the Navy given key inputs for what is important to leadership that nests within higher level guidance

- Use automation to develop draft scorecards that can track compliance with current guidance at CNO level and other levels

- Ingest potential issues, tracking what programs they align to, which ones are funded or not funded, and generate automated scorecards of how well the Navy recommended actions comply with guidance and how much of the guidance has been met

- Use automation to summarize how existing funded programs combined with issues would change how well the Navy meets guidance

- Provide option to generate list of programming actions that would be more compliant with guidance

- Provide option to compare past decisions with actual execution, program delays or Congressional action to see how a previous assessment would change

The process could be accomplished with different modules but a solution including AI that could automate the end-to end process is needed

Data / Access

- Assumption: Solution needs to operate on US Navy NMCI system (NIPR and SIPR)

- Data being processed is a combination of classified and unclassified information

- Data is a combination of structured and unstructured

- Guidance Data is generally word or PDF

- Program Data can be imported from programming system, or may need to be assembled from different databases including PBIS, ADVANA, Jupiter or other systems

- Data will need to be validated after it is combined or compiled, with notification of errors and option to see underlying input data

- Solution needs to be able to combine inputs into larger data sets or decompose into more detailed descriptions

- Provide ability to export to excel, powerpoint or word

Constraints / Guardrails

- Solution will need to be able to show information for multiple organizations across multiple years

- Solution should fit within existing process to maximum extent possible and not require re-engineering of processes

- Solution will need to operate on Navy NIPRNET and SIPRNET (NMCI)

LOE Name: N81 Model and Simulation Improvements

Problem Statement Title: STORM Agent to Assist in Troubleshoot and Diagnose Issues

Description: Synthetic Theater Operations Research Model (STORM) is a campaign modeling and simulation tool used to support the Department of War and OPNAV N81 The current manual iteration cycle creates workflow bottlenecks during model setup and testing. Success will be measured by a reduction in the time analysts spend on parameter tuning and a faster turnaround time for producing daily STORM input files and weekly dashboard reports. Measurable improvements include a significant increase in first-pass model execution accuracy and a reduction in debugging timelines.

Data and Access Considerations Data availability and access present significant complexities. Data ranges from unstructured or semi-structured STORM input text files and C2 logic code to structured MySQL outputs hosted on local Linux servers. Access is heavily restricted; the STORM source code is ITAR-restricted, meaning any system housing it requires stringent security measures to safeguard it. Furthermore, analysts frequently have to access and evaluate the source code directly to troubleshoot failures, and must also discern whether unexpected data output is due to model behavior or recurring failures in the SQL data load process.

Constraints and Guardrails The solution must operate within secure, closed-network environments up to the Secret classification level. Consequently, any tool, integration, or AI model introduced must meet stringent Authority to Operate (ATO) requirements.

Operational adjustments must seamlessly integrate into the existing disconnected analytic toolchains.

LOE Name: N81 Assessments

Problem Statement Title: AI-Powered Knowledge Management to Enable the Analytic Master Plan Digital Platform (AMP-DP)

Description: The Navy relies on legacy databases and disconnected SharePoint sites to manage analytical work, hindering the goals of the Analytic Master Plan (AMP). Past studies and reports are siloed across network drives that require exact keyword matches, making information discovery inefficient.

Consequently, analysts waste time manually searching for data. This lack of discoverability leads to redundant analysis, wasted resources on repeat studies, and delayed decision-making from OPNAV down to the Fleet.

Data and Access Considerations The solution requires ingesting a library of existing documents from several decades, plus hundreds of new reports produced annually. This includes unstructured file types like PDFs and PowerPoints from across the naval enterprise. A key dependency is establishing a process for commands to upload these documents via a summarization, metadata generation and approval workflow. Currently, data availability is hampered by manual processes, creating access limitations for analysts.

Constraints and Guardrails The system must operate within security and policy boundaries, handling information from unclassified up to SECRET. It must implement role-based access controls to ensure users only see information they are cleared to view, while respecting data ownership by commands. The tool must also follow established information management rules, like the AMP instruction.

Operationally, the system must be fast and reliable enough to support thousands of personnel across the Navy, handling thousands of queries per month.

Desired Outcomes and Measurable Improvements Success is defined by the ability for Navy staff to leverage the results of all studies executed by the Navy through a secure, centralized interface.

