The backend
CivicDataLab's data team was consolidating disparate scheme indicators into a single open-data pipeline.
Monitoring district performance shouldn't require 20 open tabs
I designed a Minimum Viable Product (MVP) for an open-data dashboard to help government officials in Assam track regional development metrics in one unified view. By aggregating indicators across multiple schemes into a single platform, the design eliminates platform-switching and simplifies daily data analysis for district officials.
It takes a “district” to make a MVP
Mentored by Anushka Gokhale (Sr. Product Designer) and collaborating with cross-functional Research, Data and Tech teams, I led the user experience through four key phases.
*Gantt have a real project with clean cut phases
Making complex performance data readable
District performance metrics in India are siloed across multiple systems and scheme-centric platforms, making tracking slow and fragmented. Assam was selected as the first state to tackle this challenge.
My role
To design the front-end user experience and help structure raw metrics into an intuitive dashboard for easy browsing.
What do district officials need of their data?
Through the insights from our research and data science teams, we identified three core user priorities.
Block-level data analysis is essential to finding patterns and problems
Information and data sources need to be transparent to establish trust in ideas
Periodic data updates needing quick checks and easy exports
Mapping familiar design patterns
Beyond core functional needs, research showed that our users weren't very tech-savvy, meaning introducing new patterns could create steep learning curves. I benchmarked existing Indian and global dashboards to map the design patterns they are already accustomed to while also framing new questions about platform requirements.
*Snippets of my notes from the mapping
Creating screens to test
In a quick 3-day sprint, I explored multiple layouts and information flows to test directly with users and identify early friction points.
*Wireframing for government products looks like small decisions with big impacts
Balancing user needs with MVP feasibility
Designing alongside an evolving dataset created a two-way feedback loop with the data team to align user desires with technical constraints.
Informing pipelines: UI concepts helped the data team understand what level of granularity was needed in sections like the overview.
Scoping phase 1: Technical limits helped trim complex features into the Phase 2 roadmap.
Mapping the information architecture
To build a foundation for the interface, I mapped an information architecture that followed a drill-down hierarchy based on the scope requirements.
*A high-level view of the IA
The solution
Core problems discovered and how they were solved for.
1. How might we build a scalable structure that preserves granular, drill-down data?
- Clear navigation structured from State → District → Department → Scheme helps handle multi-level data seamlessly.
- Persistent sidebar on district views allows fast switching between departments without resetting context.
- A Scheme Explorer view with granular block-level metrics makes analysis easier.
2. How might we provide users with easy-to-scan updates?
- Key metrics and information are surfaced at every level — state, district, department, and scheme.
- High-level summary cards deliver immediate status checks without forcing deep navigation.
- Prominent “Last Updated” timestamps ensure officials know the freshness of their data.
3. How might we build trust through complete data transparency?
- Direct CSV downloads for each scheme enable independent analysis.
- Clean, print-ready page layouts are designed for offline reporting and official meetings.
- Contextual tooltips explain metric calculations and link directly to primary data sources.
4. How might we ensure seamless data access for officials on the go?
- A mobile-first design approach ensures that officials can access the dashboard from any device, anywhere.
- Responsive layouts adapt to different screen sizes, maintaining usability and readability.
- Quick-glance summaries and collapsible sections allow for fast navigation on smaller screens.
System audit highlights
Phase 2 backlog: Explicitly documented non-MVP features for future roadmap planning.
Design discrepancies: Cataloged UI variations between Figma specs and web implementation.
Validated assumptions: Tracked baseline design assumptions to guide upcoming user testing cycles.
Key component guidelines
Usage context: Detailed functional guidelines and state rules for each UI component.
Responsive rules: Documented layout adaptations and breakpoint behavior for mobile screens.
Team feedback loop: Captured insights from data teams and end-users to justify layout and IA choices.