During the second year of a three-year digital-modernization program at a financial-services firm, the weekly earned-value dashboard shows the cumulative Cost Performance Index (CPI) slipping from 0.97 to 0.93 over the last four reporting periods. The executive sponsor asks whether this decline is a random fluctuation or an early warning that final program costs could exceed the approved funding cap.
To answer, the program manager gathers CPI values from every prior reporting cycle, plots them on a control chart, calculates the slope of the line, and extrapolates the trajectory to estimate the most probable CPI at completion if current conditions persist.
Which analytical technique is the program manager using to develop this forward-looking projection?
The program manager is conducting trend analysis. By charting historical CPI values across successive reporting intervals and projecting the line forward, they identify performance patterns that can predict future cost outcomes.
Root cause analysis digs into why a specific variance occurred but does not by itself forecast future performance.
Monte Carlo simulation models a range of possible results based on probability distributions rather than observed trends.
Variance analysis examines the magnitude of cost or schedule deviations at a single point in time; it does not plot the pattern of those deviations across multiple periods to anticipate future results.
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PgMP
Strategic Program Alignment
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