In the world of process management and quality control, the ability to differentiate between two types of variation—common cause variation and special cause variation—is crucial for improving processes and maintaining consistent quality. Recognizing and addressing these types of variation ensures that a company can maintain efficiency, reduce waste, and enhance overall product or service quality. This article explores the differences between common and special cause variation, explains their implications for business processes, and provides examples to help you better understand these concepts.
What is Variation in Process Management?
Variation refers to the differences observed in the outcome of a process over time. Every process experiences some level of variation, even under the best conditions. Understanding the sources of variation is key to controlling and improving processes. Variations can be broken down into two categories: common cause variation and special cause variation.
Common Cause Variation: The Natural Variation
Common cause variation is the variation that occurs naturally within a process. It represents the inherent fluctuations that happen during normal operation. This type of variation is often due to factors that are consistently present but not easily controlled, such as minor machine vibrations, slight fluctuations in material properties, or the everyday performance of human operators. Common cause variation is expected and can be modeled as part of the system’s natural behavior.
Characteristics of Common Cause Variation
- Stable and predictable: Common cause variation is consistent over time and predictable within certain limits.
- Systemic: The causes of common cause variation are typically embedded within the process itself. These causes are constant unless changes are made to the system.
- No immediate action required: Since this variation is inherent to the process, it does not usually indicate a need for corrective action. However, it is often an opportunity to improve the process by reducing or eliminating unnecessary sources of variation.
Examples of Common Cause Variation
- Temperature Fluctuations: In a factory, slight temperature changes in the manufacturing environment can cause small variations in the products’ physical properties.
- Operator Performance: Even highly trained workers will naturally exhibit slight performance variations from one cycle to the next, due to factors such as fatigue or attention levels.
- Machine Wear: Over time, machines will show small, predictable fluctuations in their performance as they wear, even under normal conditions.
| Source of Variation | Example | Nature |
|---|---|---|
| Machine Operation | Slight variations in machine speed | Predictable fluctuations |
| Operator Performance | Minor differences in speed or precision | Consistent over time |
| Material Properties | Variations in raw material thickness | Expected, within limits |
| Environmental Conditions | Temperature or humidity changes | Ongoing, natural changes |
Special Cause Variation: The Unpredictable Variation
Special cause variation, also called assignable cause variation, is variation that arises from an unexpected or unusual event that disrupts the normal process. This type of variation is not inherent to the process and typically occurs due to an external factor, which causes the process to behave abnormally. Special cause variation signals that something has gone wrong or that a change has occurred in the system.
Characteristics of Special Cause Variation
- Unpredictable and irregular: Special cause variation is sporadic and does not follow the same pattern over time. It occurs due to external factors that are not part of the regular process.
- Assignable causes: Special causes can usually be traced to a specific event or change, such as a machine malfunction, human error, or a change in material properties.
- Requires corrective action: Since this variation is outside the expected behavior of the process, it often requires investigation and corrective action to bring the process back to stability.
Examples of Special Cause Variation
- Machine Breakdown: A critical piece of equipment breaks down during production, causing a significant change in the process and resulting in defective products.
- Human Error: An operator makes a mistake, such as incorrect machine settings or improper use of materials, which leads to a spike in defects.
- Material Defects: A batch of raw materials is defective, affecting the quality of the final product.
- Power Surge: A sudden power surge disrupts machinery operation, causing an unexpected variation in the process.
| Source of Variation | Example | Nature |
|---|---|---|
| Machine Breakdown | Sudden failure of critical machinery | Unpredictable, irregular |
| Operator Error | Misuse of tools or incorrect settings | One-time occurrence |
| Material Defects | Poor quality raw material affecting the product | Assignable cause, external |
| External Disruptions | Power surge or sudden environmental changes | External and unusual |
Why is it Important to Distinguish Between Common Cause and Special Cause Variation?
Distinguishing between these two types of variation is critical because it determines how a business or process should respond. Common cause variation indicates that the process is functioning as expected, and improvements to the process may be needed to reduce the overall level of variation. In contrast, special cause variation signals that something unusual has occurred and corrective actions are needed to restore the process to its normal state.
