Data is fragmented
Information is spread across sources, ownership is unclear or integration leaves teams reconstructing the same context repeatedly.
Problem Library
Start with the symptom. Trace it back to the system.
Technology problems rarely arrive with the correct architecture label attached. This library begins with what people actually see, mistrust, repeat or work around.
Start from what you are seeing
Six common symptoms. Different possible causes.
The symptom is a starting point, not a diagnosis. Each problem can cross data, intelligence, systems and software layers.
Reporting is unreliable
Numbers conflict, metric definitions drift or dashboards are hard to trust because the reporting layer is inheriting problems from upstream.
Systems don’t connect
Interfaces are brittle, handoffs are manual or overlapping applications create duplicate data and repeated operational work.
Too much work is manual
People repeat steps, re-key data, reconcile files or carry fragile workflows because the underlying system capability is missing or disconnected.
Technology costs keep growing
Licensing, duplication, technical debt or support effort increase without a clear relationship to business capability or measurable value.
We don’t know where AI fits
There is pressure to adopt AI, but usefulness, evidence, workflow fit and review requirements are not yet clear enough to justify a solution.
Why this matters
Symptoms cross architecture layers.
A reporting problem may begin in source data. Manual work may be caused by a missing interface. Rising cost may come from overlapping systems rather than vendor price alone. Reformeta treats the symptom as evidence to trace—not as a product category.
SYMPTOMWhat people seeSlow · fragmented · unreliable
→CONTEXTWhere it originatesData · systems · workflows
→CAPABILITYWhat needs to changeArchitecture · engineering · validation
How to use the library
Start broad. Narrow with evidence.
The goal is not to self-diagnose perfectly. It is to make the problem legible enough to choose a useful next step.
Name the symptom
Describe what people observe without assuming which technology is responsible.
Trace the context
Look at sources, definitions, interfaces, ownership, workflow and business impact around it.
Choose the next step
Decide whether the issue needs analysis, architecture, engineering, governance or a smaller experiment.
Have a problem that does not fit a neat category?
Good. Start with what is happening. We’ll help make the system around it legible.