Quality Control Measurements

Recorded outputs from performing Control Quality that show how products or processes actually performed against defined quality metrics.

Key Points

  • They are the output of the Control Quality process and capture actual inspection and test results.
  • Values may be numeric (e.g., defect counts, dimensions) or categorical (e.g., pass/fail) and are traceable to specific quality metrics.
  • They feed Manage Quality and analysis tools (e.g., trend charts) to drive process improvements and corrective actions.
  • They are stored as project records to support decisions, change requests, and lessons learned.

Example

On a software project, the team runs system tests and logs 38 defects with severity levels, pass/fail rates for 250 test cases, and response time measurements versus targets. These logged figures are the quality control measurements used to assess compliance and to plan fixes.

PMP Example Question

Which artifact should the project manager review to see the actual results from inspections and tests performed during Control Quality?

  1. Quality control measurements
  2. Quality metrics
  3. Quality management plan
  4. Verified deliverables

Correct Answer: A — Quality control measurements

Explanation: Quality control measurements contain the documented results from Control Quality. Metrics define targets, the plan explains the approach, and verified deliverables are items that passed inspection.

AI for Project Managers — Build Plans Faster, Lead Better

Turn messy inputs into structured project plans in minutes. If you are a project manager tired of spending hours on documentation, this course shows you how to use AI to work faster while staying fully in control.

This is not a generic AI course. You will learn how to use AI as a practical co-pilot to build real project artifacts—charters, WBS, schedules, risk registers, and executive reports—using structured, reliable prompt frameworks.

You will also learn how to keep your project aligned across scope, schedule, cost, and risk, and how to interpret performance data like Earned Value Management to support better decisions and communication.

Everything is designed for immediate use. You get ready-to-use prompt templates and workflows you can apply right away in your projects. Watch the video to see how it works and start building your first AI-supported project plan.

Explore the Course


Stop Managing Admin. Start Leading the Future!

HK School of Management helps you learn AI prompt engineering for project work. Move beyond status reports and risk logs with practical prompt frameworks for everyday tasks. Practical skills, tools, and guidance you can apply right away. Covered by Udemy's 30-day refund policy.

Enroll Now