Architected a multi-tiered Power BI platform over 3 months, converting Excel logs into diagnostics covering Productivity, EWH, and Fuel Analysis.

The OpEx team lacked visibility into heavy equipment inefficiencies; raw .xlsx data obscured bottlenecks.
Architected a multi-tiered Power BI platform over 3 months, converting Excel logs into diagnostics covering Productivity, EWH, and Fuel Analysis.
Shifted the OpEx team from reactive reporting to data-led advisories, isolating downtime causes and flagging fuel burn.
A comprehensive Operational Intelligence suite for Awakmas (MDA), translating heavy machinery metrics into actionable insights.












Separated EWH into Ready, Delay, Standby, Breakdown states, isolating time-sinks (SNJ, Digger Repair).
Mapped EWH against earthmoving volume (Bcm), highlighting low-yield high-hour days.
Deployed Fuel Ratio (L/Bcm) tracking across activities, flagging suboptimal performance.
Engineered ingestion of fragmented .xlsx logs into a relational DAX model.
Designed modules (Productivity, EWH, Digger Detail, Fuel) with slicers and variance indicators.
Advised OpEx on interpreting diagnostics for continuous improvement.