Most continuous improvement programs fail within 18 months. The reason is almost always the same: leadership started by avoiding bad Six Sigma projects the wrong way. Instead of using data, they used gut feeling.
In this episode of the Why They Fail Podcast, host Kevin Clay sits down with 40-year CI veteran Wade Harper. Together, they expose the systemic failures behind poor project selection. More importantly, they show what a disciplined, data-driven deployment actually looks like.
Wade's career is built on real-world results. He engineered nuclear weapons components under Six Sigma pioneer Michael Harry at AlliedSignal. He then rose to Master Black Belt roles at Ford and Honeywell. Additionally, he led the largest Lean Six Sigma deployment in U.S. Army history. All resources, tools, and links discussed in this episode are available at Wade's website: https://ameripie.com/
Avoiding bad Six Sigma projects starts with understanding why good leaders make poor choices. Most executive teams do not lack ambition. However, they consistently avoid the hard work of establishing clear performance standards.
As a result, corporate deployments measure success using vanity metrics. Total people trained. Total certifications issued. These numbers look impressive. Unfortunately, they say nothing about bottom-line value created.
A newly appointed CI practitioner then gets sent off to tackle arbitrary projects. There is no data infrastructure. There is no clear problem statement. Therefore, the project is set up to fail before it begins.
Every project charter must be grounded in hard numbers. That is the foundation of avoiding bad Six Sigma projects. Emotion and workplace pain are not valid starting points for a deployment strategy.
One of the most costly mistakes in any CI deployment is optimizing a non-bottleneck step. For example, fixing step three in a seven-step process may look compelling in a presentation. However, if step three is not the true constraint, output at the door does not change. The financial return is zero.
Furthermore, when baseline data is absent, executives default to a destructive pattern. They begin managing people instead of managing process capabilities. Consequently, employees get blamed for failures that are actually structural and systemic.
Shingo-style process mapping is one of the most effective tools for solving this problem. It separates flow from work in a way that traditional value stream mapping does not. As a result, transactional and service teams gain the granular visibility needed to isolate defects before they move downstream.
Applying these principles consistently is what separates high-performing CI programs from failed ones.
First, every project charter must be grounded in baseline operational data, not emotion or workplace pain. Second, program success must be me...
