AUTOMATIONSCAN TRANSFORMATION METHOD™

Business first. Evidence before technology.

AutomationScan is designed to structure transformation discovery—not to manufacture a vendor winner from incomplete information.

METHOD

From business context to decision readiness.

The method separates facts, calculations, hypotheses and validation requirements.

Capture industry, business model, operating model, scale, geography, goals and current applications.

Map processes, pain, customisation, integrations, spend and measurable outcomes.

Separate ERP capabilities from specialist applications, workflow platforms, data and integration layers.

Identify maturity, application health, regulatory considerations, automation opportunities and transformation scenarios.

Generate an investigation set from industry and capability signals. This is not a procurement ranking.

Turn uncertain claims into scripted demos, POCs, reference checks, architecture evidence and migration rehearsals.

Use customer-supplied assumptions to model TCO, opportunity signals and business-case scenarios.

Compare Stay/Optimise, Modernise/Extend, Complement and Replace against the evidence.

Translate the selected direction into discovery gates, migration readiness, roadmap and governance.

EVIDENCE MODEL

AutomationScan distinguishes what the business told us from what the system calculated and what still needs proof.

Information entered directly by the business or analyst. Useful, but not independently verified.

Evidence supplied from an inventory, invoice extract, contract, process record or other business source.

Values calculated or detected from supplied records. The calculation path remains visible.

External claims carry a source, date and validation status rather than appearing as unexplained facts.

Unknowns are explicitly marked so they cannot silently become facts in a business case.

Important uncertainty becomes a scripted demo, POC, reference check, document review or owner action.

EVIDENCE STANDARD

Unverified vendor capabilities are labelled for validation.
Missing catalogue evidence is not treated as proof that a capability does not exist.
Savings are not presented as guaranteed ROI.
Customer references are not invented.
Benchmark figures are not fabricated.
Regulatory content is a consideration checklist, not legal advice.
AI/agentic claims should be tested against demonstrated workflows, controls and measurable outcomes.
Vendor or partner relationships should not secretly change the customer-specific analysis.