Assignable cause, also known as special cause variation, represents identifiable factors that create unusual patterns or shifts in your process performance. Unlike random fluctuations that naturally occur in any system, these causes stem from specific, trackable sources that disrupt normal operations.
Think of assignable cause as the smoking gun in quality investigations. When your manufacturing line suddenly produces defective parts or your service delivery times spike unexpectedly, an assignable cause lurks behind these disruptions. These factors create non-random patterns that skilled quality professionals can detect and eliminate.
The term “assignable” literally means you can assign responsibility to a particular source. Whether it’s a machine malfunction, operator error, or environmental change, these causes leave fingerprints that trained eyes can follow back to their origin.
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What is an Assignable Cause?
An assignable cause, also known as a special cause, refers to specific, identifiable factors that cause variations in a process that are not part of its normal operation. Unlike common cause variation, which is inherent and expected within a stable process, assignable causes are disruptions that lead to unexpected outcomes.
Think of them as the culprits behind sudden spikes, dips, or shifts in your data—events that demand immediate attention and correction.
For instance, imagine a factory producing widgets. If the production line suddenly starts churning out defective pieces, the root issue might be a malfunctioning machine, a new operator error, or a batch of faulty raw materials. These are all examples of assignable causes of variation because they can be pinpointed and addressed.
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Why Assignable Causes Matter?
Identifying and resolving assignable causes is critical for maintaining process stability. When left unchecked, these variations can lead to costly errors, reduced efficiency, and dissatisfied customers. By contrast, addressing them promptly ensures your process remains predictable and aligned with your quality standards.
Moreover, understanding the difference between common cause vs. special cause variation empowers you to focus your improvement efforts where they’ll have the most impact.
Common Cause vs. Special Cause Variation
To fully grasp the concept of assignable causes, it’s essential to differentiate them from common cause variation. Let’s explore both types and how they interact within a process.
Common Cause Variation
Common cause variation, sometimes called chance cause variation, is the natural, inherent variability present in any process. It’s the result of multiple small, random factors that are always at play, such as slight differences in raw materials, minor environmental changes, or small inconsistencies in human performance. These variations are predictable within a certain range and don’t typically require immediate action.
Common Cause Variation Examples
- Slight temperature fluctuations in a factory affecting paint drying times.
- Minor differences in employee typing speeds in a data entry process.
- Small variations in customer demand during regular business hours.
Common cause variation is often referred to as the “noise” of a process because it’s expected and unavoidable. It’s like the gentle hum of a well-tuned engine—always there but not disruptive.
Also Read: Lurking Variable
Special Cause Variation
In contrast, special cause variation—or assignable cause variation—is caused by specific, non-random events that disrupt the process. These are the “red flags” that signal something has gone wrong and needs to be fixed. Special causes are not part of the process’s normal operation and often require investigation to identify and eliminate.
Examples
- A machine breaking down, causing a sudden increase in defective products.
- A new supplier delivering substandard raw materials, leading to quality issues.
- An untrained employee misconfiguring equipment, resulting in errors.
Special cause variation is also known as assignable cause variation because these issues can be traced back to a specific source and corrected. The purpose of quality control tools, like control charts, is to detect when a process has changed in a nonrandom way due to these assignable causes.
Key Differences Between Common Cause and Special Cause Variation
| Aspect | Common Cause Variation | Special Cause Variation |
| Nature | Inherent, random, and expected | Non-random, specific, and unexpected |
| Cause | Multiple small, systemic factors | Identifiable, specific events |
| Predictability | Predictable within a range | Unpredictable without investigation |
| Action Required | Process improvement for long-term reduction | Immediate correction of the specific cause |
Understanding this distinction is vital for process managers. Mistaking a common cause for an assignable cause can lead to unnecessary interventions, while ignoring a special cause can allow problems to escalate.
How to Identify Assignable Causes?
Detecting assignable causes of variation requires a systematic approach. Quality control professionals often rely on tools like control charts, which plot process data over time to distinguish between common and special cause variations. Here’s how you can identify assignable causes effectively:
1. Use Control Charts
Control charts are the gold standard for spotting special cause variation. They display process data with upper and lower control limits, which represent the expected range of common cause variation. Points that fall outside these limits or show non-random patterns (e.g., consistent upward trends or sudden shifts) indicate an assignable cause.
For example, if a control chart for a bakery’s bread weight shows a sudden spike above the upper control limit, it might point to an assignable cause like a miscalibrated scale.
2. Investigate Patterns
Beyond control limits, certain patterns on a control chart can signal assignable variation. These include:
- Runs: Eight or more consecutive points above or below the centerline.
- Trends: A steady increase or decrease in data points over time.
- Cycles: Repeating patterns that suggest periodic issues, like equipment wear.
