In the world of process improvement and quality management, the ability to visualize data trends over time stands as a cornerstone skill. Within the DMAIC (Define, Measure, Analyze, Improve, Control) framework of Lean Six Sigma, the Measure phase plays a critical role in establishing baseline performance and identifying patterns that warrant further investigation. Among the various statistical tools available, run charts emerge as one of the most accessible yet powerful instruments for trend analysis.
What Are Run Charts and Why Do They Matter?
A run chart, also known as a time series chart or trend chart, represents a graphical display of data points plotted in chronological order. This simple yet effective tool allows quality professionals, managers, and team members to observe how a process behaves over time, revealing patterns, trends, and variations that might otherwise remain hidden in raw numerical data. You might also enjoy reading about Measure Phase: Understanding Takt Time and Cycle Time for Process Excellence.
The beauty of run charts lies in their simplicity. Unlike more complex statistical process control tools, run charts require minimal statistical knowledge while still providing valuable insights into process behavior. They serve as an excellent starting point during the Measure phase, helping teams determine whether a process is improving, deteriorating, or remaining stable. You might also enjoy reading about Process Capability Analysis Fundamentals: A Complete Guide to the Measure Phase.
Core Components of a Run Chart
Before diving into creation and interpretation, understanding the fundamental elements of a run chart proves essential. Every run chart contains several key components that work together to tell the story of your process.
The Vertical Axis (Y-Axis)
The vertical axis displays the measurement or metric being tracked. This could represent anything from customer satisfaction scores, defect rates, production times, or revenue figures. The scale should be appropriate to accommodate all data points while maintaining readability.
The Horizontal Axis (X-Axis)
The horizontal axis represents time in sequential order. Time intervals might include hours, days, weeks, months, or any other relevant time period appropriate for your process. Consistency in time intervals is crucial for accurate interpretation.
Data Points
Each point on the chart represents an individual measurement taken at a specific time. These points are connected by lines to help visualize the flow and direction of the data over time.
The Median Line
A horizontal reference line drawn at the median value of all data points helps identify whether measurements fall above or below the typical performance level. This line serves as an anchor point for pattern recognition.
Creating Your First Run Chart: A Step-by-Step Guide
Let us walk through the process of creating a run chart using a practical example. Imagine you manage a customer service department and want to track the average call handling time over a four-week period.
Step 1: Collect Your Data
Gather sequential data points. For our example, we have collected daily average call handling times (in minutes) for 20 working days:
Week 1: 8.2, 8.5, 7.9, 8.1, 8.3
Week 2: 8.0, 7.8, 7.6, 7.5, 7.7
Week 3: 7.4, 7.2, 7.1, 7.3, 7.0
Week 4: 6.9, 6.8, 6.7, 6.9, 7.1
Step 2: Calculate the Median
Arrange all values in numerical order and find the middle value. With 20 data points, the median falls between the 10th and 11th values. In this case, our median is 7.45 minutes.
Step 3: Set Up Your Axes
Create a graph with time (Days 1 through 20) on the horizontal axis and call handling time (6.0 to 9.0 minutes) on the vertical axis. Ensure adequate spacing for clear visualization.
Step 4: Plot Your Data Points
Mark each measurement at its corresponding time point. Connect consecutive points with straight lines to show the progression over time.
Step 5: Draw the Median Line
Add a horizontal line at 7.45 minutes across the entire chart. This reference line will help you identify patterns and shifts in the process.
Interpreting Run Chart Patterns
Once you have created your run chart, the next critical step involves interpretation. Several patterns can indicate non-random variation or special causes affecting your process.
Trend Analysis
A trend exists when you observe a continuous series of points moving in the same direction. In our customer service example, we see a clear downward trend over the four weeks, suggesting that call handling times are improving. Typically, six or more consecutive points moving in the same direction indicate a statistically significant trend.
