Definition
Problem Framing and Stakeholder Analysis Problem framing and stakeholder analysis define the operational problem before selecting a technical solution. The work identifies affected users, decision makers, workflow owners, incentives, constraints, current failure modes, desired outcomes and potential harms. For AI projects it also asks whether the problem is caused by missing capability, poor process, data quality, organisational incentives or a genuine need for probabilistic automation.
Problem framing defines the current situation, affected people, desired change, constraints and evidence. A solution statement disguised as a problem prevents exploration.
Stakeholder analysis identifies users, decision-makers, operators, data subjects and people who bear risks. Their interests and authority are rarely identical.
Engineering Mode
Problem framing determines the system boundary before architecture hardens it. Engineers need to know whose workflow changes, what decision is being supported and which harms matter. Design work maps stakeholders, incentives and escalation paths. Build work should preserve the chosen boundary in requirements and tests. Operations measure whether the framed problem is actually improving. The risk is optimizing a model for the wrong institutional problem.
Evaluation check
Ask what observable evidence would show that this concept has been applied well in a real system, repository or learning exercise.
Real Example
A hospital sepsis-prediction project can fail despite a strong model if the problem is framed too narrowly. Clinicians, nurses, patients, IT, compliance and operations teams must define who receives alerts, what action follows, how false alarms are handled and how responsibility is assigned.
Related Concepts 