3. Conduct Root Cause Analysis
Once an assignable cause is detected, perform a root cause analysis using tools like the 5 Whys or Fishbone Diagram to pinpoint the source. For instance, if defective products are spiking, ask “Why?” repeatedly to trace the issue back to its origin—perhaps a faulty component or operator error.
4. Monitor Key Process Indicators
Track metrics like defect rates, cycle times, or customer complaints to spot anomalies that might indicate special causes of variation. Regular monitoring helps catch issues early before they escalate.
Examples of Assignable Cause Variation in Action
To bring the concept to life, let’s explore some real-world scenarios where assignable causes disrupt processes:
- Manufacturing: A car assembly line experiences a sudden increase in misaligned parts. Investigation reveals that a new batch of bolts was slightly oversized, causing the issue. This is an assignable cause because it’s specific and fixable by switching suppliers.
- Healthcare: A hospital notices a spike in patient wait times. Root cause analysis shows that a scheduling software glitch double-booked appointments. Correcting the software resolves the issue, addressing the assignable cause.
- Retail: A store sees a drop in sales for a specific product. The cause? A misleading advertisement mispriced the item, deterring customers. Fixing the ad corrects the variation.
These special cause variation examples highlight the importance of quick detection and resolution to maintain process stability.
Common Causes of Variation
While assignable causes are specific and identifiable, common causes of variation are more diffuse and systemic. They stem from the inherent design or operation of the process and can only be reduced through long-term process improvements.
Common Cause Variation Definition
Common cause variation is the natural variability in a process due to its design, materials, or environment. It’s consistent and predictable, forming the baseline “noise” of the system.
Examples of Common Cause Variation
- Slight variations in dough consistency in a bakery due to humidity changes.
- Minor delays in a call center due to varying call volumes.
- Small fluctuations in delivery times caused by traffic patterns.
Addressing common cause variation requires systemic changes, such as redesigning the process, upgrading equipment, or improving training. Unlike assignable causes, these improvements are gradual and long-term.
Also Read: What is X bar in statistics?
Tools and Techniques for Managing Assignable Causes
To effectively manage assignable causes of variation, businesses rely on a suite of quality control tools. Here are some of the most effective:
1. Statistical Process Control (SPC)
SPC uses statistical methods to monitor and control processes. Control charts, a key SPC tool, help distinguish between common cause and special cause variation, enabling timely intervention when assignable causes arise.
2. Pareto Analysis
A Pareto chart identifies the most significant causes of variation by ranking issues by frequency or impact. This helps prioritize which assignable causes to address first.
3. Cause-and-Effect Diagrams
Also known as Fishbone or Ishikawa diagrams, these tools map out potential causes of a problem, helping teams brainstorm and identify assignable causes.
4. Six Sigma Methodology
Six Sigma emphasizes reducing variation through data-driven decision-making. Its DMAIC (Define, Measure, Analyze, Improve, Control) framework is particularly effective for tackling special cause variation.
The Role of Assignable Causes in Continuous Improvement
Addressing assignable causes is not just about fixing immediate problems—it’s a stepping stone to continuous improvement. By eliminating special causes, you stabilize your process, making it easier to analyze and reduce common cause variation. This creates a virtuous cycle of quality enhancement, leading to more predictable outcomes and higher customer satisfaction.
For example, a logistics company that resolves an assignable cause (e.g., a faulty GPS system causing delivery delays) can then focus on optimizing routes to reduce inherent variability, boosting overall efficiency.
Final Words
Mastering assignable cause identification and management represents a cornerstone of effective quality control. Organizations that successfully distinguish between special causes requiring immediate action and common causes needing systematic improvement gain significant competitive advantages.
The key lies in implementing robust detection systems, training personnel to recognize variation patterns, and maintaining disciplined response protocols. As technology continues advancing, predictive analytics and real-time monitoring will further enhance our ability to anticipate and prevent assignable causes before they impact quality.
Success ultimately depends on creating a culture where every team member understands their role in maintaining process stability.
FAQs About Assignable Causes
What is an assignable cause in quality control?
An assignable cause, also known as a special cause, is a specific, identifiable factor that causes unexpected variations in a process, such as equipment failure or human error.
Which is an example of common cause variation?
An example of common cause variation is slight fluctuations in product weight due to natural variations in raw materials or environmental conditions.
How do you identify special cause variation?
Special cause variation is identified using control charts, which show data points outside control limits or non-random patterns like trends or runs.
What is the difference between common cause and special cause variation?
Common cause variation is inherent, random, and expected, while special cause variation is non-random, caused by specific events, and requires immediate correction.
Why is it important to address assignable causes?
Addressing assignable causes ensures process stability, reduces defects, and prevents costly errors, paving the way for long-term process improvement.
