Trending graphs (also called run charts or trend analysis charts) are powerful tools in Lean Six Sigma and data-driven decision-making. They help you visualize changes over time, spot long-term patterns, and understand how processes behave in real-world conditions.
Unlike single-point measurements, which can be misleading, trending graphs show continuous performance. They allow businesses, healthcare systems, and organizations across industries to track improvement against goals and targets.
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What Are Trending Graphs, and How to Interpret Them?
Trend analysis charts are designed to display data over time. By plotting points sequentially, you can uncover:
- Hidden patterns and relationships
- The difference between short-term fluctuations and long-term changes
- Whether a process is moving toward or away from its desired target
On county, state, or national dashboards, trend graphs highlight how performance evolves. In Lean Six Sigma, they are used to measure improvement, reduce waste, and sustain efficiency.
What are Trend Charts and How Do They Work?
The most common trend charts include:
- Run charts: Plot data points over time on the x-axis to detect shifts and variations.
- Control charts: Add statistical upper and lower control limits, showing if variation is due to common or special causes.
- Time series charts: Used for forecasting by finding historical patterns and projecting them into the future.
Together, these charts form the foundation of data-driven continuous improvement.
Types of Trends You Can Analyze in Charts
Graphs simplify data and reveal trends that are otherwise hard to detect. Below are common trend types and how to interpret them.
Linear Trend
A straight line showing a constant rate of change. If the slope is upward, performance is improving. A downward slope signals decline.
Exponential Trend
A curve that starts slow but accelerates sharply. This often represents rapid growth (like compound interest or population growth) or fast decay (such as resource depletion).
Logarithmic Trend
Rises quickly at first, then slows down. Often seen in market saturation or diminishing returns.
Quadratic Trend
Forms a U-shape or inverted U-shape. It signals that the rate of change depends on the variable’s level, often used in optimization problems.
Sinusoidal Trend
Wave-like and recurring, often seasonal. Seen in climate patterns, energy usage, or consumer demand cycles.
Step Trend
Shows sudden jumps caused by interventions such as new policies, technology upgrades, or economic shocks.
Seasonal Trend
Regular, repeating changes tied to specific periods. Seen in retail sales peaks during holidays or agricultural output cycles.
Cyclical Trend
Represents long-term economic or business cycles. Useful for forecasting recessions, expansions, or industry-wide shifts.
Pro tip: Always interpret trends within their context. External factors like policy changes, global events, or industry disruptions can alter trend lines.
3 Best Charts to Show Trends Over Time
1. Line Chart
The simplest and most popular trend chart, perfect for showing changes over time.
- X-axis: time
- Y-axis: measured variable
- Slope indicates the direction and pace of change
Example: Tracking monthly sales or defect counts in a Six Sigma project.
2. Combo Charts
These combine two chart types (e.g., line + column) to reveal multiple insights at once.
- Compare categories and time-based variables
- Spot overlapping patterns or hidden correlations
- Great for executive dashboards and decision-making presentations
Example: Compare revenue growth with marketing spend over time.
3. Comparison Charts
Designed to highlight relationships and differences.
- Useful in business analysis, product benchmarking, or digital marketing attribution
- Compare two or more metrics side by side
- Helps identify which factors drive performance
Example: Comparing sales vs. profits or website traffic sources.
Frequently Asked Questions (FAQ) About Trending Graphs
Q1: What is the primary purpose of a trending graph in Six Sigma?
The primary purpose is to visualize a process’s performance over time to distinguish between short-term fluctuations and long-term trends. This helps you measure improvement, sustain gains, and detect when a process is moving off-target.
Q2: What is the difference between a Run Chart and a Control Chart?
A Run Chart plots data points sequentially over time to look for patterns. A Control Chart adds statistically calculated Upper and Lower Control Limits (UCL/LCL) to determine if process variation is normal (common cause) or abnormal (special cause).
Q3: What does a Step Trend typically indicate?
A Step Trend shows a sudden, sustained jump or drop in the data line. It usually indicates a specific, non-random event or intervention, such as implementing a new policy, upgrading technology, or a major change in the operating environment.
Q4: Why is it important to consider Seasonal and Cyclical Trends?
It is important because these trends represent predictable, recurring variations. Failing to account for them can lead you to mistake normal, natural changes (like holiday sales) for genuine process improvement or decline.
Q5: When should I use a Combo Chart instead of a simple Line Chart?
Use a Combo Chart (like a line chart combined with a column chart) when you need to simultaneously visualize two different types of data or show two metrics on different scales. This helps reveal hidden correlations or overlapping patterns for complex decisions.
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