Day 1: Define — Connecting the Project with Value

Six Sigma Problem Statement

• Define gap magnitude, location, timing
• Avoid embedding solutions in problem definitions
• Estimate effects on customer and performance
• Prepare a measurable problem statement

Voice of Customer and CTQ

• Extract critical-to-quality requirements from customer voice
• Translate requirements into measurable definitions
• Set suitable specification or acceptance limits
• Build CTQ tree for one case

SIPOC and Project Charter

• Define suppliers, inputs, process, outputs, customers
• Confirm start end resources and boundaries
• Set goal owner team and timing
• Prepare a project charter

Day 2: Measure — Building a Reliable Baseline

Data Collection Plan

• Define variables units sources and sample
• Select periods representing normal operation
• Assign responsibility for collection and verification
• Prepare a measurement plan

Measurement System and Data Quality

• Assess consistency and repeatability of measurement
• Separate measurement error from process variation
• Perform simplified verification of measurement method
• Review data before deeper analysis

Baseline and Process Capability

• Calculate appropriate descriptive statistics
• Examine distribution and trend
• Estimate capability against specification limits
• Build baseline profile for the problem

Day 3: Analyze — Establishing the Causes

Potential Cause Analysis

• Generate hypotheses using process/cause maps
• Prioritize causes by evidence over opinion
• Select measurable variables for testing
• Prepare a cause-hypothesis list

Relationships and Statistical Tests

• Use comparison correlation and statistical tests
• Interpret statistical and practical significance together
• Avoid claiming causation from correlation alone
• Test a hypothesis on training data

Waste and Flow Analysis

• Connect variation with waiting/WIP/rework
• Identify non-value steps and loops
• Measure bottleneck effect on performance
• Integrate Lean observations with statistical analysis

Day 4: Improve — Designing and Verifying Solutions

Generating and Selecting Solutions

• Link proposed solution with verified cause
• Balance impact, risk, effort, speed
• Reject solutions adding avoidable complexity
• Use a structured solution-selection matrix

Pilot and Incremental Improvement

• Test selected solutions on limited scale
• Define success/failure measures before implementation
• Collect post-change data using same method
• Analyze key pilot results

Designing the Improved Flow

• Reduce waste waiting and handoffs
• Standardize steps that demonstrate stability
• Define controls preventing cause recurrence
• Prepare a target-state process map

Day 5: Control — Sustaining the Gains

Developing Control Plan

• Define variables limits and measurement frequency
• Assign responses when performance leaves control
• Name data and process owners
• Prepare a practical Control Plan

Statistical Monitoring Where Appropriate

• Differentiate routine variation from special-cause signals
• Choose control charts appropriate to data
• Avoid tampering with stable process variation
• Interpret selected control-chart patterns

DMAIC Project Closure

• Confirm goal achievement against the baseline
• Transfer ownership, documents, controls to operations
• Identify follow-up or replication opportunities
• Present project story through verified result

• An integrated DMAIC project using ISO 13053 as a methodological reference
• Data exercises measuring variation capability and testing hypotheses
• Lean waste and flow analysis within the same improvement problem
• A control plan connecting measures with operational ownership