In order to make the most appropriate changes, Six Sigma professionals first gather huge amounts of data related to the business process selected for improvement. The collected data is then sorted out and classified based on the overall value that a particular dataset contributes to the business process. A dataset is simply a part of the collected data relating to a specific sub-process of the given business process.

This type of classification is necessary because it enables Six Sigma professionals to concentrate on sub-processes that add the most value. It would be a waste of precious time and resources if the entire data were to be analyzed. After identifying and classifying the important datasets, the next step relates to their analysis, which helps in identifying the most crucial factors affecting the business process. The analysis is done by comparing past and present datasets and by utilizing advanced statistical tools, techniques and methodologies.

Finding The Most Appropriate Quality Improvement Solutions

After identifying the crucial components of the business process, Six Sigma professionals conduct brainstorming sessions with representatives from the staff, middle-level management, and the top management in order to seek quality improvement suggestions. All the suggestions are then given a definite shape and passed through the Six Sigma testing process.

Advanced statistical software systems are used in the testing process for selecting the best quality improvement suggestions. The selected quality improvement initiative is then made to undergo further testing and refinement, before it is actually made available for implementation.

Checking The Effectiveness Of Implemented Quality Improvements

It is highly unlikely that a quality initiative that has passed such rigorous testing will fail to achieve the desired results - but since there is always a possibility of error, organizations can never overlook the need for implementing appropriate checks and controls. Additionally, since there is always a chance that the selected quality initiative may deliver results far below what was expected, organizations need to put in place control systems so that deviations, if any, can be accounted for.

These control systems use statistical tools for comparing actual results with the expected results, enabling Six Sigma professionals to keep a tab on the effectiveness of the implemented changes and to take immediate action if anything goes drastically wrong. The control system also helps in identifying and rectifying minor problems that can prove disastrous after a certain time if allowed to grow unhindered. It is only when proper control systems have been set up, can the organization hope to derive the maximum benefits from the implemented changes.

Thus, we can see that thinking statistically is not a choice but a compulsion or necessity for Six Sigma professionals. As business processes grow more and more complex, the need for statistical tools and techniques as well as qualified professionals will be felt even more in the near future.