In her more than seven years with Kemira, Meagan has held multiple roles specializing in chemical sales, process optimization, process engineering and continuous improvement. Her current focus, as part of the Operational Excellence team, is on big data analysis and predictive analytics to provide solutions based on the chemical, mechanical and digital environment. She has 13 years of experience in the paper industry and previously worked for both AkzoNobel Pulp & Performance Chemicals and Domtar. Meagan is a Lean Six Sigma Black Belt and holds a BS in Chemical Engineering from the University of Arkansas.
Meg: Let’s start by talking a bit about analytics culture at Kemira. How is the company’s approach to analytics evolving?
Meagan: Digital services, including predictive analytics, is currently a growth project and new initiative within Kemira. These services have evolved as a value-add for our customers in order to improve process efficiency and reduce variability. We feel that our strength is in our troubleshooting methodology, which relies heavily on data analytics with the use of process expertise and data results from our control and monitoring equipment.
Meg: Are there any common misconceptions you run into when it comes to the value of analytics enablement?
Meagan: I hear people say that they “don’t trust the computers to spit out all the answers because it is just a black box.”
Meg: What role has data science played in shaping your personal career trajectory?
Meagan: Early in my career as a process engineer, I was introduced to “data” in manufacturing. The goal at the time was to collect as much data as possible into Excel and then spend hours building thousands of graphs and control charts to monitor the process.
As I continued to learn and understand more about the processes, I was able to realize the importance of data. Listening to operators tell me what happened during a night shift was great but being able to visually see it with data was enlightening.
The shift in importance of data literacy for me came when I started using the statistical package JMP. I could create nice visualizations of results but needed to understand the statistical lingo in order to communicate what I was seeing.
Meg: As a member of the JMP Early Adopter program, you’re a lot closer to JMP than many users are. I’m wondering if there is anything that sticks out to you as an aspect of the JMP community that you feel people are underutilizing. How have you maximized the value you get from JMP?
Meagan: Probably the online webinars, which I have really enjoyed and take advantage of constantly. I only know of one other colleague of mine that utilizes these sessions, and he also encouraged me to get involved!
When I first began learning JMP, I started with the Friday afternoon live webinars. I set a reoccurring event in my calendar for every Friday and registered for whatever session was taking place, regardless of the training level (basic, intermediate, advanced).
I first started picking up – learning – the language of JMP. For example: data table, continuous vs. nominal data or character vs. numeric data, red triangles, Data Filter, Tabulate, Graph Builder, Control Chart Builder, scripting…. I kept up with the Friday sessions and would practice new tricks that I learned every time I used JMP. As I got more comfortable with the basics, I began to skip out on the basic Friday sessions and would instead watch a more advanced webinar that was available on-demand on the website. But I still prefer the live sessions to pre-recorded ones!
When I first found the online webinars, [Community Manager] @Gail_Massari had posted a very nice list of available sessions at the time – broken down by training level – so I printed it out and started going down the list one at a time. I started with the basic webinars (most of which I had already seen live) and then moved onto the intermediate ones. I like to check off lists, so I checked off each session that I finished. The basic sessions helped me build a foundational knowledge of JMP, but the intermediate sessions have allowed me to understand the power of JMP with respect to statistical data analysis, process control and modeling.
I still have a standing appointment on Fridays for JMP training and one day will finish the original list that Gail posted over two years ago, although there are so many new training sessions that it is hard to keep up!
Meg: What advice would you give to someone who is just starting out with JMP?
Meagan: Take advantage of the webinars! Start with the basics and work your way up…
Right off the bat, I really took a liking to Graph Builder, especially the drag-and-drop feature. I was fascinated with the ability to make multiple charts extremely quickly with just a few clicks… and then I learned about Column Switcher! Mind blown! That is how I began to understand the power of JMP’s visual platforms… for me, the ability to visualize statistics and share it with others was powerful.
Meg: What advice would you give to students looking to pursue a career similar to yours?
Meagan: I personally had very little programming/coding, data science or statistical training as an undergraduate student majoring in chemical engineering. I would recommend students pursue any additional training they can get in those fields while still at university.
And of course, understand the null hypothesis!
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