Overview · for the Head of Reliability & Maintenance
The next EGP belongs on the controllable levers and on the escalation list
One in five observations (19.2%) is high-risk, and that slice carries 46.7% of all revenue loss. Yet 829 of the 960 high-risk observations are flagged only P3 or P4. Reactive maintenance runs 2.3x the downtime of predictive, and spare-part shortages 2.9x the downtime of available stock.
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ℹHow to read this. Each row is one
30-day observation window, not a unique asset:
Asset_ID is not a stable key in this export
(see Data & Method). Lever differences are associations from observational data, tested for significance,
not proven causes.Unplanned downtime by maintenance strategy
Mean hours per 30-day observation. Reactive sits at 2.3x predictive; tested, large effect on failure probability.
Unplanned downtime by spare-parts status
Mean hours per observation. Shortage runs 2.9x available stock.
Mean revenue loss per observation, by month
EGP per 30-day window, . The year is flat: no trend to schedule against.
Where executive priority flags actually land
Observations by Executive Intervention Priority. Only 134 are P1 or P2.
Through-line. Loss is concentrated, not spread: the top 10% of observations carry
44.7% of revenue loss. The concentration lines up with things management controls
(strategy, spares, crew skill, PM discipline), not with where an asset happens to sit. Fund the levers, and
widen the escalation list so it catches the high-risk windows it currently misses.