CAPM Practice: Explain when it is appropriate to use an adaptive approach

This scenario illustrates that requirements stability and technical uncertainty are separate dimensions. Stable requirements could favor predictive, but high technical uncertainty means the implementation approach is unknown — requiring experimentation and iteration. An adaptive approach for the technical implementation (even with stable requirements) allows learning and course correction on the HOW, even when the WHAT is clear.

**Why not A:** Research projects absolutely use formal project management — they have schedules, budgets, stakeholders, and deliverables that require coordination and governance. Dismissing formal PM for research contexts conflates informality with agility and ignores the real need for structured management of complex, uncertain work. Many research organizations use adaptive frameworks precisely because uncertainty is high.

**Why not B:** Stable requirements are only one of two relevant dimensions; technical uncertainty is equally important. While stable requirements favor predictive upfront planning for scope, the novel algorithmic implementation means the team cannot plan the technical approach in advance — iteration and learning are necessary. A purely predictive approach would require locking in technical decisions before the team has sufficient information to make them reliably.

**Why not C:** Stating that adaptive is appropriate simply because algorithms are novel is correct as far as it goes, but it ignores the important nuance that the choice depends on weighing both factors. This answer does not acknowledge the stable requirements dimension, which is a meaningful signal about parts of the project that could benefit from predictive elements. The most accurate and complete answer recognizes that both dimensions matter and explains how they interact.