A method that integrates scope, schedule, and cost to measure project performance against the plan.
Earned Value Management is an integrated performance technique that combines scope, schedule, and cost into three core values: Planned Value (PV), Earned Value (EV), and Actual Cost (AC). From these you derive Schedule Variance (SV = EV − PV), Cost Variance (CV = EV − AC), Schedule Performance Index (SPI = EV/PV), and Cost Performance Index (CPI = EV/AC); below 1.0 signals trouble, above 1.0 efficiency. On the exam, recognize that Estimate at Completion has multiple forms — EAC = BAC/CPI assumes current efficiency continues, while EAC = AC + ETC rebuilds the remaining estimate — so match the formula to the scenario’s assumptions rather than memorizing one version.
The authorized budget assigned to the work scheduled to be completed by a point in time.
Planned Value (PV) is the authorized budget assigned to the work scheduled to be completed by a specific point in time. It represents the “time-phased baseline” — how much work, in dollar terms, the approved schedule says should be done by today. PV is also called the Budgeted Cost of Work Scheduled (BCWS) in older literature, and at project completion it equals the Budget at Completion (BAC).
The exam frequently tests the distinction between PV and Earned Value (EV). PV measures what was planned to be complete; EV measures what was actually accomplished, valued at the same planned rates. Schedule Variance (SV = EV − PV) and Schedule Performance Index (SPI = EV ÷ PV) both use PV as the baseline, so misidentifying PV in a scenario will cascade into wrong SV and SPI answers.
The budgeted value of the work actually completed at a point in time.
Earned Value (EV) is the budgeted cost of work physically completed at a given point. Expressed in dollars, it is calculated as EV = BAC × % complete, making it the central variable in Earned Value Management. EV feeds Schedule Variance (SV = EV − PV), Cost Variance (CV = EV − AC), the Schedule Performance Index (SPI = EV / PV), and the Cost Performance Index (CPI = EV / AC). EV measures work done against budget, not against what was actually spent — confusing it with Actual Cost is the common mistake. A project can run EV above AC (under budget) yet EV below PV (behind schedule), so always evaluate both variances together.
The real cost incurred for the work completed at a point in time.
Actual Cost (AC) is the total expenditure incurred for work performed on a project activity or work package during a specific time period. It is one of the three core Earned Value Management (EVM) inputs, alongside Planned Value (PV) and Earned Value (EV), and feeds directly into the Cost Variance (CV = EV − AC) and Cost Performance Index (CPI = EV ÷ AC) calculations used to assess cost efficiency.
The critical distinction to remember is that AC measures money spent, not work accomplished. A project can have a high AC while still being behind schedule if the earned value is lower — spending more does not mean more work is done. Exam questions often pair AC with EV to test whether candidates can correctly read a negative CV or a CPI below 1.0 as an over-budget condition rather than a schedule problem.
A measure of cost efficiency calculated as earned value divided by actual cost.
The Cost Performance Index (CPI) measures cost efficiency, calculated as CPI = Earned Value (EV) ÷ Actual Cost (AC). A CPI of 1.0 means spending exactly as planned; below 1.0 signals a cost overrun; above 1.0 means work is costing less than budgeted. On the exam, CPI forecasts the Estimate at Completion via EAC = BAC ÷ CPI, assuming current efficiency continues. Don’t confuse CPI with SPI (EV ÷ PV): AC measures money spent while PV measures planned value, so a project can be over budget (CPI < 1) yet ahead of schedule (SPI > 1).
A measure of schedule efficiency calculated as earned value divided by planned value.
Schedule Performance Index (SPI) is an Earned Value Management metric that quantifies schedule efficiency using the formula SPI = EV ÷ PV, where EV is Earned Value and PV is Planned Value. A result of 1.0 means the project is exactly on schedule; below 1.0 signals schedule slippage, and above 1.0 means the team is ahead of plan. The key exam distinction is between SPI and CPI (Cost Performance Index). Both use EV in the numerator, but CPI divides by AC (Actual Cost) to measure cost efficiency, while SPI divides by PV to measure time efficiency. A project can have a healthy CPI yet a poor SPI, so always evaluate both together.
A document that records identified risks, their analysis, and planned responses.
The risk register is the primary artifact for capturing individual project risks, populated when risks are identified and serving as the repository for all risk information across the project. It records each risk’s description, category, root cause, probability and impact ratings, owner, planned response strategy, and any residual or secondary risks. Because it is updated through qualitative analysis, quantitative analysis, response planning, and monitoring, it is a living document. A common exam trap is confusing it with the risk report, which summarizes overall project risk exposure rather than listing individual risks. New risks found during execution are added immediately.
Prioritizing risks by assessing their probability and impact, usually on a relative scale.
Qualitative Risk Analysis prioritizes individual project risks by assessing each one’s probability of occurrence and its impact on objectives, using relative, descriptive scales rather than numeric data. Its signature tool, the probability and impact matrix, maps each risk to a composite score that guides where response resources go. The process updates the risk register with prioritized risks, watchlists for low-priority items, and risks flagged for further analysis. On the exam, remember qualitative always precedes quantitative analysis, which assigns statistical or financial values to the highest-priority risks and is not mandatory on every project.
Numerically analyzing the combined effect of risks on project objectives.
Quantitative risk analysis assigns numerical probability and impact values to risks, then models their combined effect on objectives such as cost and schedule. Common techniques include Monte Carlo simulation, which runs many scenarios to produce a probability distribution of outcomes, and Expected Monetary Value (EMV), which multiplies a risk’s probability by its monetary impact and underpins decision tree analysis. Qualitative analysis prioritizes risks subjectively; quantitative analysis digs deeper into those high-priority risks to gauge the likelihood of meeting targets and the contingency reserve needed. It is optional on many projects.
The total cost of conformance (prevention and appraisal) and nonconformance (failures) related to quality.
Cost of Quality (COQ) sorts all quality-related spending into the cost of conformance — prevention (training, documentation, audits) plus appraisal (testing, inspections) — and the cost of nonconformance — internal failures (rework, scrap found before delivery) plus external failures (warranty, liability, lost business after delivery). Conformance costs are proactive investments; failure costs are reactive losses. PMBOK favors shifting spend toward prevention because defects caught late, especially after the customer has the product, cost far more. On the exam, classify carefully: rework is always an internal failure cost, not a prevention activity.
A graph that shows whether a process is stable and within acceptable control limits over time.
A control chart is a statistical quality tool used during the Control Quality process to monitor whether a process is performing within established limits over time. It displays a center line (the mean), an upper control limit (UCL), and a lower control limit (LCL), typically set at plus or minus three standard deviations from the mean. Data points within those limits and showing no non-random patterns indicate a process in statistical control.
The critical exam distinction is between common cause variation — natural, random fluctuation inherent to any process — and special cause variation, which signals an assignable, abnormal factor that must be investigated. Points outside the control limits always indicate special cause variation, but non-random patterns within the limits can too, which is where the rule of seven applies. Control limits are NOT the same as specification limits; specification limits reflect customer requirements and are set externally, while control limits are derived from the process data itself.