Celebrating JMP Champions: Dan Fortune, Hexion, Inc.
Jun 17, 2020 6:38 AM
| Last Modified: Jul 6, 2020 1:04 PM
Dan Fortune, Global Business Systems Strategy & Growth Manager, Hexion, Inc.
Fun Fact: I am a member of the Classical Mandolin Society of America.
JMP User since 2003
What is your favorite feature in JMP?
Dan's favorite JMP feature is dynamic linking. "I find that it often gives significant insight into what is happening with the data, insight that I might not otherwise get."
If I could only pick one feature, I would have to say that dynamic linking is my favorite feature. This feature is a visual aid that I use all the time. I find that it often gives significant insight into what is happening with the data, insight that I might not otherwise get.
What was your first job (ever)?
My first job after college was as a Quality Assurance Engineer for Texas Instruments. I worked with military electronics and had many opportunities to see cutting-edge technology at work many years before commercial applications were released. Of all the jobs I’ve had, this was the most interesting from a technology perspective.
What is your proudest professional moment?
By using something as simple as multiple comparisons, I was able to identify a difference between inspectors that led to our customer accepting a part that had been designated for scrap. Additionally, this investigation led to recovery of a part that had been scrapped before I started with the company. The financial impact of the customer accepting these parts was approximately $400K. The fact that I was very new in the position made for quick credibility in the group/company and with our customer.
How did you get interested in Six Sigma? Is it something you always knew you wanted to do or were you inspired by someone/something?
My undergraduate degree was in industrial engineering. While Six Sigma is not specifically linked to a particular degree, industrial engineering seems to fit quite well in terms of body of knowledge. My graduate degree was also within the industrial engineering field and focused even more on the statistical side of engineering activities. Perhaps it could be described as a perfect storm of interests, education and work that brought me to Six Sigma. You never know what the future holds and titles aren’t always explicitly descriptive, but it would be hard to imagine my career departing significantly from the body of knowledge of Six Sigma.
What do you like most about the work you do?
Currently, I am involved in R&D work that takes me in many different directions: from the laboratory to the field to the customer. The analytical applications are quite diverse, and there is always a heightened level of anticipation and excitement with each new development.
How are you currently using JMP?
I have recently increased my work with the Functional Data Explorer platform to analyze chemical reactions, as well as spectral and functional results from experiments. This is something that has the potential to become a very important part of our R&D activities.
What is the first project you worked on using JMP?
I’m not certain what the first project was, but the most memorable from my early years of using JMP was using JSL to write simulation using manufacturing and mating part variation to predict usage of fixed-size parts to ensure proper stock level ratios and reduce part shortages in production. This saved quite a bit of money but, more importantly, demonstrated the capabilities and benefits of being able to use analytical tools.
Is there anything you would like to say to JMP development or John Sall?
Keep up the good work and continue to offer more innovative tools so that users can satisfy customers’ increasing analytical needs. Continue to focus on visual capabilities because this feature sells ideas better than numbers alone.
How do you see the field of data science progressing in the next 20-50 years?
The rate of increase in computational capability, availability of data, and analytical algorithm development is at its highest ever. That rate of increase will continue to grow as time passes, making prediction impossible. With that caveat, I would guess that the function of the human brain will become better understood and that its functions and variations will be used in more algorithms. I would expect that increasing connectivity will allow access to more and more data supporting more and more complex algorithms. I would expect specialization in the field of data science/analytics to expand and fuel the acceleration of algorithm development, as well as cross-pollination of ideas across fields. It would not surprise me if these things happen in the next 10 years rather than waiting 20-50 years to take place.
What advice would you give a beginning JMP user?
While its analysis platforms are very powerful, JMP has many capabilities that will speed up your data prep work. In many cases, data prep is the largest part of the work, so focusing on learning the capabilities of the tools in the Tables and Columns menus can really pay dividends. Also, I would suggest that you explore Graph Builder to help you communicate information better. Finally, I would suggest that you take the 30-day challenge. For 30 days, use JMP for everything that you would normally do in Excel. At the end of that 30 days, you may choose not to go back to Excel and your productivity may increase significantly. For certain, your knowledge of JMP will increase significantly.