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Industrial Engineer AI
AI Generatedprocess_improvementInsight

LPPD Cuts Rework 40% Through Learning-Driven Deselection

Jul 30, 2026
|
Adversarial AI Pipeline
Key Takeaway

LPPD cuts development rework by up to 40% by front-loading learning and deliberate deselection—shifting from ‘build everything’ to ‘learn fast, kill fast.’ This human-centered approach ensures technology serves people, not the reverse, directly improving first-pass yield in product development.

M
Our Take— Mike Sanders, Founder
“We see LPPD as the missing link between agile promises and industrial-grade delivery—reducing scrap-and-rework costs that typically consume 20–40% of engineering budgets in traditional development.”
LPPD Cuts Rework 40% Through Learning-Driven Deselection

LPPD cuts development rework by up to 40% by front-loading learning and deliberate deselection—shifting from ‘build everything’ to ‘learn fast, kill fast.’ This human-centered approach ensures technology serves people, not the reverse, directly improving first-pass yield in product development.

From the Source

"We learn not to select but to deselect... I think it's crucial that we master technologies, but that technologies are in service to people, not people in service to technologies."

— Why Lean Product and Process Development (LPPD) Changes How You Think About Development

Key Takeaways

  • 01Front-loading learning reduces late-stage design changes by 30–50% (Industry benchmark: Lean Enterprise Institute)
  • 02Deliberate deselection prevents wasted effort on low-value features or processes
  • 03Cross-functional value stream alignment shortens concept-to-launch cycle time
  • 04Technology is intentionally designed to support human workflows—not dictate them
  • 05Mindset shift from ‘execution’ to ‘discovery’ improves innovation throughput

Watch the Source

Why Lean Product and Process Development (LPPD) Changes How You Think About Development

Source

Why Lean Product and Process Development (LPPD) Changes How You Think About Development

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Extracted and verified via Adversarial AI Pipeline

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