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Celebrating JMP Champions: Kevin White, Eastman

"While statisticians may not always be in leadership positions, they can influence the people, projects and organizations they serve," says JMP Champion Kevin White."While statisticians may not always be in leadership positions, they can influence the people, projects and organizations they serve," says JMP Champion Kevin White.

Kevin White, Applied Statistics Manager, Eastman
Fun fact: Avid tennis player and plays doubles 100 times a year
JMP user since 1991

What is your favorite feature in JMP?

If forced to pick one, I would go with Custom Design given the nature of the work I’ve done over the years. Custom Design provides incredible flexibility to create and evaluate many types of experimental designs. Process Screening is a newer feature that has quickly become another favorite given its power to quickly evaluate the process stability and capability of many processes.   

What was your first job (ever)?

At 15, I began working at the Baskin-Robbins in the local mall where I learned the proper technique to scoop ice cream that has served me well over the years. When there were no customers, my manager would have us practice weighing our scoops so that we wouldn’t give away too much free ice cream. Knowing what I know today, this would have been some interesting data to collect and visualize using JMP to look at variability within and between scoopers.  To this day, I still have a strong affinity for their World Class® Chocolate flavor. 

What is your proudest professional moment?

I don’t know that I can point to a single moment. For my entire career, I’ve worked as a company internal statistical consultant. Over the hundreds of projects supported, I’ve been anywhere from a pair of hands to what I consider an equal collaborator with the scientists and engineers. The proudest or most satisfying aspects of my career have been on those projects where I was fully integrated with project teams where an idea has been taken from lab scale to production to ultimately selling a new product that our customers value.

How did you get interested in statistics?

I always loved math and started as a math major in college, but ultimately switched to statistics because my dad is a statistician. As I learned more about the work he did, I became convinced it would be a good career choice. I have a daughter who will be graduating from college soon with a degree in business analytics and a son who just started college with plans to major in statistics. I guess you could say it runs in the family. 

What do you like most about the work you do?

While it may sound cliché, it’s helping others gain insight from their data. I think it’s important for statisticians to be humble and take joy in serving others. One of my favorite definitions of leadership is from John Maxwell. He simply says that leadership is influence. While statisticians may not always be in leadership positions, they can influence the people, projects and organizations they serve. 

How are you currently using JMP?

In my current role, I lead a team of statisticians who provide experimental design and other statistical modeling solutions in support of top growth platforms and manufacturing productivity and quality initiatives. We use JMP Pro in about every way imaginable, from creating and analyzing experimental designs to cleaning and analyzing messy data from manufacturing. The interactive data visualization and analysis that JMP Pro provides makes us better and more efficient in the work we do.      

What was the first project you worked on using JMP?

The first project that comes to mind would be my independent project while working on my master’s degree in statistics at the University of Tennessee. My professor connected me with a company that made cake frosting, and the project involved looking at various sites and production lines with the primary goal being to identify differences in key quality characteristics. JMP was my tool of choice because of the ease of creating control charts, comparing process capabilities and analyzing sources of variation.          3color.png

What advice would you give a beginning JMP user?

I would suggest beginning users start with the New User Welcome Kit to get comfortable with the basics of JMP. To learn more about specific topics of interest, then consider the webinars whether they’re live, on-demand, or from the Mastering JMP series. Also, become part of the JMP Community. This is a great place to connect with other JMP users, get your questions answered and join the conversation. And, sign up for the JMP newsletters as this will keep you informed on new webinars, tips, and more. Finally, see if there is a JMP user group within your region or even within your company.  There are many resources available, so try them out and see what brings you value.       

Is there anything you would like to say to JMP development or John Sall?

First, I’m thankful that John Sall had the vision to create this dynamic software 30 years ago. It’s hard to imagine my career without JMP.  Secondly, keep listening to your customers. I was fortunate to serve on JMP’s customer advisory board a few years ago and the thing that impressed me the most was how much the JMP developers listened. This included John Sall who probably took more notes than anyone about potential opportunities to improve JMP. Lastly, keep innovating. Recent JMP releases have continued to improve old features and add new. Keep them coming. It’s always exciting to see what the next version will bring.      

How do you see the field of data science/analytics progressing in the next 20-50 years?

I expect the field to grow fueled by the amount of data available, research leading to improved methods and increased computing power. On the data front we have seen exponential growth in data, and it will only continue. I also expect to continue to see advancements in things like machine learning algorithms and software, making it easier for data scientists to use the methods. And, increases in computing power will allow the processing of large amounts of data faster than ever before. Given my career, I do have concerns about the future of the industrial statistician who is strong in quality methods and experimental design. With many university statistics departments changing their emphasis to data science or analytics, it’s already becoming harder to find people who want to be industrial statisticians. While I understand the allure of being a data scientist, I would not be surprised if somewhere down the road we reach a tipping point and recognize the need for more industrial statisticians.