Variance and Trend Analysis

Correct Answer: The project is progressively falling behind its planned schedule

A consistently decreasing SPI trend over three consecutive periods is a clear indicator that the project is progressively falling behind its planned schedule. Here's why: SPI is a measure of schedule efficiency, where: - SPI = 1 means on schedule - SPI < 1 means behind schedule - SPI > 1 means ahead of schedule When SPI shows a negative trend (getting smaller) over multiple periods, it definitively indicates worsening schedule performance. Why other options are incorrect: - Advanced statistical methods aren't needed when the trend is already clear across three periods - Modifying the baseline won't solve the underlying performance issue and would be inappropriate - Risk response strategies may be needed to address the schedule delay, but they aren't the cause of the consistent negative trend The decreasing SPI trend is a factual measurement that needs corrective action to address schedule delays.

Correct Answer: Moving average calculation with exponential smoothing

Moving average calculation with exponential smoothing is the most appropriate technique for identifying subtle patterns in risk impact data over extended periods because: 1. It smooths out random fluctuations in the data while preserving underlying trends 2. Exponential smoothing gives more weight to recent data points, which is crucial for risk analysis 3. It helps in detecting gradual changes and emerging patterns that might not be apparent in raw data 4. It's particularly effective for long-term data analysis where seasonal variations need to be normalized The other options are less suitable because: Standard deviation analysis is better for measuring variability rather than identifying patterns over time. Root mean square error analysis is primarily used for measuring prediction accuracy, not pattern identification. Linear regression analysis assumes a linear relationship between variables, which may not capture the complex nature of risk patterns effectively.

Correct Answer: Determine the root causes of the variance and update risk response strategies

When cost variances are detected during risk monitoring, the most critical first step is to determine the root causes of these variances and update risk response strategies accordingly. This is the best approach because: 1. It addresses the fundamental issue rather than just the symptoms 2. It allows for targeted and effective corrective actions 3. It helps prevent similar variances from occurring in the future 4. It aligns with PMI's emphasis on root cause analysis in risk management The other options are less appropriate because: Analyzing historical patterns and implementing broad cost controls is too general and may not address the specific issues causing the current variance. Documenting variances and calling an emergency stakeholder meeting is reactive and doesn't focus on understanding the underlying problems. Revising the baseline and adjusting future estimates merely adapts to the problem rather than solving it, and could be premature before understanding the root causes.