Structural signals, not symptoms.
1. Failures are visible and diagnosable
When something breaks, it’s obvious what failed and why. Remediation is fast, and uncertainty doesn’t spread.
2. System boundaries are known
Each automation has a defined scope. You can point to where it starts, what it touches, and who owns it.
3. Change is intentional and reversible
You don’t fear updates. Each change is versioned, reviewed, and easy to roll back if needed.
4. Architecture reflects the business
The system mirrors the actual process. Logic follows the way work flows — not the way someone once automated it. Business functions are cohesive, and loosely coupled across boundaries.
5. The system is self-revealing
The logic is easy to follow. Naming is consistent, documentation exists, and the flow makes sense without tribal knowledge. You can navigate it without guesswork.
6. Failure is modeled, not discarded
When things go wrong, it’s part of the system — not an exception to it. Errors carry meaning, live in process state, and are handled with intent. Nothing gets thrown in a pile.
7. The system is valued and maintained
Its role is recognized. Ownership is defined. Budget, time, and care are allocated. This isn’t shadow IT — it’s operational infrastructure.
8. There is no residue
Dead flows are removed. Test logic is cleaned up. Temporary fixes don’t become permanent structure. Every part of the system exists for a reason — and it’s clear what that reason is.
9. It’s easy to reason about
Logic is broken into small, named components. Each part does one thing. Branching is minimal, coupling is explicit, and behavior is predictable. Small pieces compose cleanly — like commands in a pipeline.
10. The system is as simple as it can be
Complexity is earned, not assumed. Logic is explicit. Automations don’t try to be clever — they do exactly what’s needed, and no more.
11. Timing is predictable and appropriate
Automations run at the right time, not just any time. Triggers reflect real business events. Data isn’t stale, premature, or racing ahead of the process it supports.
12. Execution is observable over time
Every run leaves a trail. You can see what happened, when, and why — not just that “it ran.” The system tells its own history.
→ How many of these does your system meet?
This model doesn’t explain your pain. It names your structure.
If you’re scaling automation and want to see where it’s drifting, book a Clarity Audit.
No fix. Just a map.