Measurable success includes:

Speed: Reducing the time to answer complex analytical questions.

Decision Quality: Enabling leaders to identify redundant work before funding new studies.

Trust: Providing automated summaries that are verifiable via source linking.

Readiness: Empowering every Action Officer to produce higher-quality work based on the Navy's collective knowledge.

LOE Name: N81 Assessments

Problem Statement Title: AI-Powered Knowledge Management for N81 Analytic Continuity

Description: The N81 division produces analytic products that are vital for senior Navy leadership, but the process is manual, inefficient, and heavily reliant on institutional knowledge. Analysts spend a significant amount of time manually searching through historical studies, assessments, and white papers stored in SharePoint Online. This process is hampered by a lack of semantic search capabilities and inconsistent tagging, leading to duplicated efforts and a loss of analytic continuity when personnel turn over. The current workflow involves manual data extraction from multiple sources, re-creating presentations, and a cumbersome process for tracking the lineage of studies, all of which contribute to high user frustration and a high potential for error. The goal is to implement an AI/ML Large Language Model (LLM) indigenous to the SharePoint Online ecosystem to serve as a research assistant. The desired outcome is a fully in-tenant AI capability that operates natively inside SharePoint Online and connects to document libraries across N81, NAMP, NASP, and OSD CAPE. This will enable semantic search, summarization, and cross-study linkage, which will reduce duplication across the analytic ecosystem, enhance turnover and corporate knowledge retention, and support analysts with drafting, synthesis, and data-driven recommendations.

Success will be measured by a reduction in the man-hours spent on manual data extraction and historical research (e.g., a 50-hour-per-week manual effort could be significantly automated), faster generation of analytic products, and improved quality of data-driven recommendations to leadership.

Data and Access:

Data is available in both classified (up to SECRET) and unclassified formats and is a mix of structured and unstructured data from sources such as the NAMP and NASP portals, the OPNAV Assessments Archive in SharePoint, DRRS-N, PBIS/PBIS-IT, and various modeling and intelligence systems. Access is often manual, involving exports and copy/paste methods, and is hindered by classification barriers and the fact that document libraries on SharePoint Online are siloed across different organizations.

Constraints and Guardrails:

Any proposed solution must operate within the existing O365 IL5/IL6 environments and adhere to strict security and policy constraints. Data must remain inside these environments, and the use of external APIs is often not permitted. The capability must function within existing security enclaves and be subject to strict audit and identity controls. Additionally, document libraries are siloed across OPNAV, OSD, and the Services, which prevents cross-organizational discovery.

LOE Name: N83 Readiness (N831 – Automation)

Problem Statement Title: Ship Maintenance Model (SMM) – Reserve Capacity Calculation & DLI Adjustment

Description: The current method for calculating Reserve Capacity man-days and the Direct Labor Index (DLI) adjustment relies on a manual, error-prone process using Excel. Analysts must manually copy, paste, and enter data between systems, and then validate large datasets to find and correct systemic errors, such as miscategorized costs and data gaps The current manual process necessitates extensive data validation to ensure the accuracy of analytical outputs. The desired outcome is an automated system that validates data quality at the point of ingest, minimizing manual data cleaning and ensuring highly accurate, timely reporting for leadership.

The desired outcome is an automated system where data quality is validated at the point of ingest. The system would use AI/ML models to proactively flag anomalies and potential errors, allowing analysts to "manage by exception" instead of inspecting every record. The calculation of Reserve Capacity and DLI Adjustment would be fully automated, leading to more accurate and timely reporting and freeing up analysts to focus on strategic work.

Data / Access

- Data availability: The data involved includes financial cost data, operational metrics (e.g., maintenance schedules, workload, Ship sheet, CNO and Non-CNO Phasing), and associated metadata.

- Access limitations or assumptions: The source systems that generate the initial data are outside the team's direct control, so any solution must work with the data as it is received.

- Policy, legal, or operational boundaries: The solution is constrained by the limitations of the existing Ship Maintenance Model (SMM) capability and the inability to alter the source data systems.

