> ## 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.

# Scoping a Diagnostic

> Define a bounded business question, process scope and stakeholder evidence plan before the engagement begins.

Poor scope creates poor diagnostics. “Find every AI opportunity in the company” usually produces shallow evidence and uncontrolled delivery effort.

## Start with the business question

Good questions connect a process to a business outcome, for example:

* Where does proposal production create avoidable rework?
* Why is customer onboarding taking longer as the company scales?
* Where could automation improve service throughput without reducing control?

## Define scope explicitly

Document:

* process start and end points;
* teams and locations included;
* relevant systems;
* stakeholder groups;
* interview coverage;
* where screen observation will or will not be used;
* outputs;
* exclusions.

## Set success criteria

Examples include a validated current-state map, agreement on the most important constraints, a prioritised opportunity backlog, transparent value assumptions and a decision on the first implementation project.

## Identify client responsibilities

The client may need to provide a sponsor, process owner, stakeholder access, participant availability, security/privacy approvals and timely review of findings.

## Scope control question

> Does this help answer the agreed business question, or is it a new piece of work?

If it is new, trade scope, timeline or fee rather than silently absorbing it.