Control Charts trong luyện thi PMP PMI-RMP
Control charts gather data to show when a process experiences an out of control condition. These are called “[wc_highlight color=”yellow”]Special Cause Variations[/wc_highlight]”. Basically we will use the control chart to determine whether a process is stable with predictable performance or not. It helps us understand how a process performs/behaves over time. Ideally we would expect a process to be stable and consistent and the control chart can help us confirm the same.
A typical control chart has 3 lines:
a. The Mean or Median line
b. The Upper Control Limit or UCL (Specification limits – customer’s expectation)
c. The Lower Control Limit or LCL (Control limits: +/- 3 Sigma)
Data points are gathered and plotted within these 3 lines. If all your data points lie between the UCL and the LCL then you can safely assume that your process is “In Control”. Every process will always have some variance and it is inevitable but, as long as all our data points lie within the control limits then we are good. If you see no variance and all points lie on the median, then either the data collection was wrong or something else is majorly wrong which is yet to be identified. There is no way that all data points lie on the median line.
The difference between the UCL/LCL and the mean is called the sigma value of the project. In other words it signifies the level of quality in the project. Don’t worry too much about sigma right now. Just know that higher the quality the better it is. If you are really keen on understanding about Sigma values and better quality, to visit the blog on Lean Six Sigma quality improvements.
Spotting a process that is out of control (cases where the data points are either above the UCL or below the LCL) is critical. There could also be cases where all data points are within the UCL and LCL but still the process is out of control. Those cases are identified using the “Rule of 7” wherein if 7 consecutive points fall on the same side of the control chart then it suggests that something is wrong and needs to be investigated.
Look at the sample control chart above. There is a data point above the UCL and one below the LCL which signifies that this process id definitely out of control. By analyzing the control chart we can identify potential risk points. If a process is in control then practically speaking we need not do anything. But, if it is out of control then we definitely need to take remedial actions.
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