Understanding Common Cause Variation vs Special Cause Variation: Key Differences Explained

Every piece of data that is measured will show some degree of variation. No matter how hard we try to make the conditions identical, each measurement will have slight differences. This inherent difference between data points is known as variation. Variation in statistics refers to the spread of data values around a central point, often represented by the mean.

What is Variation?

Variation is defined as the degree to which individual data points differ from one another or a central value, such as the mean. It quantifies how spread out the values are in a dataset. If the variance is zero, it indicates that all the data points are identical, which is a rare occurrence. On the other hand, if the variance is high, it indicates that the data points are widely spread out. A smaller variance suggests that the data points are closer to the mean. It is important to note that variance cannot be negative, as it is derived from squared differences from the mean.

Variation is an important concept to understand because it plays a significant role in assessing the consistency of a process. For example, in quality control or project management, understanding the variation in data helps in identifying potential problems and deciding whether corrective actions are needed.

Types of Variation

Variation can broadly be classified into two main categories: common cause variation and special cause variation. These two types are essential to understand, especially in the context of project management, where data analysis and process monitoring are crucial.

Common Cause Variation

Common cause variation, also referred to as “natural causes” or “random variation,” is the type of variation that is inherent in a process or system. These variations are considered a normal part of the system, and they occur continuously over time. Harry Alpert first introduced the term common cause variation in 1947. This type of variation is not due to any specific or unusual factors but is instead a product of the natural fluctuations that happen within any process.

Common cause variations are predictable, and they typically result from factors that have been present historically within the system. These causes are often difficult to control or eliminate entirely because they are embedded in the design or structure of the system. However, they do not indicate a failure of the system, as they represent the natural variation that would be expected under normal operating conditions.

Characteristics of Common Cause Variation

1. Predictable Variation: Common cause variation is predictable. Although it is random, statistical analysis can help anticipate the general range within which it will fall. This allows project managers to set control limits based on historical data, helping to manage expectations.

2. Inherent in the System: This type of variation is built into the process. It reflects the limitations of the process design or external factors that affect the process. For example, the temperature in a factory might vary slightly each day due to seasonal changes, which could affect product consistency.

3. Not a Result of Specific Events: Unlike special cause variation, common cause variation does not arise due to specific incidents or events. It is a general characteristic of the system that persists over time.

4. Stable Over Time: While common cause variation exists, it typically remains within a certain range. For instance, if you’re measuring the time it takes for an employee to complete a task, the time may fluctuate slightly, but it will generally remain within a predictable range over an extended period.

The Importance of Common Cause Variation

Understanding common cause variation is crucial for managing processes. When variation falls within the expected range, the process is considered statistically stable. If no special causes are present, there is no need to take corrective action, as the variation is simply a part of the natural fluctuations within the system.

In project management, common cause variation indicates that the project is progressing smoothly, with no significant disruptions or unexpected changes. If a process is stable and the variation is consistent with historical data, managers can make informed decisions without the need for immediate intervention.

For instance, if a project team consistently meets deadlines with slight fluctuations in task completion time, this would be considered common cause variation. There’s no need for drastic changes to improve the process, as the variation falls within acceptable limits.

Examples of Common Cause Variation

To better understand common cause variation, consider the following examples:

1. Employee Task Completion Time: Imagine an employee who is tasked with completing a specific project. Over several weeks, the time it takes for the employee to finish the task may fluctuate, but it is always within a reasonable range. Sometimes, the employee may finish in two days, and other times, it might take two and a half days. These slight differences are considered common cause variation, as they fall within the expected range of completion times.

2. Daily Commute: Suppose you estimate that it takes you 20 minutes to get to work every day. On some days, it might take 25 minutes due to weather conditions or traffic, while on other days, it might only take 18 minutes. This fluctuation in commute time is an example of common cause variation, as it is part of the usual variation that happens during daily commuting.

3. Project Management Procedures: In project management, common cause variation might occur due to factors such as poor working conditions, normal wear and tear of equipment, minor measurement errors, or changes in external factors like weather. These factors are not unusual but are part of the system’s normal functioning and should be accounted for when monitoring project progress.

In all of these examples, the variation is predictable, and while it may affect the outcome, it does not represent an immediate threat or require corrective actions unless the variation becomes too large or outside the expected range.

Statistical Tools for Identifying Common Cause Variation

In practice, statistical tools such as control charts are often used to monitor and track common cause variation. These charts help visualize the variation over time, making it easier to determine if the process is stable or if corrective actions are needed.

