{"id":212185,"date":"2024-09-12T09:16:54","date_gmt":"2024-09-12T16:16:54","guid":{"rendered":"https:\/\/clickup.com\/blog\/?p=212185"},"modified":"2026-01-21T12:50:17","modified_gmt":"2026-01-21T20:50:17","slug":"control-charts-in-project-management","status":"publish","type":"post","link":"https:\/\/clickup.com\/blog\/control-charts-in-project-management\/","title":{"rendered":"How to Use Control Charts in Project Management (With Examples)"},"content":{"rendered":"\n

In the 1900s, canaries were used as sentinels in coal mines. When carbon monoxide\u2014undetectable to human beings\u2014reached dangerously high levels, the birds stopped singing. This served as a timely warning, giving the miners enough time to escape. <\/p>\n\n\n\n

Control charts are like canaries. When everything is under control, the control chart, which is a graph plotting quantitative measures against time, will present a non-threatening picture. Unexpected variations or extraordinary deviations that threaten your project will set alarm bells ringing.<\/p>\n\n\n

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First developed in 1924 by Walter A. Shewhart<\/a>, control charts were used to differentiate between random variation\u2014which is normal\u2014and disruptive variation in the manufacturing process for telecommunications equipment at Bell Labs. Today, these charts are used in quality control, healthcare, R&D, and service industries.\u00a0<\/p>\n\n\n<\/div>\n\n\n

Project Management Professionals (PMPs) use them for quality management and process control. They help monitor performance, identify special-cause variations, and ensure project managers can take corrective action to keep variation within predefined limits. In the long term, they serve as a tool to drive continuous improvement and data-driven decision-making. <\/p>\n\n\n\n

This article explains the use of control charts in project management with examples describing real-world scenarios. Let\u2019s see how they can help you build proactive rather than reactive project management strategies and stay one step ahead.<\/p>\n\n\n\n

Understanding Control Charts<\/h2>\n\n\n\n

A control chart<\/strong>, also called a statistical process control (SPC) chart or Shewhart chart<\/strong>, is a powerful graphical tool designed to monitor and maintain control over process quality and project execution<\/a>. It ensures that operations proceed under stable, consistent conditions, helping to maximize efficiency and maintain the overall flow of your business.<\/p>\n\n\n

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Example 1:<\/strong> Let\u2019s say the school bus is meant to arrive at your doorstep at 7:00 AM every morning. Some days it\u2019s a bit late, others it\u2019s a little early. Either way, it reaches school before the morning bell rings, so you aren\u2019t too worried.<\/em>\u00a0<\/p>\n\n\n<\/div>\n\n

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Control chart showing school bus arrival times. There\u2019s some variation, but not too much<\/figcaption><\/figure><\/div>\n\n\n

Now, what happens if one day, the bus arrives 20 minutes early? Or 20 minutes late? That’s a large variation from the usual routine and one that will severely disrupt your own morning schedule. <\/p>\n\n\n\n

So, the basic idea behind control charts is that every process involves variations, but only some of these variations result in catastrophic failure. <\/strong>By visually tracking all process variations, a control chart can help identify variations and address issues in projects early. This proactive approach supports a smoother, more reliable business operation.<\/p>\n\n\n\n

Every control chart contains five elements<\/strong>.<\/p>\n\n\n\n