Control Chart in Tableau

A Control Chart is a statistical chart used to monitor process performance over time and identify variations that fall outside acceptable limits. It helps distinguish between normal variation and special-cause variation by using upper and lower control limits. They are useful for:

• Identifying outliers and abnormal trends
• Monitoring the stability of a process over time
• Understanding variation using standard deviation
• Visualizing upper and lower control limits
• Supporting data-driven decision-making

Creating a Control Chart

Tableau does not provide a direct Control Chart option, but it can be created using table calculations, parameters and a dual-axis setup.

Note: For this article, a sample dataset "vgsales.csv" is used, to download click here.

Step 1: Create the Base Line Chart

Drag the Year field to the Columns shelf and drag Global_Sales to the Rows shelf.

Step 2: Create Parameter for Standard Deviation Level

1. Click the drop-down arrow in the Data pane and select Create Parameter.

2. Configure the parameter as follows:

• Name: Level_of_SD_z
• Data Type: Integer
• Allowable Values: List
• List of Values: 1, 2, 3
• Click OK.

Step 3: Create Upper Bound (UB)

1. From the Data pane drop-down, select Create Calculated Field and name the field UB.

2. Enter the following formula:

WINDOW_AVG( SUM( [Global_Sales] ) ) + ( [Level_of_SD_z] * WINDOW_STDEV( SUM( [Global_Sales] ) ) )

Step 4: Create Lower Bound (LB)

Again select Create Calculated Field and name the field LB. Enter the following formula:

WINDOW_AVG( SUM( [Global_Sales] ) ) - ( [Level_of_SD_z] * WINDOW_STDEV( SUM( [Global_Sales] ) ) )

Step 5: Identify Outliers

Create another calculated field and name it Outliers and enter the following condition:

SUM( [Global_Sales] ) < [LB] OR SUM( [Global_Sales] ) > [UB]

Step 6: Configure Measure Values

Drag Measure Values to the Marks card and in the Measure Values shelf, keep only LB and UB

Remove all other measures.

Step 7: Create Dual Axis

Drag Measure Values to the Rows shelf and right-click the second axis and select Dual Axis.

Step 8: Add Central Line (CL)

Create a new calculated field named CL and enter the formula:

WINDOW_AVG( SUM( [Global_Sales] ) )

Drag CL into Measure Values.

Step 9: Synchronize Axes

Right-click on the Value axis and select Synchronize Axis.

Step 10: Highlight Outliers

1. In the Global_Sales Marks card, drag Outliers to the Color shelf.

2. Click Edit colors: False -> Green and True -> Red.

Step 11: Show Parameter Control

Go to the Parameters pane right-click Level_of_SD_z and select Show Parameter.

Step 12: Adjust Control Limits

Change the Level_of_SD_z value to:

• 1 for tighter limits
• 2 for moderate limits
• 3 for wider limits

Final Output

The final Control Chart displays:

• A central average line (CL)
• Upper and lower control limits (UB & LB)
• Sales trends over time
• Outliers highlighted clearly in red
• Interactive control using standard deviation levels

This chart is ideal for monitoring stability, detecting anomalies and analyzing process behavior over time.