eqAnalytics

Every asset lives in one governed record, pulled from your CMMS and fixed asset data. The same record feeds every other stage, so the asset data behind a request does not have to be rebuilt each time it moves.

Replacement priority is scored on lifecycle stage, condition, and use, not age alone. Priority becomes something the committee can sort on, rather than a case each department argues on its own terms.

Useful life is measured against actual asset age and real performance, not just a depreciation schedule. Where the evidence supports a longer life, the capital earmarked for that asset is freed for equipment genuinely at end of life.

Service and repair history feeds straight into the replacement decision. A machine repaired three times in a quarter stops being an anecdote and becomes part of the written case.

Replacement need is forecast out to a ten-year capital horizon. The forecast moves as condition and service data change, instead of being rebuilt from scratch each planning cycle.

Condition is captured in the field, plus manufacturer end-of-support data to guide timing. Assessments stay attached to the device rather than living in a survey file that is never opened again.

Device-level need rolls up to department, site, and system. Leadership sees one number, and anyone who questions it can trace it back to the specific devices behind it.

Compare equipment performance and need across every site in the system. Where one site is carrying a materially older fleet than the rest, it surfaces before it becomes an emergency.

Data gaps get found and enriched, whatever shape your data starts in. Most systems start with imperfect data, and this is the work that makes it usable for planning.