Special Cause Variation: Difference between revisions
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'''Special Cause Variation''', also known as assignable cause variation, is the fluctuation that is caused by known but unpredictable factors, resuling in a non-random distribution ([[Normal Distribution]]) of output data <ref name="scvdfntn>{{cite web | title = Special Cause Variation | url = http://www.isixsigma.com/dictionary/Special_Cause_Variation-336.htm | accessdate = 2006-11-10}}</ref>. It can be identified using [[Statistical process control]] and will usually show up in a [[Control chart]] as outlier samples (i.e., exceeding the lower or upper control limit) or as a systematic pattern (run) of adjacent samples. It will also affect the calculation of the chart specifications (center line and control limits). Unlike [[Common Cause Variation]], special causes of variation can be eliminated by reacting to individual variations. |
'''Special Cause Variation''', also known as assignable cause variation, is the fluctuation that is caused by known but unpredictable factors, resuling in a non-random distribution ([[Normal Distribution]]) of output data <ref name="scvdfntn>{{cite web | title = Special Cause Variation | url = http://www.isixsigma.com/dictionary/Special_Cause_Variation-336.htm | accessdate = 2006-11-10}}</ref>. It can be identified using [[Statistical process control]] and will usually show up in a [[Control chart]] as outlier samples (i.e., exceeding the lower or upper control limit) or as a systematic pattern (run) of adjacent samples. It will also affect the calculation of the chart specifications (center line and control limits). Unlike [[Common Cause Variation]], special causes of variation can be eliminated by reacting to individual variations, and has to be removed before dealing with [[Common Cause Variation]]. |
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== How to Respond == |
== How to Respond == |
Revision as of 09:03, 10 November 2006
Special Cause Variation, also known as assignable cause variation, is the fluctuation that is caused by known but unpredictable factors, resuling in a non-random distribution (Normal Distribution) of output data [1]. It can be identified using Statistical process control and will usually show up in a Control chart as outlier samples (i.e., exceeding the lower or upper control limit) or as a systematic pattern (run) of adjacent samples. It will also affect the calculation of the chart specifications (center line and control limits). Unlike Common Cause Variation, special causes of variation can be eliminated by reacting to individual variations, and has to be removed before dealing with Common Cause Variation.
How to Respond
It is not difficult to deal with special causes if they are spotted early. Tracking down special causes relies heavily on people's memories of what made that occurrence different from all the others. People may quickly forget any unusual circumstances that may have triggered the unusual variation.
When a special cause is spotted, do the following step by step:
- Control any damage or problems with an immediate, short-term fix. Be careful not to view this fix as a permanent solution.
- Once a quick fix is in place, search for the root causes by asking 5 Whys which is one of the techniques in Six Sigma technology usually to dealing with Common Cause Variation.
- If one of the answers gernerated from 5 Whys is "don't know", then Cause-and-Effect diagram (Ishikawa diagram) may be employed. Other methodologies which are used for seeking root causes include:
- Kepner and Tregoe method [2].
- Eight Disciplines Problem Solving
- R.I.S.E (WDP Consulting) [3].
- Once the root cause is discovered, apply the following tools stepwise to remove the variations and develop a longer-term remedy.
- Problem Profile Analysis
- Differences and Changes
- Test Matrix
- Selection Analysis
- Planning and Problem Prevention
Most special causes have a negative impact on the output of the process and need to be removed. Occasionally, a special cause can have a positive impact depending on the nature of the process. If this is the case, finds ways to capture and integrate it into the system.
How to Avoid
Spcial Cause Variation can be avoided by
- Changing the process to accommodate the special cause. This usually adds cost and bureaucracy.
- Blaming individuals soly. Not only does everyone makes mistakes, but also chances are that the problem would have occurred regardless of individuals involved.
- Exhorting workers to simply "do better." Most people, excetp for elites, can only do as well as the system allows them to do.
References
- ^ "Special Cause Variation". Retrieved 2006-11-10.
- ^ "Kepner and Tregoe method". Retrieved 2006-11-10.
- ^ "Problem Solving (RISE)". Retrieved 2006-11-10.