The Hidden Cost of Going It Alone: Why GIS Needs Data Governance Across Departments

Geographic Information Systems (GIS) have become the backbone of modern organizations — helping departments map infrastructure, manage assets, and make data-driven decisions. But too often, the power of GIS is limited not by technology, but by people and process. One of the most common and costly challenges organizations face is operating GIS without a data governance agreement that defines authoritative layers, schemas, standards of service, and responsibilities between departments.

Without clear governance, even the best GIS platform can become a patchwork of disconnected datasets, conflicting priorities, and uncertain accountability.

1. The Challenge of “Multiple Versions of the Truth”

When every department maintains its own GIS layers without coordination, it’s only a matter of time before inconsistencies emerge.

The Planning Department’s parcel layer may not align with the one used by Public Works for utility management.

Emergency Services may update address points independently, unaware that another group is managing the same data for 911 response.

Departments might even disagree on what dataset is authoritative — meaning which one should be trusted as the official source.

The result? Confusion, duplication, and mistrust. Decision-makers begin to question the validity of the data itself. Projects slow down as staff scramble to reconcile discrepancies or verify information that should have been standardized from the outset.

2. Schema Drift and Compatibility Issues

Without agreed-upon schemas (the data structure or model that defines how features are named, coded, and related), GIS databases can quickly diverge from one another.

One team might name a field “Parcel_ID,” while another uses “ParcelNumber.”

One layer might store acreage as a floating-point number, while another stores it as text.

These minor differences add up to big integration headaches. Automated scripts fail. Analytical models break. And what should be a seamless exchange of information across systems becomes a manual, error-prone process.

Governance doesn’t just mean having the same data — it means having data that works together.

3. Lack of Service Standards and Performance Expectations

When there’s no governance agreement, each department may have its own understanding of service levels:

How frequently should data be updated

Who is responsible for QA/QC

How requests for new data or edits should be prioritized

What response times users should expect from GIS support teams

The absence of standards of service creates friction and unmet expectations. Departments relying on GIS for time-sensitive operations, such as permitting, emergency management, or field inspections, can find themselves working with outdated or incomplete data.

A governance agreement clarifies these expectations, ensuring that the organization’s GIS infrastructure supports everyone effectively and consistently.

4. Unclear Roles and Responsibilities

Another common pain point is the question of “Who owns what?”

When data ownership and stewardship aren’t clearly assigned, essential maintenance tasks often fall through the cracks. Metadata goes out of date. Edits are made inconsistently. Layers get replaced, duplicated, or deleted without notice.

Without defined roles, accountability disappears — and so does trust in the system.

A governance framework explicitly defines:

Who owns each dataset

Who maintains it

Who has the authority to edit, approve, or publish it

How conflicts or errors are resolved

This clarity helps prevent both accidental errors and interdepartmental friction.

5. Strategic Impacts: Slowed Innovation and Missed Opportunities

When departments work in isolation, the entire organization loses out on the collective value of GIS.

Without shared standards or collaboration, it isn’t easy to:

Build enterprise dashboards that integrate data from multiple sources

Develop web maps and applications that rely on standardized schemas

Support AI and analytics workflows that require consistent and reliable data inputs

In other words, a lack of governance turns GIS from a strategic asset into a siloed tool. The organization spends more time managing data than using it to solve problems.

6. The Path Forward: Building a Data Governance Agreement

Establishing GIS data governance doesn’t have to be bureaucratic or heavy-handed. It simply requires a clear, shared understanding of how data should be managed and maintained. A strong governance agreement typically includes:

Authoritative Layers: Which datasets are considered the official source for each topic (parcels, roads, addresses, etc.).

Data Schemas: Field names, data types, and coding conventions that ensure compatibility across systems.

Standards of Service: Expectations for update frequency, quality control, and user support.

Roles and Responsibilities: Clear assignments for data stewards, editors, publishers, and reviewers.

Change Management Process: How new layers, schema changes, or data corrections are proposed and approved.

When organizations formalize these elements, collaboration becomes easier, data becomes more reliable, and GIS can finally deliver on its promise of providing a single, trusted source of truth.

In Closing

GIS is at its most potent when it connects, not divides, departments. But achieving that connection requires more than technology; it requires governance.

Without a data governance agreement, an organization risks wasting effort, achieving inconsistent results, and missing opportunities. With one, it gains confidence, clarity, and a foundation for more intelligent decisions.

In the end, GIS isn’t just about maps — it’s about management. And data governance is the roadmap that keeps everyone moving in the same direction.