SPC is an accessible statistical approach to resolving problems and finding solutions. It can be used throughout the lifecycle of a project to assess performance and progress
It is a type of run chart showing performance over time with upper and lower limits to indicate the levels of variation.
S – Statistical: some statistical concepts used to help us understand processes
P – Process: we deliver our work through processes. i.e. how we do things
C – Control: predictable
Interpreting an SPC chart
There are four rules that help you identify what the system is doing. If one of the rules has been broken, this means that ‘special cause ‘ variation is present in the system. It is also perfectly normal for a process to show no signs of special cause. This means that only ‘common cause ‘ variation is present.
Rule 1 = Any point outside the control limits
Rule 2 = Seven consecutive points all above or all below the centre line, or all increasing or decreasing:
Rule 3 = Unusual pattern or trends within the control limits:
Rule 4 = Number of points inside middle third of the region between the control limits differs markedly from two -thirds of the total number of points:
The goal is to reduce the variation to create a more efficient system.
Common causes and special causes of variation indicate the need for two different types of improvement which can help you achieve this. See Deming’s System of Profound Knowledge.
If controlled variation (common cause) is displayed in the SPC chart, the process is stable and predictable, which means that the variation is inherent in the process and the system will need to be changed.
If uncontrolled variation (special cause) is displayed in the SPC chart, the process is unstable and unpredictable.
Variation may be caused by factors outside the process. In this case, you need to identify these sources and resolve them, rather than change the system itself.
Things to consider
- You should not react to special cause variation by changing the process, as it may not be the system at fault.
- You should not ignore special cause variation by assuming that its part of the process. It is usually caused by outside factors which you need to understand in order to reduce them.
- You should ensure that the chart is not comparing more than one process and displaying false signals.
- An example of this would be data covering two hospital sites or two procedures that are very different.
- SPC is a tool that will help you understand the scale of any problem (the degree of variation) and identify possible causes when used with other investigative tools, eg process mapping. You are then able to measure the impact of any improvement: does it cause more variation?
- Institute for Healthcare Improvement: Statistical process control as a tool for research and health care improvement