Some organizations make use of various project improvement methods. As a Six Sigma expert, you might have to champion your own method on occasion. Here are some reasons to choose Six Sigma over other methods described in this part.
1. When facing the unknown
Six Sigma is designed so you can begin a project even when you don’t know the cause of the problem. In some cases, teams aren’t even sure what the exact problem is – they only know some metric is not performing as desired. For example, an organization might experience a drop in profits that doesn’t correct itself in several consecutive quarters. Six Sigma methods can begin to seek the causes of the problem, prioritize them, and work toward solutions.
2. When problems are widespread and not defined
Even when a problem is understood, if it is wide in scope and not well defined, improvement projects that are not tightly managed can escalate in scope to a point that they become unmanageable. In this situation, teams attempt to solve increasingly bigger issues. As a result, no problem is ever completely solved. Six Sigma includes controls for avoiding such scope creep so teams can make incremental improvements that steadily improve a process over time. We’ll talk about scope creep more in later chapters.
3. When solving complex problems
If processes are complex and feature many variables, it is difficult to determine how to approach a solution, much less define, and measure success. Knowledge of statistical analysis and process control lets teams approach problems that involve enormous amounts of data and many variables. Through analysis and a graphical representation, complex ideas can be distilled to specific hypotheses, premises, and conclusions.
4. When costs are closely tied to processes
Because Six Sigma’s statistical process control component lets teams make more accurate assumptions than almost any other method, it is very appropriate for situations that are closely tied to revenue or cost. When a single tiny change can result in millions of dollars in gains or losses, teams must validate assumptions with an extremely small margin of error. Guesswork, basic research, and even years of experience cannot do that as accurately as properly implemented Six Sigma methods.
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