Advanced Topics in Process Improvement
This domain tests data-driven improvement methods: Lean, Six Sigma DMAIC, Theory of Constraints, simulation, and process mining. Expect questions on waste, bottlenecks, root cause, and control after improvement.
Methods
- DMAIC: Define, Measure, Analyze, Improve, Control.
- Lean waste includes DOWNTIME: defects, overproduction, waiting, non-utilized talent, transportation, inventory, motion, extra-processing.
- Value stream mapping separates value-added, necessary non-value-added, and waste.
- Theory of Constraints: identify the bottleneck, exploit it, subordinate other steps, elevate it, then repeat.
- Process mining supports discovery, conformance checking, and enhancement.
- Simulation tests changes against variability and volume before rollout.
Worked example
An insurance claims process has a 12-day cycle time. The value stream map shows four hours of work and 11 days of waiting. Pareto analysis shows 60% of delay at 'await medical report.' A fishbone diagram identifies batch release of reports as a cause. The improvement is daily electronic release, standard work, and a non-interrupting reminder. Simulation at 20% higher volume predicts cycle time falls to six days without adding staff. A control plan tracks cycle time, wait time, and first-pass yield. Reasoning: improve the bottleneck and waiting, not the busy but unconstrained steps.
Traps that cost marks
- Jumping to solutions before measuring.
- Optimizing a non-bottleneck and creating local efficiency.
- Confusing cycle time with throughput.
- Ignoring variability; piloting without a control plan.