Common Cause Variation Vs Special Cause Variation

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Aug 21, 2023

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Howmuchever perfection you try to bring into the process, there will always be a little variation. Variance means how the data is distributed about an expected value. A zero variation situation means both results are identical, which is a rare situation. The world of quality management experiences its forms of variation, notably common cause, and special cause variation. Understanding the difference between common cause and special cause variation is like deciphering the ingredients behind the flavors in the baker's creations. Common cause variation implies consistency whereas special cause variation includes the inconsistencies coming in the process. In this blog, we will understand the difference between common cause variation and special cause variation in detail. 

What is Variance?

Variance provides us with an idea of the way data is distributed around an anticipated value or mean. If you have the value of a zero variance means the results are similar which is a rare condition. A high variance indicates that the points of data are separated from one another--and also the mean, whereas a smaller variance indicates that the data points are close to the average. Variance is always non-negative.

Every single piece of data that is measured will show a degree of variation. No, regardless of how hard we make it, we will never achieve identical results for two different situations. Each result will differ even if the difference is small. A variation could be described as "the number used to determine how much individuals within a group differ."

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Types of Variance

When dealing with variations in their work, professionals must confront knowing the decision of when to act and when to not take action. Since if you react to every change in the process and alter the process, it will be an endless process. Dr. Deming called this "tempering the process." In the end, rather than improving the quality, tempering actually, lowers the quality. Deming demonstrated the effects of tempering using the aid of a funnel study.

Variation can be classified into two categories:

  • Common Causes
  • Special Causes

Common Causes

Common Cause Variation refers to the inherent, anticipated variability that occurs naturally in any process. It is caused by the regular interactions between multiple elements within the system and is a contributing factor to the overall stability of the system. This kind of variation is considered to be consistent and predictable since it follows a consistent pattern over time. Common cause variations are similar to the fluctuation of the time a person commutes due to weather, traffic, or other factors that are uncontrollable. While it may cause small variations in the outcome but it is within a safe range and can be managed by making adjustments to the process. Quality control measures are designed at reducing common causes variations by fine-tuning processes and improving overall efficiency. Knowing and dealing with common causes for variations is crucial for maintaining the same quality of service or product while also optimizing operations and ensuring the long-term stability of processes.

Special Causes

Special cause variation refers to the unpredictable fluctuations in a process that are caused by factors outside the usual realm of operation. Unlike common cause variation, which results from inherent but consistent factors within a process, special cause variation arises sporadically due to exceptional circumstances. These circumstances could include equipment malfunctions, sudden changes in the environment, or human errors.

Special cause variation often leads to significant deviations from the norm and can result in outcomes that are far from the expected average. It is characterized by its sporadic nature, as it does not follow a predictable pattern. Identifying and addressing special cause variation is crucial in maintaining process stability and quality. Quality control methods, such as control charts, help to distinguish between common and special causes of variation. By pinpointing the factors responsible for special cause variation, organizations can implement targeted solutions to prevent future occurrences and ensure consistent and reliable process outcomes.

Common Cause Variation Vs. Special Cause Variation

The difference between common cause variation vs. special cause variation is represented below:

AspectCommon Cause VariationSpecial Cause Variation
OriginInherent to the process itselfExternal to the regular process
NatureConsistent and predictableSporadic and unpredictable

Impact on Process

Contributes to natural variationCauses significant deviations
Control and StabilityCan be managed through process improvementRequires specific corrective action
The pattern on Control ChartFluctuates within control limitsExtends beyond control limits
ExampleTemperature variations in a baking processSudden equipment malfunction

 

The two kinds of variations, though connected, possess distinct features that require precise comprehension and effective management. Understanding their distinct characteristics will illuminate their significance in ensuring the stability of processes and improving overall performance.

Origin and Nature:Common cause variation arises from the inherent fluctuations that are an integral element of every process. It is a reflection of the normal variations that result from numerous factors, including minor variations in input conditions, small equipment changes, and personal operator variations. This kind of variation is stable in time and can be seen as a constant background noise that influences the results of processes.

However, the special cause variation results from external factors that aren't part of the normal process conditions. It's sporadic, and usually caused by external factors like sudden breakdowns of equipment or significant environmental changes, or human mistakes. Special cause variations disrupt the normal process flow and can cause deviations that are different from the usual pattern. Because it is not random, it is important to be identified and addressed promptly.

Impact on Process and Stability: Common causes for variation can contribute to the natural spreading of data points within the mean or average of the process. While it could cause small deviations, these variations can be controlled within the parameters of control over the process. Process improvements and optimization can reduce the effects of common cause variations and increase the overall stability of the process.

However, special cause variations can affect the outcomes of the process. It can lead to outcomes that are different from the average and can result in mistakes, defects, or inefficiencies. The unpredictable nature of special cause variations requires immediate attention to avoid it from happening again and to ensure stability.

Control and Management: Controlling common cause variations involves setting limits of control or acceptable ranges in that the procedure is expected to function. Control of the process using statistical (SPC) tools such as control charts, track the process in time to identify patterns and deviations from the expected pattern. By analyzing the data, businesses can tweak processes and ensure the same quality.

To address the issue of special cause variation, it requires an entirely different method. Root cause analysis is designed to determine the exact causes that cause the non-random variations. Once the root cause is identified, corrective measures are taken to either eliminate or minimize its impact. This proactive approach helps prevent future instances of variation due to special causes and increases the reliability of the process.

Visualizing on Control Charts: Control charts are visual representations of variations. In the case of common cause variation data points change within control limits, showing the normal spread. However, in the case of special cause variation, the data points go beyond these limits, which indicates the existence of an unusual influence that is affecting the process.

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Conclusion

If you're looking to increase your knowledge of quality control and process management understanding these variations is an essential aspect, especially in situations like PMP certification training. Like the way a conductor's skill determines the result of a performance, your skill in identifying common causes and special cause variations can have a significant impact on the effectiveness of your process management procedures. If you can master these concepts, you'll be better prepared to optimize processes, identify issues, and produce the smooth results that are expected of PMP-certified professionals.

 

Frequently Asked Questions (FAQs):

What are the most common causes of variation? 

Common cause variation refers to the natural and expected variations in a process that result from everyday events. It helps to explain the natural variation of data points within the process average, and it follows a predictable pattern throughout time.

What is the special cause of variance? 

Special cause variation is caused by external and sporadic elements which cause non-random shifts in the process's outcomes. This can cause deviations that are beyond the normal range and disrupt the flow of the process.

What do common cause variations be controlled? 

Common cause variation can be managed by using techniques for process optimization. The use of statistical process control (SPC) tools such as control charts can help monitor and keep the procedure within a reasonable limit.

What methods are used to address the issue of special cause variation? 

Special cause variation requires root cause analysis to determine the specific causes that cause the variances. Once they are identified, corrective measures can be taken to stop their repetition.

What are these concepts and how do they connect to PMP certification? 

Understanding common cause and special cause variations is essential in project management situations such as PMP certification courses. The knowledge gained from these concepts allows professionals to ensure the stability of processes improve outcomes, and achieve the precision that comes with PMP-certified experts.

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