Shifts in Process Level
A shift occurs when a series of consecutive points fall on one side of the median line. The rule of thumb suggests that eight or more consecutive points above or below the median indicate a shift in process performance. In our example, the last 10 points all fall below the median, suggesting a sustained improvement in performance.
Runs
A run represents a sequence of points on the same side of the median line. Too many or too few runs compared to what would be expected by chance can indicate special causes affecting your process.
Astronomical Points
These are data points that appear obviously different from all others, falling far outside the normal range of variation. Such points demand immediate investigation to understand their cause.
Practical Applications Across Industries
Run charts find application across diverse sectors and processes. Manufacturing facilities use them to track defect rates, cycle times, and equipment downtime. Healthcare organizations monitor patient wait times, medication errors, and readmission rates. Retail businesses track daily sales, inventory turnover, and customer complaints.
Consider a hospital emergency department tracking patient wait times. By creating a run chart showing average wait times over several months, administrators might discover that wait times spike every weekend, prompting them to adjust staffing schedules accordingly. This simple visualization transforms raw data into actionable insights.
Common Pitfalls to Avoid
While run charts are straightforward tools, several common mistakes can undermine their effectiveness. First, avoid using insufficient data points. A minimum of 10 to 15 points is recommended for meaningful pattern recognition. Second, ensure your time intervals remain consistent throughout the data collection period. Third, resist the temptation to overreact to normal variation; not every fluctuation indicates a problem requiring intervention.
Another frequent error involves mixing different types of data or changing measurement methods midway through data collection. Such inconsistencies make accurate interpretation impossible and can lead to incorrect conclusions about process behavior.
Beyond Basic Run Charts: Advanced Considerations
As you become more comfortable with basic run charts, you can explore additional analytical techniques. Annotating your charts with relevant events, process changes, or external factors helps establish cause-and-effect relationships. For instance, if you implemented a new training program on Day 10, noting this on your run chart helps determine whether the training influenced performance.
Multiple run charts can be created for related metrics to identify correlations and relationships between different aspects of your process. This multi-dimensional view often reveals insights that single charts cannot provide.
Transitioning from Run Charts to Control Charts
Run charts serve as an excellent precursor to more sophisticated statistical process control tools, particularly control charts. Once you have established that significant patterns exist in your run chart, you may want to calculate control limits and create control charts for more rigorous process monitoring. This natural progression represents the maturation of your measurement and analysis capabilities within the Six Sigma framework.
Taking Your Skills to the Next Level
Understanding run charts represents just one component of the comprehensive toolkit available through Lean Six Sigma methodology. The Measure phase encompasses numerous additional concepts, including measurement system analysis, process capability studies, and various data collection techniques. Mastering these tools empowers you to drive meaningful improvements in any organizational context.
The journey from novice to expert in quality management requires structured learning, practical application, and ongoing development. Run charts provide an accessible entry point, but the full power of Six Sigma emerges when you understand how to integrate multiple tools and techniques into a cohesive improvement strategy.
Whether you aspire to lead improvement projects, enhance your analytical skills, or advance your career in operations management, formal training provides the foundation for success. Professional Lean Six Sigma certification programs offer comprehensive curriculum, hands-on practice, and expert guidance that transforms theoretical knowledge into practical expertise.
Enrol in Lean Six Sigma Training Today
The skills you develop through Lean Six Sigma training extend far beyond creating run charts. You will gain the ability to identify improvement opportunities, lead cross-functional teams, apply statistical analysis, and deliver measurable results that impact organizational performance. From Yellow Belt fundamentals to Black Belt mastery, structured certification paths accommodate professionals at every career stage.
Do not let valuable insights remain hidden in your data. Take the first step toward becoming a skilled problem solver and change agent within your organization. Enrol in Lean Six Sigma training today and discover how powerful yet accessible tools like run charts can transform the way you understand and improve processes. Your journey toward data-driven decision making and continuous improvement begins with a single commitment to professional development. Make that commitment today.
