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Is this process actually ready to automate?

AI and automation scale whatever they're pointed at — including the chaos. Twelve questions across four dimensions tell you whether this process is ready for touchless workflow, or whether automation will just make the firefighting faster.

Standardization

Does the process run the same way every time, everywhere?

1. The process is documented, and the documentation matches how the work is actually done.

2. Different people (or teams, or shifts) execute the process the same way.

3. Inputs arrive in a consistent, predictable format.

Exception & Error Profile

Automation is only as good as its handling of the cases that don't fit.

4. We know our exception rate — what percentage of items fall outside the standard path.

5. Exceptions have a defined handling path with a named owner (not "whoever notices").

6. When errors occur, root causes are identified and addressed — not just patched.

Controls & Oversight

Touchless doesn't mean unwatched.

7. Critical control points (approvals, reconciliations, compliance checks) are explicitly identified.

8. We have defined what a human must still review after automation — and why.

9. If the automated process drifted or failed silently, our monitoring would catch it within days, not months.

Data Quality

Models and bots inherit every flaw in the data they run on.

10. The data feeding this process is accurate and complete enough to act on without manual correction.

11. There is a single agreed source of truth — not competing spreadsheets and systems.

12. We have baseline metrics (volume, cycle time, error rate) to compare against after automation.

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Automation readiness is whether a process is stable, standardized, and documented enough that automating it will produce reliable output. Automating an unstable process does not fix it — it executes the existing defects faster and at greater scale, while making them harder to see.

What it assesses

Process stability, degree of standardization, exception rate, data quality, and documentation — the five conditions that determine whether automation multiplies value or multiplies error.

Who it is for

Leaders evaluating an RPA, workflow, or AI automation investment who want to know whether the underlying process is ready before committing budget.

How to read the result

A low score is not an argument against automation. It is a sequence instruction: stabilize and standardize first, then automate. Automation applied to a process with a high exception rate typically increases total handling cost.

What the tool asks for

Common questions

Should you automate a broken process?

No. Automation executes whatever process it is given, faster and at larger scale. If the process produces defects, automation produces more of them — and buries the cause under a layer of tooling.

What makes a process ready for automation?

Low variation, a documented standard, a manageable exception rate, structured input data, and a clearly defined output. Processes meeting those conditions automate reliably; processes that do not tend to generate more exception handling than they save.

What is the right order — improve or automate?

Stabilize, standardize, then automate. Improvement removes variation and defects; automation locks in whatever remains. Reversing the order makes the defects permanent.

How do exception rates affect automation ROI?

Heavily. Exceptions fall back to manual handling, and automated exception handling is usually more expensive per case than the original manual process. A high exception rate can erase the entire business case.

Related tools

COPQ Calculator · Mandate Clarity Diagnostic — or see the full Windy Hill Toolkit.

Built by Windy Hill Partners, a process improvement consultancy applying Lean Six Sigma and DMAIC. Every tool here is free and ungated at the point of use.