AI Workbench

Problem and outcome

The problem or intended outcome is unclear or framed as a predetermined solution.The problem and outcome are named, but they remain broad or mostly assumed.Evidence supports a specific user problem, intended outcome, and meaningful measures of success.Evidence shows the problem's importance and scale. The intended outcome, baseline, and measures align with the organization's purpose.

Users and wider journey

The users and their current experience are unclear.Key users or journey steps are described, but the account relies mainly on assumptions or second-hand views.Research explains key users' goals, behaviour, pain points, channels, and place in the wider journey.Research includes relevant excluded groups and connected services. Findings materially changed the problem framing or scope.

Constraints and viability

Material organizational, policy, technical, or operational constraints are missing.Some constraints are listed, but their impact or evidence is unclear.Evidence identifies the crucial constraints, capacity, costs, dependencies, and responsible decision makers.Hard and changeable constraints are distinguished. Owners understand the changes, resources, and commitments required.

Options considered

Discovery assumes one solution.It considers a few similar options with limited evidence or comparison.It compares genuinely different responses, including non-technology options, against user and organizational needs.Credible evidence tests the main trade-offs. Feedback and research changed the shortlist or preferred direction.

Direction and rationale

Discovery reaches no clear direction or reason to continue.It names a preferred direction, but the rationale does not address evidence, alternatives, value, or cost.The direction and scope follow from the evidence, expected value, constraints, and comparison of alternatives.The rationale explains why to continue, change direction, or stop. It records evidence gaps and conditions that could change the choice.