![](https://www.thedataschool.co.uk/content/images/2025/01/image-34.png)
A control chart in Tableau is used to monitor the stability of a process over time. This can be applied to monitoring the stability of a process or assessing quality control. It can also be used in sports to monitor the consistency of performance over time.
It typically involves a line chart with two reference lines which represent the upper standard deviation and the lower.
A standard deviation tells a reader how spread out the values are from the mean (average). The upper and lower control limits in the chart are normally set to 1 so therefore a user would be able to see how far something is straying from the mean or if the process is stable/consistent.
How to build a control chart
Step 1: Drag a time dimension to columns and a measure to rows
Optional Step 2: Duplicate the measure and change the marks to circles.
![](https://www.thedataschool.co.uk/content/images/2025/01/image-35.png)
Then right click on axis and click dual axis and synchronise. You can then hide this axis.
Step 3: Drag distribution lines onto view/chart
![](https://www.thedataschool.co.uk/content/images/2025/01/image-37.png)
Step 4: Select standard deviation from value drop down
![](https://www.thedataschool.co.uk/content/images/2025/01/image-36.png)
Change colour of lines depending on stability
To change the colour of the dots depending on if they are outside the standard deviation then create 3 calculations
Step 1: Create an upper standard deviation calculation
e.g WINDOW_AVG(avg([measure])) + WINDOW_STDEV(avg(measure))
Step 2: Create a lower standard deviation calculation
e.g WINDOW_AVG(avg([measure])) - WINDOW_STDEV(avg(measure))
Step 3: Create an if statement to determine if 0ver or above its false else true
if avg(measure)> [Window Standard +] then FALSE
ELSEIF AVG([Casualty Age]) < [Window Standard -] THEN FALSE
ELSE TRUE END
Step 4: Drag to marks card
![](https://www.thedataschool.co.uk/content/images/2025/01/image-38.png)