Variance Analysis

Variance Analysis

Introduction: Why This Matters

Variance analysis is a core project management technique used to measure performance by comparing planned results against actual results. It helps project managers understand whether the project is ahead or behind schedule, under or over budget, and within or outside of quality thresholds.

On the PMP exam, variance analysis frequently appears in questions related to monitoring and controlling project work, earned value management, and identifying the causes of deviations. In real-world projects, it is a vital tool for keeping projects on track and taking corrective actions early.

Purpose and Objectives

Primary Purpose: To evaluate deviations between baseline plans and actual results to guide corrective and preventive actions.

Key Objectives:

• Measure project performance against baselines.
• Identify cost, schedule, or scope deviations.
• Investigate the reasons for variances.
• Support decision-making on corrective or preventive actions.
• Use variance analysis as part of earned value management (EVM).

Overview

Variance analysis compares baseline expectations to actual performance, then turns those differences into insight and action.

• Baselines: Cost, schedule, and scope baselines provide the “plan” for comparison.
• Actuals: Work performance data tells you what is happening in real time.
• Variance values: Quantify deviation and trigger deeper analysis when thresholds are exceeded.

Characteristics

• Baseline-driven: Meaningful only when baselines are accurate and controlled.
• Quantifies deviation: Shows how far off you are (cost, schedule, scope, or quality).
• Action-oriented: Supports corrective actions, preventive actions, and forecasting.
• EVM-compatible: Often paired with earned value management metrics (CV, SV, CPI, SPI).
• Threshold-aware: Not every variance is a fire. Know what requires action.

Practical Example

Context: In a construction project for a new terminal at an international airport, the project manager performed variance analysis to evaluate cost and schedule performance.

Activities:

• Measured current performance: PV = $10M, EV = $9M, AC = $11M.
• Calculated schedule variance: SV = EV – PV = $9M – $10M = -$1M (behind schedule).
• Calculated cost variance: CV = EV – AC = $9M – $11M = -$2M (over budget).
• Investigated and responded: Escalated early, renegotiated contractor timelines, and implemented cost controls.

Outcome: The manager identified schedule and cost problems early enough to take corrective action before the overruns became unrecoverable.

Common Pitfalls

Analysis Without Meaning

• Pitfall: Focusing only on variance numbers and not the causes.
• Prevention: Pair variance analysis with root cause analysis before selecting actions.

Weak or Missing Baselines

• Pitfall: Failing to use baselines or using outdated baselines.
• Prevention: Maintain approved baselines and follow change control when updates are needed.

Timing and Overreaction

• Pitfall: Delayed reporting reduces options. Overreacting to small variances wastes time and energy.
• Prevention: Report frequently, and use thresholds to decide when action is required.

Quick Recap Table

Key Takeaways

• Variance analysis measures performance against approved baselines.
• Key EVM variance metrics include CV and SV, and performance indexes include CPI and SPI.
• Variances provide early warning signs so you can act before problems grow.
• On the PMP exam, focus on whether the variance is favorable or unfavorable and what action it should trigger.

Next Step

Having covered variance analysis, we now move to the next data analysis technique: SWOT Analysis.

Bibliography

Project Management Institute. (2021). A Guide to the Project Management Body of Knowledge (Project Management Body of Knowledge Guide) (7th ed.). Project Management Institute.