Intervention & Outcome Tracking
Closing the loop from insight to action to measured outcome. Outcomes are described as observed or associated changes — attribution limits are stated on each card. All interventions are illustrative.
Umm Salal recurring-complaint elimination (document checklist redesign + staff coaching)
Quality Assurance · Municipality Services · Umm Salal · initiated Mar 9, 2026
ProblemUmm Salal center generated the highest repeat-complaint rate nationally, driven by rejected applications.
Attribution: Improvement observed after the intervention within a stable demand period; other factors (seasonality, staffing changes) not fully controlled — estimated contribution, not proof of direct causation.
Health appointment booking awareness campaign
CGB Communications + Health Services · Health Services · initiated Mar 31, 2026
ProblemDigital health-appointment booking was underused (54% share) despite being the fastest channel.
Attribution: Adoption gain coincided with the campaign window; the booking redesign shipped in March also contributed — estimated contribution shared between the two.
Al Rayyan capacity relief (weekend hours + mobile units)
Service Center Operations · Al Rayyan · initiated Jul 5, 2026
ProblemAl Rayyan first-response time reached 2.4x the national average; both centers above design capacity.
Attribution: Outcome will be read against the June baseline; summer demand seasonality is a known confounder.
Labour Services 30-day response plan
Labour Services + CGB Government Performance · Labour Services · initiated Jul 8, 2026
ProblemWork-permit renewal complaints rose 46% week-over-week; entity sentiment negative for six consecutive weeks.
Attribution: Sentiment is influenced by external news cycles; recovery will be treated as associated with, not proven by, the response plan.
Kawader app remediation sprint
CGB Digital · Civil Service Services · initiated Jul 7, 2026
ProblemKawader holds a verified 1.6-star App Store rating; registration failures dominate public reviews.
Attribution: Store ratings lag fixes; early reviews will still reflect the pre-fix experience.
In production, before/after windows would be locked at initiation and measured against control baselines to reduce attribution bias. Improvements shown are associated with the interventions, not proof of direct causation.