Control charts typically consist of upper and lower control limits, which represent the range of variation that is expected under normal conditions. When the data points fall within these limits, it indicates that the variation is due to common causes. However, if the data points fall outside of these limits, it could signal the presence of special cause variation, requiring further investigation.

By using these tools, project managers can ensure that processes are operating within the expected range and take appropriate action when necessary.

In contrast to common cause variation, special cause variation is a type of variation that occurs due to unexpected, specific factors or events. While common cause variation is inherent in the system, special cause variation arises from unusual, unpredictable, and often isolated occurrences that disrupt the normal flow of a process. Understanding this type of variation is vital in managing projects, as it helps to identify problems that may need corrective actions.

What is Special Cause Variation?

Special cause variation refers to deviations in a process that are not part of the normal behavior or natural fluctuations of the system. This variation is caused by external factors, equipment malfunctions, or sudden changes in the environment that are outside the system’s typical operating conditions. Special cause variation is also called “assignable cause variation” because it can typically be traced to a specific event or change in the system.

Unlike common cause variation, which is expected and part of the usual process, special cause variation is often unexpected and requires immediate attention. When such variation occurs, it is an indicator that something outside the norm has happened, and corrective actions may be needed to address the issue and prevent it from recurring.

Characteristics of Special Cause Variation

1. Unpredictable and Sporadic: Special cause variation tends to be sporadic, meaning it occurs irregularly and is often difficult to predict. It arises from events or changes that are not part of the routine operation and can significantly disrupt the process when they occur.

2. Specific and Isolated: Unlike common cause variation, which is spread out over time, special cause variation is usually the result of a specific, isolated event. This could be an equipment malfunction, a sudden environmental change, or even human error. Once identified, it is often possible to pinpoint the exact cause of the variation.

3. Outside Historical Experience: Special cause variation represents something that has not occurred before or is rare. It falls outside the typical range of variation that is observed in historical data, meaning it cannot be predicted from past performance or experience. This makes it more challenging to detect and manage.

4. Indicates a System Disruption: The occurrence of special cause variation typically signals a disruption or malfunction within the system. It is often a warning that something has gone wrong in the process, and immediate action is required to address the issue and restore normal operations.

The Importance of Special Cause Variation

Understanding special cause variation is crucial for ensuring that a process remains under control. While common cause variation is a normal part of system behavior, special cause variation can point to significant problems that may disrupt the overall project or process. Identifying and addressing special cause variation promptly can help prevent it from becoming a more serious issue that impacts the quality or success of a project.

In project management, special cause variation is often a signal that there is a problem with the current process, method, or resource. Identifying the cause of the variation and taking corrective action is essential to restore the process to its optimal state.

Examples of Special Cause Variation

To better understand special cause variation, consider the following examples:

1. Machine Malfunction: Imagine you are overseeing a manufacturing process where a machine has been functioning smoothly for months. One day, the machine breaks down unexpectedly, causing production delays. The breakdown of the machine is a special cause variation because it is not a regular occurrence and has caused an unusual disruption to the process. It is a specific event that requires immediate attention to repair the machine and prevent further delays.

2. Power Outage: A sudden power cut during a project can cause delays or disruptions to the workflow. For example, if a team is working on a critical task and the power goes out unexpectedly, it will halt progress. The power outage is a special cause variation because it is an unpredictable event that is outside the control of the team. Once the power is restored, corrective actions may be required to ensure that the project is back on track.

3. Software Glitch: During a software development project, the team might experience a sudden glitch in the system that prevents the program from functioning as intended. This could be a bug in the code, an unexpected system crash, or a problem with the database. Since this glitch is an isolated, unexpected event, it falls under special cause variation. Once identified, the development team will need to address the issue and prevent it from happening again.

4. Unexpected Market Change: In a project that depends on market conditions, a sudden change in market demand can lead to unexpected disruptions. For instance, if a supplier goes out of business unexpectedly or if new regulations are introduced that affect the project’s scope, these events would be considered special cause variation. They are unusual occurrences that require a response to mitigate their impact on the project.

5. Employee Absenteeism: If a key team member unexpectedly falls ill or experiences a personal emergency, their absence could cause delays or disruptions in the project. This event is not part of the normal process and would be classified as a special cause variation. Management would need to address the absence, perhaps by redistributing tasks or bringing in a temporary replacement.

Identifying Special Cause Variation Using Control Charts

Control charts are often used to monitor processes and identify special cause variation. A control chart helps track data points over time and shows whether the variation is within the expected range. When special cause variation occurs, it typically causes data points to fall outside of the control limits, signaling that the process has been disrupted.

