Service
A practical audit for teams that need a clear view of what is blocking day-to-day EAM use. The review stays close to work orders, master data, SQL/FlexSQL logic, reports, custom rules and interface handovers. The result is a prioritised improvement backlog, not a theoretical slide deck.
Typical starting points
The service is useful when the issue is specific enough to inspect in real systems, reports, data samples or daily workflows.
I compare maintenance plans, generated orders and completion history with the work technicians actually perform. This exposes obsolete intervals, wrong triggers and recurring cancellations before they distort workload and compliance figures.
I trace important figures through joins, filters, status rules and calculated fields, then validate the result with report users. The goal is one agreed definition that can be tested against representative records.
I identify where each rule runs, which business decision it supports and what depends on it. Useful custom logic becomes documented, testable and safer to change instead of remaining tribal knowledge.
I follow representative records across EAM and connected systems to separate usability or training issues from mapping, timing and validation failures. That keeps the improvement focused on the real cause.
Scope and deliverables
The scope stays close to the systems, data and workflows that affect day-to-day work. The deliverables are designed to support a clear next decision.
How it works
A defined sequence keeps the work focused. Representative examples and access to the right owners make the review faster and more reliable.
Review current processes, reports and data samples
Interview operational and technical owners
Trace the main bottlenecks across EAM, interfaces and office workflows
Deliver a clear improvement backlog ordered by operational and commercial impact
Fit and boundaries
A focused scope makes the work easier to evaluate, deliver and hand over.
Related services
Operational problems can cross system, data, interface, workflow and AI/ML boundaries. These services are often relevant together, but each can also stand alone.
Bring the current workflow or problem, a few representative examples and the business context. The first step is to decide what is worth changing, testing or leaving alone.