> ## Documentation Index
> Fetch the complete documentation index at: https://irisdocs.prescientlabs.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Running a Diagnostic Engagement

> A practical end-to-end method for turning a client problem into validated evidence, prioritised opportunities and an implementation decision.

A diagnostic is not a generic AI workshop. Its purpose is to build enough evidence for the client to make a better decision about what should change and what should be implemented first.

## The diagnostic sequence

1. **Kickoff** — confirm objective, scope, stakeholders, timeline, governance and success criteria.
2. **Stakeholder selection** — include leadership, process ownership, frontline execution and relevant adjacent teams.
3. **Evidence capture** — use interviews, screen observation where appropriate, documents and structured operational data where useful.
4. **Current-state understanding** — reconstruct the workflow, variants, handoffs, queues, rework, workarounds and system switching.
5. **Validation** — separate confirmed evidence from inference and unresolved assumptions.
6. **Opportunity identification** — consider eliminate, simplify, standardise, automate, augment, integrate, redesign, train or change policy.
7. **Prioritisation** — assess impact, feasibility, data readiness, risk, effort, time to value and dependencies.
8. **Value modelling** — estimate capacity, cost, revenue, cycle-time, quality or risk benefits with transparent assumptions.
9. **Roadmap** — sequence quick wins, prerequisites and strategic initiatives.
10. **Executive readout** — present the conclusions, evidence and recommended first project.
11. **Implementation transition** — convert the diagnostic into a defined next engagement where justified.

## Where Iris supports the method

Iris can support unstructured evidence capture through stakeholder interviews and consent-based screen observation, and structured process analysis where the relevant product capability is available. It helps create a more repeatable evidence base for the consultant.

The consultant still owns:

* the business question;
* scope;
* stakeholder coverage;
* validation;
* recommendation quality;
* executive narrative;
* implementation decisions.

## What good looks like

The final recommendation should be traceable to evidence, commercially relevant and specific enough for the client to decide what to do next.