Impact on Process Control
Understanding and correctly interpreting the variation type influences decisions related to process improvement, resource allocation, and troubleshooting:
- Common Cause Variation: If the variation is due to common causes, management should focus on improving the process by reducing variation. This can be done through regular maintenance, training programs, or system improvements. Typically, this type of variation is addressed by preventative measures and continuous improvement methodologies like Six Sigma or Lean.
- Special Cause Variation: Special causes require immediate attention to identify the source of the disruption. Once the special cause is identified, corrective action must be taken. This is often done by investigating the root cause and implementing a solution. For example, if a machine breakdown occurs, repairs and a review of the maintenance schedule may be needed.
Consequences of Misidentifying the Cause of Variation
Incorrectly identifying the cause of variation can lead to inappropriate actions that may not solve the problem. For instance, addressing common cause variation with corrective measures (meant for special causes) might waste resources, disrupt normal operations, and potentially introduce new inefficiencies.
Conversely, ignoring special cause variation by assuming it’s common cause variation can allow the process to go out of control, leading to defects, waste, and even unsafe working conditions. Therefore, it’s essential to accurately distinguish between these two types of variation and respond accordingly.
The Role of Control Charts in Identifying Variation
Control charts are one of the most effective tools for identifying both common cause and special cause variation. By plotting process data over time, control charts visually highlight when a process is stable and when it’s exhibiting unusual behavior.
How Control Charts Detect Common Cause Variation
When a process is under control and only common cause variation is present, data points will fall within control limits (typically ±3 standard deviations from the process mean) and exhibit random scatter around the centerline. This indicates that the process is stable, and no immediate corrective action is needed.
How Control Charts Detect Special Cause Variation
Special cause variation is often revealed when data points fall outside the control limits. These points are “outliers,” indicating that the process is no longer behaving as expected. In addition, patterns such as trends, cycles, or runs (e.g., seven consecutive points on one side of the mean) can also signal special cause variation. These patterns indicate that something abnormal has occurred and that an investigation is needed.
Example of Control Chart Interpretation
Consider the following control chart showing a process that tracks the width of a product. The solid lines represent the control limits, and the dashed line represents the process mean. If a datapoint falls outside the control limits, or if we observe a sustained upward trend, we would suspect special cause variation.
In the chart above, the process is “out of control” for the 6th, 10th, and 14th datapoints as they are outside the control limits. This indicates a special cause variation, and corrective action is needed.
Addressing Common Cause and Special Cause Variation
Handling Common Cause Variation
For common cause variation, organizations typically focus on improving the process’s consistency and reducing the overall level of variation. Strategies may include:
- Standardization: Developing standard operating procedures (SOPs) to ensure consistent performance.
- Training and Development: Ensuring that employees are well-trained and understand the factors affecting variation.
- Maintenance: Regular equipment maintenance to reduce wear and tear and ensure optimal performance.
- Process Optimization: Identifying opportunities for process improvements using methodologies like Lean or Six Sigma.
Handling Special Cause Variation
When special cause variation is identified, the goal is to investigate and eliminate the root cause. Steps include:
- Root Cause Analysis (RCA): Using techniques like Five Whys or Fishbone Diagrams to identify the underlying issue.
- Corrective Action: Once the cause is identified, corrective actions such as repairs, adjustments, or retraining are necessary.
- Preventive Measures: To avoid recurrence, organizations may implement new procedures, enhanced monitoring, or better training.
Conclusion
Understanding the difference between common cause and special cause variation is essential for effective process management and quality control. While common cause variation represents natural fluctuations inherent in any process, special cause variation signals an abnormality that requires immediate corrective action. By using tools like control charts and root cause analysis, organizations can detect and address these variations, ensuring smoother operations and higher-quality outputs.
By managing both types of variation effectively, businesses can improve efficiency, reduce waste, and maintain better control over their processes.
