• Learning Path
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• Core Tech

Lean Six Sigma is a proven, data-driven methodology for finding and eliminating the friction that destabilizes your systems. Originally built for manufacturing, it has become a powerful framework for technical teams who need to stabilize broken digital workflows, reduce technical debt, and prepare their processes to scale with automation and AI.

This path is designed for engineering managers, site reliability engineers, DevOps leads, cloud architects, and other technical professionals responsible for keeping complex systems running. No prior statistics or Lean Six Sigma experience is required. You'll work through the full DMAIC cycle—Define, Measure, Analyze, Improve, and Control—using examples drawn from IT operations and software delivery rather than the factory floor. Along the way, you'll translate vague complaints like alert fatigue and slow deployment times into measurable Cost of Poor Quality, establish objective performance baselines using metrics such as Rolled Throughput Yield and DPMO, apply statistical tools to isolate true root causes, and build control plans that keep processes stable enough to survive RPA and AI automation.

By the end of this path, you'll be able to quantify operational friction in financial terms leadership understands, prove causation with data instead of gut feelings, and engineer lasting stability directly into your existing Agile sprint cycles.

This skill path is actively in production. More content will be added as it publishes. Planned content includes:

**Lean Six Sigma Foundations (Published)** — Establish DMAIC as your roadmap for resolving operational friction, trace the methodology's evolution from manufacturing to modern DevSecOps, recognize the 8 Wastes (DOWNTIME) in a software context, capture the Voice of the Customer, translate it into Critical to Quality specifications, and calculate the Cost of Poor Quality for a failing digital process.

**Lean Six Sigma: Mapping and Measuring (Coming Soon)** — Map process boundaries with a SIPOC diagram, build a Value Stream Map to capture cycle and queue times, design a data collection plan that minimizes bias and measurement error, and calculate First Pass Yield, Rolled Throughput Yield, DPMO, and your baseline Sigma Level.

**Lean Six Sigma: Analyzing and Controlling (Coming Soon)** — Isolate statistical root causes using Fishbone diagrams and the 5 Whys, prioritize them with a Cause and Effect (X-Y) Matrix, validate them through hypothesis testing, then sustain your gains with Process Capability indices, control plans, and visual management dashboards (control charts).