Day 1: Diagnosing Quality Gaps and Selecting Methods

Defining Quality and the Gap

• Identify unmet expectations or standards
• Measure problem magnitude, not impressions
• Define affected parties, location, timing
• Write a focused improvement statement

Process Mapping and Failure Points

• Map steps handoffs and decisions
• Identify rework waiting and defects
• Connect quality gaps with occurrence points
• Build current-state map with defect points

Selecting the Improvement Approach

• Use PDCA for rapid change experiments
• Distinguish improvement from deeper analytical projects
• Identify situations requiring formal corrective action
• Choose approaches for three different cases

Day 2: Cause Analysis and Solution Experiment

Evidence for the Quality Gap

• Define measures before solution design begins
• Choose samples and periods reflecting problem
• Separate opinion from observable evidence
• Prepare fact sheet separating evidence/assumptions

Establishing the Cause

• Use iterative questioning and cause diagrams
• Test proposed causes against data/observation
• Avoid blaming employee error alone
• Build a testable cause hypothesis

Designing a PDCA Experiment

• Define limited change and expected result
• Set experiment duration and success measures
• Manage risks introduced by the test
• Simulate complete improvement cycle against baseline

Day 3: Measurement, Standardization, and Improvement Portfolio

Checking the Change Effect

• Compare results against the baseline
• Distinguish genuine improvement from ordinary variation
• Identify unintended side effects
• Decide whether to adopt, modify, stop

Standardizing the Improved Method

• Update procedure forms and training
• Assign ownership for new-performance monitoring
• Retire steps restoring old methods
• Prepare a sustainment plan

Managing the Improvement Backlog

• Prioritize opportunities by customer effect/effort
• Distribute initiatives across available team capacity
• Track progress/results, not activity volume
• Build a quarterly improvement board

• Process maps linking quality gaps with where they occur
• Cause analysis grounded in data and observation
• Small PDCA experiments completed before broad rollout
• An improvement board combining priority ownership and intended result