What the data says
Synthetic data · illustrative onlyApplication funnel
Intake → decision → outcome. Rejections split into technical (fixable defects) vs genuine (real ineligibility).
Rejection composition
Share of rejections that are technical vs genuine.
Technical-rejection drivers — the 80/20
Pareto of technical reason codes. The few bars on the left are where fixing the form/UX removes most avoidable rejections.
Volume & technical-rejection rate by district
Bars = applications. Line = % of that district's rejections that are technical. Click a bar to drill in.
Top services by volume
Click a bar to drill into a service.
Approval-flow friction
How many times applications were bounced back internally or sent to the citizen for correction.
Turnaround time (decided)
Distribution of end-to-end TAT in days. Red = beyond service SLA.
Monthly trend
Applications submitted and SLA-breach rate over time.
Where TAT breaches concentrate — by service
Services ranked by SLA-breach rate (min. 20 decided applications). Click ⏱ to jump to a sample slow case.
Application journey
Event-by-event path of one application through the approval chain. Pick a case: