Process Improvement Consultant
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- Build the improvement discipline: define value, map the process and use DMAIC to remove waste
- Prove causes with data, prioritize failure risk and distinguish signal from normal process variation
- Scale the gain with automation, standard work, controls and change mechanisms that keep the process healthy
Benchmark: Amazon Process Improvement Program Manager + Sr Process Improvement Specialist, AIR ACES (current Sep 2026) Market refresh: Lean/Six Sigma, value-stream mapping, root-cause/FMEA, SPC/process mining, scalable automation, KPI ownership, standard work, operator engagement and sustai...
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Enrichment
Build the improvement discipline: define value, map the process and use DMAIC to remove waste
Lean Six Sigma + DMAIC improvement logic
Coverage: Process Improvement: Lean, Six Sigma & Kaizen
Value-stream / process mapping + future-state flow
Coverage: Business Process Mapping & BPMN / Standard Work
Prove causes with data, prioritize failure risk and distinguish signal from normal process variation
Root-cause analysis + FMEA risk prioritization
Coverage: Operational Excellence Analytics / Problem Solving / Reliability
SPC, process stability + process mining
Coverage: Statistics & Probability / SPC / Process Mining
Scale the gain with automation, standard work, controls and change mechanisms that keep the process healthy
Workflow automation + AI-enabled process improvement
Coverage: Workflow Automation / AI Agents / Digital Process Improvement
Control, standard work + sustained adoption
Coverage: Operational Excellence / Change Management / Coaching & Feedback
Role-Readiness Proof / Capstone
Lead an end-to-end DMAIC improvement on a real or simulated operation. Define the customer/CTQ, charter and target; create SIPOC/value-stream/BPMN views and a trustworthy baseline; validate measurement quality; identify waste and variation; prove root causes with 5-Why/FMEA plus data; use SPC and process-mining evidence where available; design and pilot the future state; automate one repeatable step; quantify cost, quality, cycle-time, capacity and reliability impact; then deploy standard work, controls, owner/runbook documentation, KPI dashboard, operator engagement and a 30/60/90-day sustainment review.
Proof Rubric
- Show a statistically and operationally credible baseline
- distinguish common-cause from special-cause variation
- validate root causes before prescribing countermeasures
- prioritize failure risk explicitly
- quantify before/after performance and confidence
- demonstrate the automation under failure/exception cases
- create usable standard work and control triggers
- assign owners and escalation paths
- and prove the gain is sustained through KPI/SPC evidence, Gemba/operator feedback and a documented continuous-improvement cadence