![]() 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). ![]() When I first began learning JMP, I started with the Friday afternoon live webinars. I only know of one other colleague of mine that utilizes these sessions, and he also encouraged me to get involved! Meagan: Probably the online webinars, which I have really enjoyed and take advantage of constantly. How have you maximized the value you get from JMP? 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. Meg: As a member of the JMP Early Adopter program, you’re a lot closer to JMP than many users are. I could create nice visualizations of results but needed to understand the statistical lingo in order to communicate what I was seeing. The shift in importance of data literacy for me came when I started using the statistical package JMP. 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 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.Īs I continued to learn and understand more about the processes, I was able to realize the importance of data. Meagan: Early in my career as a process engineer, I was introduced to “data” in manufacturing. Meg: What role has data science played in shaping your personal career trajectory? 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: Are there any common misconceptions you run into when it comes to the value of analytics enablement? 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. These services have evolved as a value-add for our customers in order to improve process efficiency and reduce variability. Meagan: Digital services, including predictive analytics, is currently a growth project and new initiative within Kemira. How is the company’s approach to analytics evolving? Meg: Let’s start by talking a bit about analytics culture at Kemira. Meagan is a Lean Six Sigma Black Belt and holds a BS in Chemical Engineering from the University of Arkansas. She has 13 years of experience in the paper industry and previously worked for both AkzoNobel Pulp & Performance Chemicals and Domtar. 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. In her more than seven years with Kemira, Meagan has held multiple roles specializing in chemical sales, process optimization, process engineering and continuous improvement. A leading supplier to water-intensive industries including pulp & paper, water treatment and energy, Kemira is driving global sustainability transformation through innovation in biobased products. Meagan Walker is an Operational Excellence Senior Specialist at Kemira, a Finnish sustainable chemical supplier.
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