How state licensing, permitting and enforcement agencies turn governance, architecture and business intelligence into decisions that leaders trust
A legislator asks how long your agency is taking to process license renewals this quarter. It’s a reasonable question, and it deserves a same-day answer. Instead, a staffer opens three systems, cross-references two spreadsheets and calls a colleague who left for the day an hour ago, all to produce a number nobody on the call is fully willing to stand behind.
This scenario plays out across state regulatory agencies every single day. Data problems rarely announce themselves as a single crisis. They show up instead as a delayed answer, a duplicate licensee record or an auditor’s follow-up question that takes a week to run down.
Data management and analytics landed at number eight on NASCIO’s 2026 State CIO Top 10 Priorities, and NASCIO flagged the category as one that declined this year, a shift that’s easy to misread as permission to look away. This year’s Top 10 marks NASCIO’s 20th annual report and draws on responses from all 51 state and territory CIOs.
That decline is worth reading carefully, because NASCIO’s own descriptions of the priorities ranked above it all assume the same thing: clean, accessible and well-governed data. Every predictive model, every fraud-detection algorithm and every executive dashboard draws on the records your agency already keeps. When licensing data scatters across spreadsheets, aging databases, shared drives and email threads, no amount of technology spending produces an answer your board trusts.
This article continues a 10-part series examining NASCIO’s top priorities for state regulatory agencies in 2026. Each installment explores how pairing advanced technology platforms with disciplined operational practices helps agencies meet elevated expectations, stretch limited resources and deliver better outcomes for the public they serve.
NASCIO defines Data Management & Analytics as seven components:
NASCIO’s companion ranking of priority technologies reinforces the emphasis, placing data management eighth and data analytics ninth among the tools state CIOs plan to fund in 2026.
Only 22% of states report having an established, enterprise-wide data quality program, even though 95% of state CIOs and chief data officers say AI and generative AI adoption is increasing the importance of data management.
For a licensing, permitting or enforcement agency, those seven components lead to four practical questions. Who owns each data element? Where does the authoritative record live? Which staff member views which field? How fast does a program manager answer a legislator asking about processing times?
Governance policies collapse when systems fail to enforce them. A written rule about who views disciplinary history means little when every staff member opens every record.
Role-based security turns policy into enforcement. The approach restricts access according to each person’s role, granting exactly the visibility that role requires. Strong implementations deliver several things governance teams need:
That last point pays off quickly. Staff who assemble information requests for other departments spend those hours away from licensing work, and role-based access hands requesters a secure door instead of a queue. GL Suite applies the same rules to reports and queries, so whoever cannot open a record cannot run analytics on it either.
Analytics fail quietly when the same licensee exists three times across three systems. Sound architecture consolidates licensing, inspections, continuing education, enforcement and financial records into one platform, then moves information in and out through governed interfaces rather than manual re-keying.
GAO has repeatedly found that fragmented, inconsistent data management — the result of records maintained separately across programs and systems with no common standards — limits government’s ability to validate and use its own data, a structural risk equally at play when licensee records live in three uncoordinated systems.
Our white paper Key Components of a Professional Licensing System describes the interfaces that carry most of this traffic:
Each interface needs safeguards. Automated alerts confirm when jobs finish, report whether they succeed and notify staff the moment a job fails. Silent interface failures corrupt analytics faster than any other technical problem, because the numbers still look plausible.
NASCIO names business intelligence explicitly, and this component delivers the fastest visible return. Robust reporting in GL Suite spans three layers:
The Microsoft Power BI integration renders those results visually and purpose-built dashboards track staff performance, business process performance and process flow performance. Managers drill into a bottleneck rather than requesting a special report and waiting a week.
Common reports that regulatory leaders run include applications and renewals by status, enforcement cases by status and date, open inspections by inspector and date, open claims, daily deposits and reconciliation and reports that internal audit procedures require. Role-based rules determine who views, reads and edits each one.
Prediction demands history. Agencies build that history by tracking daily work, then modeling patterns once the record accumulates. Because licensing systems log every action a user takes, they expose slow processes and error-prone ones.
Today, 72% of state CIOs and chief data officers describe their organization’s overall approach to data management as “reactive” rather than proactive or managed, exactly the maturity gap that stalls predictive analytics before it starts.
Start with the key performance indicators our white paper recommends:
Track those five consistently and forecasting follows naturally. Renewal season volume, inspection backlogs and enforcement caseloads all repeat in patterns that clean operational data reveals. Regulatory agencies that skip this step end up modeling noise.
Continuous improvement closes the loop. Metrics expose a bottleneck, the agency reconfigures the workflow, and the next reporting cycle measures the result. Regulatory agency software like GL Suite supports that cycle through configuration tools that let authorized staff adjust fields, screens and reports without custom development, keeping modernization in agency hands.
Data governance and cybersecurity share the same subject matter. Our eBook 5 Moves CIOs Must Take to Modernize State Tech pairs GovRAMP-ready cloud infrastructure with role-based access, audit trails and automated retention for exactly that reason.
State chief information security officers report growing responsibilities: 86% of state chief information security officers say their responsibilities are growing, yet more than a third have no dedicated cybersecurity budget line. It represents a gap that makes independently verified vendor security controls more valuable, not less.
GL Suite achieved GovRAMP Ready status in January 2026, the first licensing solution to meet the standard. GovRAMP Ready validates roughly 80 controls built on NIST SP 800-53, the federal catalog that organizes more than 1,000 security and privacy controls across 20 control families, verified by a third-party auditor rather than self-attestation. Data stewards gain documented answers about encryption, authentication, incident response and recovery objectives. Our conversation with CEO Bill Moseley explains how GovRAMP Ready raises the bar for vendor security.
1. Where does data management and analytics rank on NASCIO’s 2026 list? Data management and analytics ranks eighth among the 2026 State CIO Top 10 policy and technology priorities. NASCIO’s parallel technology ranking places data management eighth and data analytics ninth.
2. What does data governance mean for a licensing agency? Data governance covers the policies and accountability structures that determine how the agency collects, classifies, protects, retains and shares licensee information, along with the named roles responsible for each decision.
3. How does role-based security support data governance? Role-based security enforces governance policy inside the system. It grants each user access to exactly the records and reports their role requires, logs activity for audit purposes and allows immediate revocation when roles change.
4. What data does an agency need before attempting predictive analytics? Agencies need a consistent history of operational events: cycle times, volumes, accuracy rates and response times captured the same way across every process. Systems that log user actions automatically build that history as a byproduct of daily work.
Priority #8 rewards agencies that treat data as infrastructure rather than exhaust. Governance defines the rules; architecture consolidates the record; business intelligence surfaces the insight; and security protects all three.
GL Solutions has helped regulatory agencies run, grow and adapt since 1997. Explore how robust reporting in GL Suite delivers real-time queries, interactive dashboards and role-secure analytics, or contact our team to discuss your agency’s data strategy.
Renee Moseley joined GL Solutions in 2016 with an educational and professional background in research and writing, along with software documentation. At GL Solutions she produces informative content to help regulatory agencies stay current on news and information that supports their success.
