Tackling special causes

Barb ClearyDo you have data that’s an anomaly or special cause that you want to exclude from your analysis? Do you want the ability to temporarily exclude certain data from your data set analysis? Special causes and outlying data can occur in any data collection process, learn how to easily handle these situations.

If you are calculating and charting average weekly temperature in a room, but find that one night the thermostat has been inadvertently set to 90 degrees, how will that data point affect your average? Clearly, the answer is that it would create a false sense of a higher temperature average for the week, and in effect create a misleading report.

There may be times that it is appropriate to leave out irregular data points such as this one, to be sure, without feeling that you’re “cheating” on the numbers. Additionally, there may be special causes that have been addressed and no longer apply to the calculations, and you’d like to remove these. Or perhaps you’d like to exclude certain pieces of data on a temporary basis, to analyze their effect on the calculations. Having the flexibility to remove or exclude anomaly data from your control chart can help you more easily focus on your process and remove any additional noise from the chart or the calculations.

CHARTrunner Lean SPC charting software, just released version 3.0 offers the option to “cause out” or mark data to be treated as a special cause, providing an easy way to exclude unwanted data from chart calculations so the statistics reflect the process more accurately. While treating data as a special cause can be a complex process in many SPC software packages, CHARTrunner Lean allows you to dynamically make the changes and adjustments right on the screen. The caused data is still visible in “ghosted” form so that it can be used for storytelling, discussion, and understanding about the underlying process. The benefit of this approach is that you don’t have to find the data source and record that needs to be caused. Simply highlight the sample(s) and select cause. Maybe the best feature from a traceability perspective is that the excluded data remains in the source data; however it is not included in the charted SPC calculations.


Annotate and “ghost” special cause data dynamically on the control chart.

“Cause out data” is only one of the features offered in the latest release of CHARTrunner Lean, which has been improved to streamline the charting workflow and analysis process, to improve the ease and functionality of the software. The addition of g-charts and t-charts, for example, supports analysis of rarely occurring events, and a three-step Chart Wizard assistant enhances the ease of creating charts. Other helpful SPC charting features include:

  • Inclusion of sum chart, average charts;
  • Group and sampling;
  • Creation of chart templates;
  • Support for stored procedures and query parameters;
  • Improvement in filtering options;
  • Support for SQL Server and Oracle

…and more. Find out how the newest advantages of CHARTrunner Lean can help demonstrate proof of quality in your organization. See these features for yourself  or request a free 30-day software trial, or attend a free web demo.

One thought on “Tackling special causes

  1. I have downloaded the 30-day trial version and had a question about ‘causing out’ data points. Are you only able to ’cause out’ data points if your chart is based on a certain type of data source? I have a chart built on a Microsoft Access View and the tool doesn’t provide the ability to ’cause out’ data points. However, another chart is built on Microsoft Excel data and the tool allows this data to be ’caused out’. Thanks.

Comments are closed.