LOE Name: N83 Readiness (N832 – Automation)

Problem Statement Title: Flying Hour Cost Reports (FHCRs) development and validation

Description: The end-to-end production of the Flying Hour Cost Report (FHCR) is a monolithic process. Many of the stakeholder's upstream and associated processes are also manual, compounding the operational friction. The workflow involves manual data extraction, spreadsheet-based analysis, and the manual creation of PowerPoint slides for executive briefings The current workflow involves sequential data extraction and analysis, which extends the timeline from the close of an execution month to final report generation. The process also relies heavily on specialized personnel. The desired outcome is an automated, end-to-end workflow that accelerates report generation time, improves the timeliness of insights, and broadens the system's usability across the team.

The desired outcome is a fully automated, end-to-end workflow. In this system, data would be ingested via APIs, processed automatically, and fed into a dynamic Business Intelligence (BI) dashboard. This would create a "live" report that is always up-to-date, allowing for the automatic generation of executive summaries. This would dramatically reduce report generation time, improve the timeliness and quality of insights, and reduce reliance on manual processes and specific individuals.

Data / Access

- Data availability: The data involved includes Cost, Flying Hours, and AIMD Overhead.

- Access limitations or assumptions: Data resides in disconnected systems that lack existing integrations or APIs.

- Policy, legal, or operational boundaries: The final output must be in a format suitable for executive-level briefings, which has historically been PowerPoint.

LOE Name: N83 Readiness (N83i – Automation)

Problem Statement Title: Developing Master Data File (MDF), Readiness LOE, Readiness Requirement Report

Description: The current process to generate the Master Data File (MDF) and related readiness reports is inefficient and heavily manual. It begins with "heavy follow-up" via email and phone to get stakeholders to submit data. This data often arrives in inconsistent formats and is frequently incomplete, which necessitates a lengthy cycle of manual re-formatting and additional follow-up.

This lack of standardization introduces errors during data consolidation, creates significant delays at the start of the reporting cycle, and diverts skilled analyst time to low-value administrative tasks.

The desired outcome is a centralized, web-based intake portal where stakeholders can submit data through standardized forms. The system would automate reminders and track submission status, ensuring all data is complete and correctly formatted upon arrival. This would eliminate manual data chasing, reduce errors, accelerate the reporting cycle, and allow analysts to focus on high-value analysis rather than administrative coordination.

Data / Access

- Data availability: The process relies on feeder data from multiple programmatic and operational stakeholders (e.g., fleet-provided data, programmatic requirements, fuel rates).

- Access limitations or assumptions: The primary challenge is not access itself, but the inconsistent format and incompleteness of the data provided by external sources.

- Policy, legal, or operational boundaries: Data providers are external stakeholders with their own processes. Their behavior cannot be dictated without providing them with improved tools and a more efficient submission process.

LOE Name: N83 Readiness (N834 Expeditionary - Automation)

Problem Statement Title: Model Maintenance Factor Validation Tool

Description: Develop an automated means to create and or validate maintenance factor variables used by the Expeditionary Costing Model. The process to annually calculate or validate equipment maintenance factors is currently a manual, spreadsheet-based process that can take 3-4 months to complete. It involves manual analysis of multiple years of maintenance cost data for hundreds of items fielded to the fleet from tactical vehicles and heavy construction equipment to underwater robotic systems. This workload consumes significant time, is not easily repeatable nor are the results easily validated.

The annual process is also highly dependent on specific personnel who have competing priorities in support of real-world missions.

The desired outcome is a fully automated, end-to-end workflow. In this tool, historical cost and authorized allowance data would be defined, formatted and sourced from multiple systems (maintenance, inventory, and authorized requirements data bases). Historically, MFs have been calculated using subjective subject matter expertise coupled with an engineering-based formula: (1/Frequency Touched)×Frequency of Use×Likelihood of Repair×Overhaul Cost. Development of alternate methods are necessary but outputs must work with the existing N834 cost model (The tool will need to be able to align and bin fielded equipment by commodity type and identify the corresponding Table of Allowance section number so that a single maintenance factor can be assessed and applied to each section within the N834 model). This would dramatically reduce analysis time, improve the timeliness and quality of insights, and reduce reliance on manual processes.

Data / Access

- Data availability: The data involved includes financial / maintenance cost data, inventory data and TOA requirements data sourced from third-party maintained systems.

- Access limitations or assumptions: Data currently resides in disconnected systems that lack existing integrations or APIs. Much of the data is being brought into WDP/Jupiter.

format suitable for upload into the model.

