The explosive growth of Six Sigma methods in diverse industries has created a huge need for software to automate statistical analysis. Selection of the best tools for your company can be difficult.
As illustrated in Figure 1, a typical business uses three broad categories of software applications. At one extreme are general purpose applications, such as Microsoft® Office and Lotus Notes. These applications are used by everyone and are typically selected by a central IT department.
At the other extreme are specialized analysis tools used by only a few people for highly technical tasks. These applications are typically selected by users who have the advanced training to understand the methods.
In the middle are analytical automation tools. These are used by a broad base of people who want quick answers to tough problems. Those who select, purchase, and use these powerful tools may not be analytical experts, so these tools must be easy to learn and use.
This paper provides an overview of two leading statistical automation tools, Minitab® and Crystal Ball®. For engineers, scientists and anyone who works with data, Minitab and Crystal Ball provide complementary capabilities for the automation of statistical tasks. Minitab is a comprehensive statistical analysis application, while Crystal Ball runs and analyzes simulations of models representing physical systems. Both tools are easy to learn and have developed large, international user bases through a wide range of industries.
This paper describes the different types of problems Minitab and Crystal Ball are designed to solve. The major capabilities and features of each application are reviewed. Finally, the paper describes a case study in which both applications are used together to optimize the design of a new product.
Why Statistical Analysis and Simulation are Important
Statistical methods were invented as tools to explain and predict phenomena observed in the natural world. Models developed through these methods have become essential aspects of business and science. For example, to design a product, an engineer relies heavily upon models of physical systems. To assess a business plan, an accountant uses models of economic and human systems.