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Understanding Statistical Process Control
Statistical Process Control, often shortened to SPC, can be described as a philosophy, a strategy, and a practical set of analytical tools designed to improve processes and systems.
The American Society of Quality (ASQ) defines SPC as "the use of statistical techniques to control a process or production method. Statistical Process Control tools and procedures can help you monitor process behaviour, discover issues in internal systems, and find solutions for production issues".
In simple terms, SPC involves plotting data over time on charts to help organisations understand what normal variation looks like, and when something unusual is happening that requires action.
By distinguishing between common and abnormal variation, SPC helps teams respond appropriately, rather than reacting to noise or missing genuine signals for improvement.
Statistical Process Control is widely used to monitor and predict process performance, identify opportunities for improvement, and assess whether changes lead to sustained success over time.
The Origins of Statistical Process Control
Statistical Process Control was developed by physicist Walter A. Shewhart while working at Bell Labs. His work focused on understanding variation in data and, critically, separating common causes of variation from special causes.
Shewhart introduced the control chart as a way of determining whether a process was statistically stable, which is where the term Statistical Process Control originates.
Early control charts helped identify unusual patterns or extreme values in data that suggested something in the process had changed. Over time, SPC evolved to include a range of chart types, each suited to different kinds of data and processes.
A well-known historical use of SPC was during the Second World War, when it was used in the United States to maintain quality in the production of munitions and other critical military supplies. Although its use declined briefly after the war, SPC gained renewed momentum in the 1980s and has since been widely adopted across many industries worldwide.
Why SPC Still Matters Today
Today's organisations face increased competition, rising operational costs, and growing pressure to do more with limited resources. Having robust tools to understand, monitor, and improve processes is essential.
The primary aim of Statistical Process Control is to support continuous improvement by using data and statistical methods to guide decision-making. SPC enables leaders to understand what their data is genuinely telling them and take action with confidence, rather than relying on assumptions or one-off snapshots.
Unlike traditional quality control approaches that focus on fixing problems after they occur, SPC helps organisations detect issues early and prevent them from happening in the first place.
While SPC is often associated with manufacturing and healthcare, including the NHS where its impact has been particularly significant, its application goes far beyond these sectors.
In practice, any organisation with measurable processes can benefit from using Statistical Process Control to improve performance, quality, and outcomes.
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