Comment from Persistence Analytics Group LLC

Comment on FTA-2026-0200 State of Good Repair Program Persistence Analytics Group LLC / United Grid submits this comment regarding FTA’s information collection for the State of Good Repair Program. PAG / United Grid supports the purpose of the State of Good Repair Program: helping public transportation systems finance capital projects to maintain, replace, and rehabilitate critical transit assets, including rolling stock, track, equipment, structures, signals, communications, stations, maintenance facilities, and related Transit Asset Management planning. State of Good Repair is not only an asset-condition issue. It is an infrastructure-assumption integrity issue. The value of this information collection should be judged by whether it helps FTA, transit agencies, Congress, riders, taxpayers, and local governments understand whether the assumptions behind public transit capital investment are holding over time. FTA should ensure the information collection supports the following: 1. Useful-life verification Transit agencies should be able to show whether actual asset performance is consistent with the useful-life assumptions used in capital planning, grant applications, and replacement schedules. 2. Deferred maintenance visibility The collection should help distinguish ordinary condition deterioration from deferred maintenance that may create larger future safety, service, or public-cost exposure. 3. Investment-priority evidence State of Good Repair funding should be tied to evidence of asset condition, service criticality, safety risk, lifecycle cost, rider impact, and consequences of delay. 4. TAM plan accountability Because State of Good Repair funding must align with Transit Asset Management plans, FTA should ensure those plans are not merely compliance documents. They should reflect real asset risk, realistic replacement timing, and evidence-based investment priorities. 5. Post-investment verification FTA should encourage recipients to compare projected outcomes with actual results after capital investment. Did replacement or rehabilitation improve reliability, reduce maintenance burden, improve safety, extend useful life, or prevent service disruption as expected? 6. Service-risk transparency Condition data should be connected to rider-facing consequences, including delays, outages, service reductions, safety risk, accessibility impacts, and reliability failures. 7. Public-cost exposure Weak assumptions about asset condition, useful life, replacement cost, or maintenance needs can shift costs to future riders, taxpayers, state governments, and local agencies. The collection should help identify where those risks are accumulating. 8. Burden and practical utility FTA should minimize unnecessary reporting burden, but not at the expense of decision quality. The information collected should be useful for funding decisions, oversight, lifecycle accountability, and public transparency. PAG / United Grid recommends that FTA strengthen the practical utility of this collection by ensuring State of Good Repair reporting can answer these questions: * What asset is at risk? * What useful life is being assumed? * What evidence supports that assumption? * What happens if the asset fails earlier than expected? * What service or safety consequence follows? * What public cost hardens if replacement or rehabilitation is delayed? * What post-investment evidence confirms the funding produced the intended outcome? The broader principle is simple: State of Good Repair should not mean reported condition alone. It should mean decision-grade evidence that transit assets, maintenance plans, funding priorities, and service obligations can hold over time. Public transportation depends on long-lived assets and long-term public commitments. Weak asset assumptions can lead to deferred maintenance, service disruption, safety risk, stranded capital, and higher future taxpayer exposure. FTA should continue this information collection, but should use it to strengthen assumption verification, lifecycle accountability, and post-investment performance review. Respectfully submitted, Neil P. Osnato Founder Persistence Analytics Group LLC | United Grid National Security & Infrastructure Risk Analytics Demand Durability | Grid Stress | Load Integrity SAM.gov registered UEI: D3VYU39H6DX9 D-U-N-S: 142849930 CAGE: 19T34 neil@persistenceanalyticsgroup.com 609-464-9055 https://persistenceanalyticsgroup.com/