Modernizing government software

The problem: Limited by legacy technology but eager to innovate

Over the past decade, a State of Colorado Division had accrued a patchwork of outdated software systems, including manual batch processing of permit data, a difficult-to-use support workflow for interacting with the public, and an ad-hoc permit assignment solution in Microsoft Access. This piecemeal technology constellation resulted in time-consuming data management, an inflexible technology stack, and occasional enterprise system failures in a Division that faced continually evolving demands from State and public stakeholders. Additionally, the government team at the Division felt they had little time or opportunity to innovate internally, in part because their data was disorganized and in some cases inaccessible.

The Division recognized a need for modernization and contracted Cornflower Labs to implement a modern, cloud-based system to integrate their technology stack, regain control of their own data, and handle permit assignments in a custom, modern, flexible management system.

The approach: Integrating cloud-based modernization and AI transformation

The Cornflower Labs worked with Division technical leadership to create a long-term technology modernization strategy, working first with Division stakeholders to capture the parts of the outdated systems which worked well and which worked poorly. Based on this evaluation, Cornflower recommended modernization improvements via a transition to an AWS-based customizable software permit assignment system while retaining well-liked aspects of the legacy systems.

By using a Scrum-based project management method, Cornflower Labs engaged agency stakeholders in the entire design and testing process. Cornflower Labs’ process leveraged software development and design best practices: designers began with low-resolution wireframes and progressively moved to high-resolution interface prototypes. The technical team then began code testing and deployed the code seamlessly into production. This method reduced risk, ensured staff and leadership were involved in the change management process, and allowed nice-to-have features to be easily integrated into the overall system.

To complement the Division’s modernization efforts, Cornflower Labs developed an AI-powered chatbot tool to seamlessly break down complex permitting documents for internal and external stakeholders, enabling easy understanding and navigation of the Division’s content and improving the Citizen Experience (CX) of the Division’s users. The AI tool automatically reads from Division documents, providing real-time automated responses combined with citation-based support for all insights, complementing the Division’s traditional support methods and reducing support load.

Services provided

• User-centered design
• Custom workflow management tool
• Data validation and data cleaning processes
• Integrations with other technology systems
• Automated CSV processing
• Cornflower Chat design and implementation

Value created: Enabling streamlined data analysis and process improvement by moving to a modern cloud-based system

By engaging a custom version of an AWS-hosted platform, the Division realized significant process improvements, reducing manual errors to zero when updating permit assignments and freeing up staff to focus on higher-priority and higher-impact tasks. In addition, the Division was able to consolidate all of their permit data in a modern, cloud-based SQL database, moving to a shared, real-time permit management assignments system. One long-term effect of this integration was to enable up-to-date data analysis via SQL and visualization via Tableau. This helped Department decision-makers obtain direct insight into permitting assignment workflows, further reducing the need for Division staff to manually compile data and reports.

The modernization effort also enabled easy customization of code and data schemas, launching further AWS-based innovation in software projects with Cornflower Labs as a strategic partner of the Division.

The overall results led to:

• Higher user satisfaction in the system
• Improved ability to update and modify the system to effectively respond to external and internal needs
• Reduced manual file transfer and calculation needs, eliminating error-prone and time-consuming processes
• Improved ability of division staff to assign permit inspections and analyze permit data