Cost Leakage Reduction
Turn unclear operational activity into tracked categories, accountable follow-up and measurable savings.

This impact room brings together the data products I have delivered, the operational problems I worked on, the measurable results created and the skills I applied to make the impact repeatable.
Across the work, I used analytics, BI, automation and AI to reduce avoidable cost, shorten processing time, improve reporting and give teams a clearer view of what needed attention.
Turn unclear operational activity into tracked categories, accountable follow-up and measurable savings.
Expose bottlenecks, aging work, exceptions and capacity gaps so leaders can reduce cycle time.
Replace manual Excel reporting with governed dashboards, reusable rules and repeatable data pipelines.
I separate measured delivery outcomes, estimated cost exposure, model performance and synthetic demo outputs so you can review the proof without exposing private operational data.
Used where the work has a clear before-and-after operational result, such as reporting time saved or processing time reduced.
Used where analytics surfaced avoidable cost or risk patterns that teams could inspect and act on.
Used in public sandboxes with synthetic, sample or anonymised data to show workflow, logic, controls and decision outputs safely.
Each case shows the problem I worked on, what I built, what the team could measure afterwards and the technology that made the result repeatable.
Alarm response activity was difficult to inspect consistently, especially where false alarms had unresolved or unclear causes. This created avoidable response effort, weak root-cause visibility and heavy manual Excel reporting.
Implemented a Power BI alarm reporting workflow with cleaner cause categorization, response tracking, exception visibility and recurring operational review views for managers and response teams.
The team can now track alarm patterns, reduce repeated false-alarm responses, prioritize unresolved causes and make decisions from a shared dashboard instead of scattered spreadsheets.
Regional teams needed faster management reporting across countries, cleaner data quality rules and consistent KPI visibility for operational and finance reviews.
I built regional BI assets around Snowflake warehousing, Power BI reporting, CRM analytics, business-rule validation, SOP documentation and analyst enablement.
Leaders gained a clearer view of country performance, budget movement, operations trends and recurring reporting quality issues before month-end decisions.
Migration operations needed a clearer view of processing stages, aging cases, capacity constraints and exceptions affecting exit-permit turnaround.
I built Fabric, SQL and Power BI analytics that tracked stage-level movement, highlighted bottlenecks and supported operational capacity planning.
Management could inspect where work was slowing, adjust resources and communicate operational performance using evidence rather than fragmented status updates.
Recurring KPI packs, reconciliations and exception reviews required manual effort and slowed operational reporting cycles.
Automated recurring reporting workflows, created reusable business rules and built exception views for managers to inspect issues faster.
Teams spent less time assembling reports and more time reviewing risk, workload, quality and programme performance.
High-volume resettlement operations needed reliable visibility into case movement, workload allocation, quality checks, departure readiness and system migration readiness.
I built Tableau, SQL and Python reporting workflows, supported UAT and data-quality reviews, mentored analysts and contributed to migration of 100,000+ case records to the START platform.
Departments gained better inspection of workload, processing quality and readiness signals across sensitive beneficiary operations.
Claims teams needed cleaner reconciliations, stronger visibility into inconsistent claims records and practical signals for fraud and payment-risk review.
I built claims reporting, reconciliation workflows, data-quality checks and an early fraud-detection model for medical claims analysis.
The work helped strengthen claims review discipline, reduce ambiguity in reconciliations and connect analytics to financial-risk monitoring.
Use the sandbox to test my projects directly: DataLens BI, churn prediction, WorkIQ, document intelligence, forecasting and other interactive tools.
Use the War Room to see how project risks, evidence, dashboards and decision movement can be organized for serious data and AI delivery.
Start with one business pain point, one measurable success metric and a clear path from data source to decision.