PMP Practice: Define Scope

This scenario presents high uncertainty in customer needs, regulatory environment, and technical feasibility — classic indicators that scope should evolve incrementally rather than be locked up front. A hybrid approach balances the sponsor's legitimate need for budget justification with the project's need for adaptive scope management. By creating a high-level product vision and roadmap, Sevda provides enough definition for financial planning while preserving flexibility to refine scope as the team learns. Time-boxed iterations with regular stakeholder reviews allow the team to incorporate feedback, respond to regulatory changes, and leverage emerging AI capabilities. This approach delivers value progressively while managing the significant uncertainties inherent in AI-driven health technology. The closing fact that the sponsor needs budget approval makes option B superior to a pure agile approach — it acknowledges organizational governance needs while applying adaptive principles where they create the most value.

**Why not A:** Developing a detailed WBS with fixed deliverables using a purely predictive approach ignores the significant uncertainty around customer preferences, evolving regulatory requirements, and rapidly changing AI capabilities. Locking scope upfront in this context would prevent the team from adapting to discoveries and changes that are expected throughout the project.

**Why not B:** Creating an MVP definition and then deferring all scope decisions is too passive. While the MVP concept is sound, waiting for the technology landscape to stabilize provides no mechanism for ongoing scope refinement. The sponsor needs enough definition for budget approval now, and the team needs a framework for making scope decisions incrementally.

**Why not D:** Recommending postponement until regulatory requirements are finalized and customer preferences are understood would delay the project indefinitely. Regulatory requirements for AI-driven health advice are evolving rapidly, and customer preferences may never fully stabilize. This approach fails to recognize that the project can deliver value incrementally while managing uncertainty.