Six Sigma Tools: Correlation/Regression Analysis

Many of the organizations that use the six sigma method know that when they move to each next step in the DMAIC process, things can get complicated. Specifically during the analyze phase, there is a need to identify the data that have been gathered during the measure phase. All of the steps need to be followed closely in order to come up with the necessary improvements that will be implemented later on. For this task, using a six sigma tool called correlation/regression analysis would be effective.

Business organizations have to contend with and try to prevent defects and deviations in the well-developed processes that they have introduced upon the establishment of their ventures. Although this can be a normal goal for most business owners, it is still a very challenging task. So, taking these things into proper perspective is essential to come up with the good, well-researched decisions for your business’ prosperity.

It is a fact that the necessary and considerable capital to get a business up and established often causes business owners to  think twice when it comes to how they can possibly address proper resolutions to whatever issues their company is facing now, or well into the future.  No one starts a business with the intentions of closing it down the next year.  All businesses are intended to last well in to the future, but most do not make it for the long haul. Successful business owners know that decisions cannot be made subjectively. If an entrepreneur is to introduce proper resolutions to any defect they are experiencing now, they have to be proven and tested.

This is the reason that proper data gathering is always encouraged when measuring the extent of the defects that an organization is experiencing, and why the Six Sigma quality control system is so deeply rooted in statistics and mathematical accuracy. This is also the time where one is encouraged to gather as much detail as appropriate on what has caused a defect and will likely cause it to worsen in the future. This is essential so decisions will be based on statistical data and not just mere assumption.

When data is gathered in the Measure stage of the DMAIC (or DMADV) process, the variables along with their interrelationships are closely considered and identified. Oftentimes, a scatter diagram is drawn to visualize the strength, the form, and even the direction of any relationship within the independent and dependent variables. Thus, allowing one to determine how interrelated they are (or are not) along the way.

Through this method, the correlation coefficient is then determined; the result will often allow one to quantify a linear relationship. Then a relationship is identified as neutral, negative, or positive. Regression analysis is then used. This is to develop a model that will describe the relationship as a linear one in order to be able to use this information when carrying out predictions and estimations in the future.

It is essential to include uncertainty in the estimates that are being carried out as well. This is especially true when one is testing variables, as well as the relationship between them. This is essential to establish whether the relationship between these variables is indeed statistically significant. If it is established that it is so, then the model can now be established as valid.

Today, six sigma tools, such as correlation/regression analysis, are being used by many organizations to determine business improvements and solutions that they wish to introduce into their organizations. Knowing how one variable affects another and what changes they are likely to initiate as a result is essential. This way, one will be able to project the extent of their quality control efforts once they are fully immersed in the Six Sigma Methodology.