Level: Intermediate

I have had a couple of requests for help during my live training classes and online training classes on how to build a Six Sigma Control Chart. Now I am not professing to be a Six Sigma black belt, but I do know how to write DAX and I do know how to use Power BI. So here goes. This is what I am going to build.

## The Method

As usual, I used the Adventure Works database in this article. I then used DAX formulas and Power BI visuals to arrive at this six sigma chart. Here are the steps I followed to produce the result.

1. I created a DAX formula for total sales.

Total Sales = SUM(Sales[ExtendedAmount])

2. Then I created a DAX formula to obtain the mean (average) of the sales by day.

Average Sales = CALCULATE( AVERAGEX('Calendar',[Total Sales]), ALLSELECTED('Calendar'))

Note that I used AVERAGEX function iterating over the Calendar table in order to get the average sales over the selected days instead of the average per transaction.

3. Next I calculated the LCL and UCL by adding/subtracting one standard deviation, as follows.

Std Dev = CALCULATE(STDEVX.P('Calendar',[Total Sales]), ALLSELECTED('Calendar')) LCL = [Average Sales] - [Std Dev] UCL = [Average Sales] + [Std Dev]

4. I then created a combo chart – the lines show the average and control limits (LCL and UCL) and the columns show the total sales values. I used a slicer to filter the time period.

The idea is to create an interactive dynamic chart that displays sales distribution over the selected time period. The part of the columns below LCL, above UCL, and between LCL and UCL are to be displayed with different colours. To get this, I had segmented the columns with the following DAX formulas.

Part Lower Bar = IF([Total Sales] <[LCL],[Total Sales]) Full Lower = IF([Total Sales] >=[LCL],[LCL]) Middle = IF([Total Sales] > [LCL] && [Total Sales] <=[UCL], [Total Sales]-[LCL], if([Total Sales] >[LCL],[UCL] - [LCL])) Upper = IF([Total Sales] >[UCL],[Total Sales]-[UCL])

To understand how I arrived at each of these DAX formulas that resulted in the interactive six sigma control chart as given at the beginning of this article, view the following video.

Very clever. The average sales over selected time calculation is an often used formula for many business scenarios. I’ve seen it more usually applied with percentage growth/decline calculations to identify entities that are above the average and those that pull the average down (and require further attention).

This will be useful in testing boundaries of inventory levels.

I’ll give it a try. Thanks Matt.

Very interesting. thanks Matt

This would not be considered an acceptable method of creating control limits for an x bar chart. Nor would the use of a bar chart be a good choice for identifying trends and assignables causes that’s aren’t single movements beyond the control limits (something that’s going to happen quite regularly with a 1s limit).

Or you could use this XmR custom visual: https://github.com/tcd1nc/PowerBI-Control-Chart

Nifty, thanks.

Amazing!