LOE Name: N83 Readiness (N834 Expeditionary - Automation)

Problem Statement Title: Model SYSCOM Programmatic Requirements

Description: Develop a process to model programmatic requirements for Navy SYSCOMs supporting procurement and sustainment of solutions fielded to the Expeditionary forces. The process to annually assess each SYSCOM and relevant program office within is currently a manual Level of Effort (LOE). The requirements for each program office have significant variation based on program size, portfolio size, sustainment needs, equipment complexity and the services provided to operational forces.

The desired outcome is a documented process to assess requirements at the individual program office level that can then be incorporated into the existing N834 cost model. The process must be based on available data and provide a means to apply variables to consistently assess the annual projected costs to support a program.

Data / Access

- Data availability: The data involved includes historical LOE-assessed data, financial / maintenance cost data, inventory data and TOA requirements data sourced from third-party maintained systems.

- Access limitations or assumptions: Data currently resides in disconnected systems that lack existing integrations or APIs. Some of the data is being brought into WDP/Jupiter.

format suitable for implementation into the model.

LOE Name: Congressional Correspondence: Questions / Inserts for the Record (QFR/IFR)

Problem Statement Title: QFR/IFR Response Support Tool

Description: The QFR / IFR process occurs every year in conjunction with congressional hearings. The process is managed in the ETMS2 tasker control system. There are several challenges that impede the process.

- Proper routing of QFRs/IFRs to the correct Office(s) of Primary Responsibility and Office(s) of Coordinating Responsibility (OCR).

This often results in lost time to research and compose the responses, as well as “orphan” responses that are never addressed because the QFR/IFR is completed with a “No Equity” response and the tasker is closed out without an actual response.

- Alignment with current strategic guidance. While the details of the responses may change, it is important that the narratives align with current strategic guidance, some of which changes on an annual basis, and some of which change significantly when the administration changes over.

- Alignment with historical responses. Some QFRs/IFRs “repeat” from year to year and like above, while the details may change, it is important that responses are “traceable” to previous iterations.

- Timing. QFRs/IFRs are often forwarded with very compressed timeframes for response, adding to the difficulty of vetting, coordinating, and completing in a timely manner. A significant share of the time consumed in composing responses is researching the strategic guidance, specific budgetary details, and alignment with overall Navy strategy for the budget, leaving little time to derive the specific details needed to answer the question at hand.

Desired outcomes:

- A fully automated and complete answer to the QFR/IFR, ready for leadership approval

- Instant and correct routing of QFRs/IFRs to the appropriate OPR/OCR

- Automated generation of initial responses that align with strategic guidance, current directives, and historical responses. These “pre-populated” drafts can be used by the OPR/OCR to get started, alleviate some of the time burden, and generate time to gather the specific details that will result in a comprehensive response to the

QFR/IFR.

- All responses align across the OPNAV and Secretariat staffs.

LOE Name: Congressional Correspondence: Program Briefs

Problem Statement Title: Automated Program Brief Support Tool

Description: In conjunction with the submission of the Navy’s President Budget proposal, congressional staffers request Program Briefs for specific topics. These topics are assigned across the OPNAV and Secretariat staffs. The format for the program briefs generally contains the same information but does change/evolve from year to year based on requirements from Congress, internal recommendations, changes in policy, the content of the budget request, and multiple other factors.

Desired outcomes:

- A pre-populated Program Brief that adheres to the current format, includes appropriate budgetary information, and is ready for editing by the appropriate staff entity.

- For “repeat” briefs, the ability to pull information from previous years and produce a “companion” supplement that summarizes changes and highlights from previous year submissions.

- A summary of specific congressional member concerns, tailored to the content and purpose of the program brief in question.

- All briefs are integrated across the OPNAV and Secretariat staffs and align with all current guidance.

LOE Name: Congressional Correspondence: Other RFIs

Problem Statement Title: Congressional Correspondence Tool

Description: In addition to the prescribed congressional products that occur in conjunction with the President’s Budget, congressional members query the Navy with individual requests for information throughout the year. A tool that can ingest these questions and generate a draft answer will save time and will complement existing products.

Desired outcomes:

- A draft answer formatted properly IAW official correspondence guidelines, ready for signature or review/editing as appropriate.

- Action memos and “chop chains” are generated and assigned.

- Draft responses are aligned with previously submitted responses and tailored to the interests of the specific member of Congress.

- Products comply with current strategic guidance and are updated to account for guidance that has been canceled or superseded.