Carithm Research Paper 02
Workshops do not lose revenue because they fail to identify issues — they lose revenue because they cannot convert early signals into timely customer decisions.
A vehicle is inspected, and a component is flagged as nearing end-of-life.
The condition is not urgent enough for immediate action, so the recommendation is deferred.
Shortly after, the same vehicle returns with a failure that now requires urgent repair rather than planned maintenance.
The failure was not unexpected — it was not acted on at the correct time.
Customers do not reject maintenance because they distrust workshops.
They reject it because recommendations are not anchored in visible timing logic.
“It might need replacing soon” does not create urgency.
Most workshops already have the data needed to improve decisions:
The limitation is not data availability — it is lack of structure in how it is interpreted.
The constraint is not diagnostic capability — it is timing intelligence.
Most workshops identify issues correctly but lack a structured way to determine when those issues become actionable.
This leads to deferred maintenance, lost preventative revenue, and avoidable repeat failures.
Closing this gap requires converting service history into lifecycle positioning — so decisions are based on progression, not opinion.
This is the problem Carithm addresses for workshops — turning existing service logs into structured lifecycle context that makes preventative decisions clearer, earlier, and easier to approve.