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The Flow of Discovery: Automating the standard paths and enabling the non-standard paths

John Sall, Founder and Chairman, JMP

Ryan Lekivetz, Manager, Advanced Analytics R&D, JMP

Rebecca Lyzinski, Clinical Research Developer, JMP

Aurora Tiffany-Davis, Principal Software Developer, JMP

Mandy Chambers, Principal Test Engineer, JMP


JMP is built for discovery, but discovery is not just happening to see something in a graph; it usually involves a lot of work and many process steps.  The problem is that the steps are not always the same in each situation or in each set of data – the analysis has to be interactive. You must be able to pursue clues, identify things, drill down to details, and adapt to new conditions.


The analytic process is fundamentally interactive, and JMP supports interactivity.  But there can be “easy buttons” along the way, and you can create your own “easy buttons” for the steps that you plan to take again.


Whether your work can be planned or is a wild path of exploration and serendipity, JMP has the modes to make your work speedy, efficient and productive, while keeping you in an environment of discovery.



Great concept & tool! I am integrating it in my DOE teaching and training course. Before designing the experiment, training people to first focus on defining the experiment goal with the associated model is essential.

I have a couple of remarks:

1. There should be one extra step before reporting: DOE validation; extra runs are necessary to check DOE performance.

2. I propose to standardize the workflow step terminology: here it is different from JMP easy DOE and the tutorial.