Six Sigma – Measuring with Continuous or Discrete Data

Six Sigma provides many tools for transforming data into actual information that can be used to improve various aspects of a company. As you go about doing this, you begin to realize the importance of how the data should be measured. This is one of the factors that will help you clearly understand how it should be transformed and what will take place after this has been accomplished. The Six Sigma measurement technique refers to the type of data that is to be measured within a particular process.

The data measured for any Six Sigma project is important because it can indicate the seriousness of a problem that exists as well as its magnitude. Investigating the problem in the context of the process you are measuring is what will help you improve the overall process. Different measurements will help you gather different data. These would include: the length of time it takes fore a process to be executed, the count of defects produced within the course of a day, or the dimension on a particular product part.

Continuous data is one type that is measured on a regular basis. Continuous data can assume a range of numerical responses on a scale that is continuous, hence its name. It is also known as variable data. Since it can be used to measure a wide range of values, the slightest defect can be detected as well as measured, and then used for improvement purposes.

There are two types of continuous data. They are physical property data and resource data. Physical property data will depict the tangible aspects of a process. Examples include: weight, width, length, height, and temperature. Resource data, on the other hand, details the assets related to a particular process. This type of data would include both time and money.

Another type of data that is important to the measurement of many processes is discrete data. Discrete data is the presence or absence of a characteristic in each device that is being tested. It is also known as attribute data and contains an either/or quality. There are three types of discrete data. One is characteristic data. This type of data details the attributes of a particular process. Measuring the number of break/fixes within a network issue would be an example of this type of data. Count data is another type that depicts the number or frequency of an event that is observable. This type of event would be measured as it occurs within a particular process. This type of data is commonly used to measure defects. Intangible data is the third type. This illustrates a part of the overall process that is intangible. An example of this would be measuring a person’s feeling about something on a scale from good to bad or high to low.

The types of data listed above are often used in a number of different processes to solve problems within the Six Sigma Methodology. They can even be used to detect them before they become problems which will improve overall productivity.