In a control chart, the points representing the process will usually fall within a specific range, typically within three standard deviations from the mean. If the points fall outside of these limits, it suggests that an unusual event has occurred, indicating special cause variation. Once the special cause is identified, corrective actions can be taken to resolve the issue.

For example, if a project team is tracking the number of tasks completed each week, the chart will display data points within the expected range if the project is progressing smoothly. However, if a sudden dip in the number of tasks completed occurs due to an unexpected event, the data points will fall outside the control limits, signaling the need for investigation.

Addressing Special Cause Variation

When special cause variation is identified, it is essential to take immediate corrective action. The steps to address special cause variation include:

1. Identify the Cause: The first step in addressing special cause variation is to identify the root cause of the disruption. This could involve investigating recent changes in the process, equipment, resources, or external factors that may have contributed to the variation.

2. Take Corrective Action: Once the cause is identified, take the necessary corrective action to eliminate the problem and restore the process to normal. This could involve repairing equipment, addressing human errors, changing processes, or making adjustments to resources.

3. Monitor for Recurrence: After corrective action has been taken, it is important to monitor the process to ensure that the special cause variation does not occur again. This may involve implementing additional safeguards, improving training, or making other improvements to the system.

4. Evaluate Process Changes: If the special cause variation reveals a flaw in the system or process, it may be necessary to make changes to prevent similar disruptions in the future. This could involve redesigning processes, investing in new equipment, or improving quality control measures.

Understanding the distinction between common cause variation and special cause variation is essential for managing processes effectively. Differentiating between these two types of variation enables project managers and process owners to make informed decisions about when to take corrective actions and when to let the process continue running smoothly.

The Role of Control Charts in Identifying Variation

Control charts are one of the most effective tools for distinguishing between common cause and special cause variation. These charts help track data points over time, providing a visual representation of the stability or instability of a process. By using control charts, project managers can easily identify when a process is operating within the expected range (common cause variation) and when an unusual event has occurred (special cause variation).

Components of a Control Chart

A control chart typically consists of several key components:

1. Data Points: These represent the values measured from the process over time.

2. Mean (Central Line): This is the average value of the data points, representing the expected value under normal conditions.

3. Control Limits: The upper and lower control limits are typically set at three standard deviations from the mean, representing the expected range of variation within which most data points should fall.

4. Out-of-Control Points: Data points that fall outside the control limits signal that something unusual has occurred and require investigation.

The purpose of using control charts is to monitor variation in the system over time. When the data points remain within the control limits, it suggests that the variation is due to common causes. However, if the data points fall outside of the control limits, it indicates that special cause variation may be present, and further investigation is required.

Identifying Common Cause Variation on Control Charts

Common cause variation appears on control charts as data points that remain within the control limits over time. The process behaves predictably, and while there may be fluctuations in the data, these fluctuations are within the expected range. Common cause variation is a natural part of the system and does not typically indicate any immediate issues.

When a process exhibits only common cause variation, the control chart will show random data points scattered around the central line (mean), with the points remaining within the upper and lower control limits. This indicates that the system is stable and predictable, and no corrective action is required. The process is statistically stable, and the variation is part of normal operations.

Identifying Special Cause Variation on Control Charts

Special cause variation is identified when data points fall outside the control limits. When this happens, it suggests that something out of the ordinary has occurred, causing an abnormal disruption to the process. Special cause variation may also appear as a pattern of points that show a clear trend, shift, or sudden change in the process behavior.

There are several patterns to look for on control charts that indicate special cause variation:

1. Points Outside Control Limits: The most straightforward indicator of special cause variation is when one or more data points fall outside the upper or lower control limits. This is a clear sign that the process is no longer operating as expected and that something unusual has occurred.

2. Trends: A series of consecutive data points that consistently rise or fall in a particular direction may signal special cause variation. This could indicate a gradual shift in the process or a trend caused by an external factor.

3. Run of Consecutive Points on One Side of the Mean: A large number of consecutive data points that all fall on the same side of the mean can also suggest special cause variation. This could indicate that a process is being influenced by a factor that is pushing it in one direction.

4. Sudden Shifts: A sudden shift in the data points, where the values dramatically change in a short period, is another indicator of special cause variation. This could happen if a major disruption occurs, such as equipment failure or a change in external conditions.

Causes of Special Cause Variation

Special cause variation can arise from a wide variety of factors, many of which are external to the process. Some common causes of special cause variation include:

• Equipment Failures: A malfunction or breakdown in machinery can cause a sudden disruption to the process, leading to special cause variation. For example, a defective sensor on a production line could cause unexpected changes in product quality.

