JMP software combines comprehensive statistical analysis with unique graphical interactivity and scripting capabilities that enable everyone in an organization to contribute to the productivity gains promised by Six Sigma.
Graphical Interactivity
JMP makes it easy for everyone in an organization, including those with limited formal statistical training, to analyze data and interpret the results, which are presented in a simple graphical format in one window. Every graph is ‘live linked’ back to data and other graphs. Clicking on any item in a graph highlights the information related to that item in all other graphs that are open and also highlights the information in the data table. Conversely, highlighting a row of data causes the related values to be highlighted in all graphs.
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Figure 1: When the user identifies and clicks on outlier 13 in the deposition metric graph, Thickness, Run #, and related data are automatically highlighted.
Scripting
Scripting records various actions performed in JMP to create an analysis or graph. It is particularly effective when used by content or statistical experts to automate reports and standardize analytical reporting procedures across an enterprise. The captured steps can be replayed later or shared with others who need to do the same analysis in their jobs. The steps are saved as a script that can be associated with a data table or can stand alone. In Fig. 2, the user has captured a script to launch a custom pop-up window where others can enter data and perform a specific analysis. In this example, when a user enters the upper bound value of 1.6 and hits ‘OK,’ the script excludes values of deposition metric and automatically runs the analysis. The script runs distributions that automatically exclude the data associated with Row 13 in the data table based on Upper and Lower Bound values entered by the user. There are multiple options for saving scripts. The user may want to collaborate by sending the data table and analysis steps saved in a script to a second person to check the results against a production baseline at another production site. A script can be run at any time to reproduce a result. In our collaboration scenario, the analyst emails the data table with script attached to another analyst to compare results. Collaboration through scripting in this way minimizes the software training burden and reduces the chances of making the wrong analysis choices that lead to incorrect conclusions. No knowledge of programming is required.
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Fig. 2: The JMP script builds a custom window with a list box and data entry boxes for Lower and Upper Bound values that will be entered by the user. The script then launches the appropriate specified analysis.
Conclusions
The analytical tool chosen for Six Sigma efforts must support three goals: 1) Provide the power of comprehensive analytics 2) Simplify analyses 3) Teach beginners to make process improvements JMP supports these goals with graphical interactivity that makes analysis a visual, point and click process. Scripting in JMP reduces the number of steps a user needs to perform, thereby reducing cycle time and opportunities for error. JMP’s comprehensive analytics accommodate power users who can then deploy streamlined analysis routines to be reused by other practitioners, enabling more people to make business process improvements.
Chuck Boiler
Marketing Strategist JMP, A Business Unit of SAS
