The Role of Data in Six Sigma Decision Making

The Importance of Data-Driven Decisions

Data-driven decision making is fundamental to Six Sigma because it:

• Eliminates guesswork and assumptions
• Provides objective evidence
• Enables accurate measurement of improvements
• Facilitates fact-based discussions

Types of Data to Collect

Continuous Data

• Measurements (time, length, weight)
• Temperatures
• Costs
• Dimensions

Discrete Data

• Counts of defects
• Pass/fail results
• Categories
• Rankings

Data Collection Methods

Effective data collection requires:

• Clear operational definitions
• Standardized collection forms
• Trained data collectors
• Validation procedures
• Proper sampling methods

Data Analysis Techniques

Common analysis methods include:

• Basic statistics (mean, median, mode)
• Variation analysis
• Trend analysis
• Correlation studies
• Hypothesis testing

Presenting Data Effectively

Key visualization tools:

• Control charts
• Pareto diagrams
• Scatter plots
• Box plots
• Run charts