• Human Error: Mistakes made by workers or operators can introduce special cause variation. For instance, a worker may accidentally introduce the wrong material into a process, leading to a deviation from normal results.

• Environmental Factors: Changes in the environment, such as temperature fluctuations, power outages, or unexpected weather events, can disrupt the stability of a process and lead to special cause variation.

• Supply Chain Disruptions: Issues such as delays in receiving materials, changes in suppliers, or fluctuations in material quality can introduce special cause variation, as they are not part of the expected process behavior.

• Process Changes: Any deliberate or accidental change to the process, such as a new procedure, equipment upgrade, or modification, can introduce special cause variation. Even small adjustments can have significant impacts on the results of a process.

When to Take Action: Common Cause vs Special Cause

One of the main differences between common cause and special cause variation is how they are handled. Common cause variation is part of the system and is generally accepted as normal. No immediate action is required unless the variation exceeds a tolerable threshold. However, special cause variation indicates that something outside the usual process has occurred, and corrective action is necessary.

Addressing Common Cause Variation

When common cause variation is identified, the appropriate response depends on whether the variation is acceptable within the process. If the variation is within an acceptable range, no immediate action is needed. The process can continue as it is, and managers can focus on monitoring to ensure that the variation remains stable.

However, if the variation is too large or has become problematic over time, it may indicate that the system needs to be improved. In such cases, a fundamental change to the process might be required to reduce the variation and make the process more predictable. For example, if a manufacturing process consistently produces defective products, this could signal a need for improvements in equipment, procedures, or training.

Addressing Special Cause Variation

Special cause variation, on the other hand, requires immediate investigation and corrective action. The first step is to identify the source of the variation. Once the cause is identified, steps should be taken to eliminate the root cause of the problem. This might involve repairing equipment, retraining employees, adjusting processes, or changing external factors that influence the system.

Once corrective actions have been taken, the process should be monitored closely to ensure that the special cause variation does not recur. If the issue is not resolved, further investigation may be needed, and additional measures may need to be implemented to prevent future disruptions.

The Importance of Differentiating Between Common Cause and Special Cause Variation

Differentiating between common cause and special cause variation is critical for effective process management. By identifying whether the variation is part of the normal process or the result of an unexpected event, managers can make informed decisions about whether corrective action is necessary. Responding to special cause variation promptly can help prevent larger issues from developing and ensure that the process remains stable. On the other hand, understanding that common cause variation is inherent in the system allows for a more balanced approach, where minor fluctuations are accepted as part of the process without unnecessary intervention.

Understanding and managing variation is a critical skill in project management. Whether it’s predicting project outcomes, monitoring progress, or identifying potential risks, recognizing when a process is affected by common cause or special cause variation can make all the difference in a project’s success. In this final part, we will explore how this knowledge can be applied in project management to enhance decision-making, reduce risks, and improve overall project outcomes.

Importance of Managing Variation in Project Management

In project management, processes must be consistent and efficient to ensure that the project stays on track and meets its objectives. The ability to distinguish between common cause and special cause variation helps project managers understand how well a project is performing and whether deviations from the plan are a normal part of the process or due to unforeseen factors.

Managing variation is essential because it enables project managers to:

1. Predict Project Performance: By understanding variation, project managers can forecast potential project timelines, costs, and resource requirements. This helps in planning and setting realistic expectations.

2. Assess Process Stability: When project processes show common cause variation, it suggests that the process is stable and predictable, while the presence of special cause variation points to potential disruptions or problems that need to be addressed.

3. Improve Decision Making: Recognizing the source of variation helps managers make informed decisions. They can decide when to take corrective action for special cause variation and when to make improvements for long-term process stability.

Applying Knowledge of Variation to Project Scheduling

One of the key areas where variation impacts project management is in scheduling. Projects often face unpredictable challenges, and understanding how variation affects the completion of tasks is crucial for maintaining a realistic timeline.

Managing Task Completion Time

In any project, tasks are rarely completed exactly as planned. There are often fluctuations in the time it takes to complete individual tasks, which are influenced by many factors such as resource availability, complexity, and team performance. These variations can be categorized as either common cause or special cause variation.

1. Common Cause Variation: If a team consistently completes a task a little earlier or later than planned, but these variations fall within an expected range, this is common cause variation. For example, a task might take 10 hours one week and 12 hours the next, but the variation is within an acceptable range. In this case, the project manager should not be alarmed and can plan for this level of variation by building buffer time into the schedule.

