Role, Responsibility & Task of JMP Team

Question

HI all,
For large customers, you may find that they have a dedicated JMP team internally. 
I'd like to know Role, Responsibility & Task of JMP Team.

Korea's largest customer has two departments working on JMP. 
Of course, the teams doesn't do just JMP-related work like a typical data science team.
One is the R&D data science team in the data science lab.
There are several teams in the data science lab, but since JMP is used the most in the R&D area in the case of that company,
   that team is in charge of JMP-related work.
The team's main tasks related to JMP are data analysis using JMP, JMP customizing (script, add-in development, internal system interface), JMP-related internal consultant, internal JMP Tech support, etc.
The other team is the Digital competency team. The team is responsible for JMP training, data analysis capability enhancement using JMP, JMP contract, etc.

Anyway, I'd like to know to Role, Responsibility & Task of JMP team in another company (e.g. TELA account). 
And also I hope that I could hear from you on Role, Responsibility & Task, organizational structure, etc. of the JMP team.

Thanks
Ikju

IkjuShin · Answer

Hi Bill,
Thank you for your comment.
There seems to be little misunderstanding. They are TELA customers. All employees can use JMP, and the team is responsible for managing JMP in the company and supporting internal JMP users.
They(Data Science Lab) are using both JMP and Python(R seems to be less popular than before)
I think that JMP excels in two ways;
1. JMP has outstanding advantages as a common language and common tool that all members of the company can use.
2. JMP has excellent advantages as a business communication tool to communicate with buyers and suppliers.
These two are the advantages of JMP that cannot be compared with other products such as Python and Minitab etc., I think.
They(Data Science Lab) seem to think so too.
Thanks
Ikju

martindemel · Answer

Hi Bill, I think the "internal use only" story about Rolls Royce Meg has written has some nice arguments on that. One was an internal challenge where JMP outperformed Python/R

Bill_Worley · Answer

Hi Ikju,

You mention that the Data Science Lab is using JMP.   Based on what I have experienced (others please weigh in) you are quite lucky to have a data science team that even considers JMP as a viable option.  Most data scientists in the U.S. do not consider JMP as a viable option for one main reason and that is "big data".   The consensus among data scientists here is that JMP cannot handle big data and is therefore not an option for their work.

A nice success story that we could share or at least learn from internally would be great. Would it be possible to let us know how the Data Science Lab is using JMP and where they have had success using JMP in conjunction with, or as opposed to tools like Python and R?

Best,

Bill