In the CPMAI lifecycle, which phase focuses on checking whether the model satisfies defined business requirements before deployment?

In the CPMAI lifecycle, which phase focuses on checking whether the model satisfies defined business requirements before deployment?

• A. Deployment
• B. Data Understanding
• C. Evaluation
• D. Minimum Viable Model (MVM)

Answer: (C)

Evaluating whether the model meets defined business requirements before deployment is the evaluation phase. In this stage, you verify that the model’s outputs and behavior align with what the business needs, including accuracy and performance targets, reliability, safety, fairness, and any regulatory or operational constraints. It’s the formal check that the model will actually deliver the intended value in real use and won’t introduce unacceptable risks once it goes live. This gatekeeping ensures stakeholders approve the model’s readiness, and it helps catch misalignments between technical performance and business objectives before moving into production. Deployment comes after this validation, as the act of releasing the model. Data Understanding focuses on exploring and characterizing the data you’ll work with, and Minimum Viable Model aims to produce a simple version to test feasibility and gather early feedback rather than full business requirement validation.

Evaluating whether the model meets defined business requirements before deployment is the evaluation phase. In this stage, you verify that the model’s outputs and behavior align with what the business needs, including accuracy and performance targets, reliability, safety, fairness, and any regulatory or operational constraints. It’s the formal check that the model will actually deliver the intended value in real use and won’t introduce unacceptable risks once it goes live. This gatekeeping ensures stakeholders approve the model’s readiness, and it helps catch misalignments between technical performance and business objectives before moving into production.

Deployment comes after this validation, as the act of releasing the model. Data Understanding focuses on exploring and characterizing the data you’ll work with, and Minimum Viable Model aims to produce a simple version to test feasibility and gather early feedback rather than full business requirement validation.