2. Special Cause Variation: If a task that normally takes 10 hours suddenly takes 25 hours due to a machine breakdown, this is an example of special cause variation. This kind of deviation is unexpected and outside the normal range. The project manager should investigate the cause of the delay, make necessary repairs or adjustments, and update the project plan to accommodate any additional time required.

By monitoring task completion times and using control charts, project managers can quickly spot when special cause variation occurs and take action to mitigate further delays. Recognizing and addressing special cause variation early helps keep the project on track.

Using Variation Analysis for Budget Management

Budgeting is another area where variation can have significant impacts. In projects, costs can fluctuate due to unforeseen circumstances such as supplier price changes, resource shortages, or unexpected labor costs. Properly managing these variations is essential for ensuring that the project remains within budget.

Tracking Costs and Identifying Variations

1. Common Cause Variation: Some level of fluctuation in costs is normal in most projects. For example, the price of materials might increase slightly due to seasonal demand, or labor rates might vary based on the time of day or week. These types of fluctuations are part of the natural process and fall under common cause variation. As long as these fluctuations are within an acceptable range, no immediate action is needed.

2. Special Cause Variation: If there is a sudden and significant cost increase that exceeds the normal range, such as an unexpected change in the price of materials or an equipment failure requiring an unplanned purchase, this is special cause variation. The project manager needs to identify the specific cause of the unexpected cost, assess its impact, and determine the necessary corrective actions to address the issue.

Monitoring project costs using tools like earned value management (EVM) can help project managers track cost performance and identify when special cause variation is affecting the budget. If special cause variation is identified, corrective actions can be implemented, such as renegotiating contracts or finding alternative suppliers.

Managing Quality and Process Control

Quality control is a key aspect of project management, particularly in manufacturing, construction, or software development projects. Ensuring consistent quality while minimizing defects requires an understanding of variation and how to address it when necessary.

Quality Control and Common Cause Variation

When a process is operating with common cause variation, quality performance is generally consistent, and the variation is predictable. For example, in a manufacturing process, slight differences in product dimensions are often normal. As long as the variation remains within established control limits, the process is considered stable, and the quality of the product meets the expected standards.

Project managers can use quality control charts to monitor product defects, production rates, or other key quality indicators. When the variation is within expected limits, the project manager can confidently proceed with production without taking corrective action.

Special Cause Variation in Quality Control

However, if there is a sudden spike in defects or a significant deviation from the expected quality levels, it may indicate the presence of special cause variation. For example, if a new batch of materials causes defects or a machine malfunctions, leading to defects in the product, this is special cause variation.

Special cause variation in quality control must be addressed immediately to prevent further impact on the project’s quality standards. The project manager would investigate the root cause of the quality issue, implement corrective measures (such as replacing faulty equipment or adjusting processes), and assess the impact on project deliverables.

Risk Management and Variation

Risk management is an essential component of any project, and understanding variation plays a critical role in identifying, assessing, and mitigating risks. Both common cause and special cause variations can contribute to project risks, and managing these variations effectively is key to maintaining control over the project.

Identifying Risks Due to Common Cause Variation

While common cause variation is typically predictable, it can still lead to risks if not properly managed. For example, if a project consistently experiences minor delays in task completion or cost fluctuations, these variations can accumulate over time and increase the overall project risk. Project managers can use predictive tools and monitoring techniques, such as control charts, to assess whether the common cause variation is within acceptable limits and whether it poses any significant risk to the project.

Managing Special Cause Risks

Special cause variation, on the other hand, can introduce higher levels of risk to the project. Unexpected events, such as equipment failure, accidents, or supply chain disruptions, can result in delays, increased costs, and reduced quality. When special cause variation occurs, the project manager needs to act quickly to assess the impact of the disruption, mitigate any negative effects, and update the project plan to reflect the new reality.

By identifying and addressing special cause variation early, project managers can prevent risks from escalating and causing long-term damage to the project.

Conclusion

In conclusion, understanding common cause and special cause variation is crucial for successful project management. By using tools like control charts and statistical analysis, project managers can track variation in key areas such as scheduling, budgeting, quality control, and risk management. Differentiating between the two types of variation enables managers to make informed decisions about when to take corrective action and when to allow the process to continue without intervention.

Managing variation effectively helps ensure that the project remains on track, within budget, and on schedule, while also maintaining the required level of quality. By recognizing and addressing both common cause and special cause variation, project managers can enhance their ability to manage risks, reduce disruptions, and achieve project success.