A project manager is leading a software development project. The team is consistently delivering work late, causing schedule delays. The project manager suspects the initial duration estimates were too optimistic. What is the best action to improve future estimation accuracy?
Historical data improves estimation accuracy.
Why this answer
Reviewing historical data and lessons learned from similar projects (Option A) directly addresses the root cause of inaccurate estimates by leveraging empirical evidence from past work. This aligns with the PMI's iterative estimation approach, where actual performance data (e.g., velocity from previous sprints) is used to calibrate future estimates, improving accuracy over time. In software development, this is analogous to using historical cycle times or story point completion rates to refine planning poker sessions.
Exam trap
CompTIA often tests the misconception that schedule extensions or resource additions are the primary corrective actions for delays, when the correct approach is to improve the estimation process itself through data-driven methods like historical analysis.
How to eliminate wrong answers
Option B is wrong because extending the schedule does not improve estimation accuracy; it merely accommodates the symptom of delays without addressing the flawed estimation process. Option C is wrong because adding team members to a late software project often increases coordination overhead (Brooks's Law) and does not correct the underlying optimistic estimates. Option D is wrong because applying a blanket 20% increase is arbitrary and unsupported by data; it ignores the specific factors that caused the original estimates to be too optimistic, such as overlooked complexity or technical debt.