Impact Measurement
Did the intervention actually work? Before-and-after evidence on the outcomes citizens experience.
Synthetic demonstration outcome. This scenario illustrates how the platform measures impact after the recommended interventions are implemented. Figures are simulated and do not represent real results.
Permit Processing Optimization
Baseline: W36–W39 2026 → Scenario: 12 weeks post-intervention
BEFORE
- Average processing time
- 8.4 days
- Backlog
- 4,820
- SLA achievement
- 76%
- Rework
- 21%
- Citizen satisfaction
- 72%
AFTER
- Average processing time
- 6.3 days
- Backlog
- 3,410
- SLA achievement
- 89%
- Rework
- 14%
- Citizen satisfaction
- 81%
IMPACT
Processing Time25%
Backlog29%
SLA achievement13 percentage points
Rework7 percentage points
Citizen satisfaction9 percentage points
13,185
citizen waiting-days avoided per month (est.)
754
additional cases per 4 weeks completed within SLA (est.)
5 / 5
success metrics improved
Outcome trajectory
Shaded bands mark the pilot and post-intervention periods.
Average processing time (days)
Backlog (open cases)
SLA achievement (%)
Interventions measured
Automated document pre-validation (REC-2026-014)View →
Workload redistribution Unit Central → Unit East (REC-2026-015)View →
Fast lane for complete applications (REC-2026-016)View →
Open Service 360 How impact is measured
• Baseline and post-intervention periods of equal length, same service scope.
• Success metrics defined up-front in the action plan (e.g. rework below 15%).
• Seasonality and volume changes checked before attributing improvement to an intervention.
• Where multiple interventions overlap, impact is reported jointly — not attributed to a single action.
Prototype method: simulated pre/post comparison over synthetic weekly data. A production system would use interrupted time-series or matched comparison groups.