Why Permitting Is a Data Problem

Every permit application touches multiple agencies. A wind energy project in Montana might require sign-off from the Bureau of Land Management, the state Department of Environmental Quality, the county planning office, and the local utility district — each running its own process, its own forms, and its own timeline.

The result is a process that’s slow not because the underlying regulations are unreasonable, but because the data infrastructure behind them was never designed to interoperate. Applicants resubmit the same information six times. Reviewers manually search for precedent decisions that already exist somewhere in a filing cabinet or a siloed database. Agencies duplicate effort because there’s no shared view of what’s been reviewed, what’s been approved, and what’s still pending.

This is a data problem.

The silo problem

Permitting data lives in fragments. Federal environmental reviews are spread across dozens of agency systems, many of which still rely on document formats that predate modern data processing. State agencies maintain their own databases, often built on legacy platforms that were never intended to expose data externally. County and municipal records are frequently paper-based or stored in scanned PDFs on minimally maintained local servers.

When a reviewer needs to reference a past decision — a comparable environmental assessment, a prior approval for a similar project type, a precedent from an adjacent jurisdiction — they’re searching manually across systems that don’t share a common language. This isn’t a workflow problem. No amount of process improvement fixes a missing data layer.

What interoperability actually requires

Building permitting systems that work across jurisdictions requires solving three infrastructure problems before anything else.

The first is standardization. Documents and records from different agencies need to share enough common structure that they can be compared, combined, and queried. That means consistent metadata — jurisdiction level, agency, document type, project category, effective date, geographic scope. Without that foundation, you can’t build reliable search, and you can’t build anything meaningful downstream.

The second is currency. Regulations change. A permitting corpus that was accurate six months ago may now contain superseded rules, amended ordinances, or updated agency guidance. Any system built on static data degrades over time. The infrastructure has to include update pipelines — mechanisms for ingesting new documents, flagging changed content, and propagating updates to dependent records.

The third is hierarchy. Federal rules set a floor. State rules add requirements on top. County and municipal rules layer further still. A query about permitting requirements for a specific project type in a specific location needs to understand that hierarchy — not just retrieve documents that match keywords, but surface the right level of authority for the question being asked.

Why this is worth solving now

The federal government is actively trying to accelerate permitting for critical infrastructure — energy transmission, broadband, water systems, transportation. The bottleneck in nearly every case is the review process, and the review process is slow because the underlying data infrastructure doesn’t support it.

Several national laboratories and federal agencies are already building pieces of this foundation. The opportunity for state and local governments is to connect to that foundation rather than rebuild it — to adopt shared data standards, contribute their own regulatory corpus to an interoperable system, and gain access to a review process that’s informed by decades of comparable decisions rather than starting from scratch each time.

The technology to do this exists. The challenge is integration, governance, and the organizational will to treat permitting data as shared infrastructure rather than agency-specific records.

That’s the problem worth building for.