Ability to update manual processes through automation
Industry: Chemicals
Department: Operations
Region: Asia-Pacific
improved chemical catalyst lifespan
increase in revenue via predictive analytics
increase in efficiency
Empowered employees to harness data through democratization
Ability to update manual processes through automation
Improved decision making through quicker insights and a higher level of analysis
“ We wanted to be a solely data-driven organization and move away from making ‘gut feeling’ decisions. We looked to Alteryx for the right tools and expertise. ”
Chatsuda Kanjanarat, SVP Transformation Excellence
Global Chemical
For a chemical reaction to occur at speed and scale within a controlled environment, a catalyst is often introduced into the formula. Catalysts also have the unique characteristic of causing a chemical reaction to happen in a different way. When it came to changing the status quo, the team at GC wanted to move away from doing things the way they’ve always been done.
“We often changed our chemical catalysts at known intervals, simply because that’s how we’ve always done it” said Chatsuda Kanjanarat, SVP Transformation Excellence, GC. “We looked to Alteryx for the tools and expertise to change that.”
Alteryx served as the catalyst for change at GC, starting with its team of engineers, who make up 70% of the entire organization. As they began leveraging Alteryx, they sought out a solution to the arduous task of maintaining and swapping catalysts every five years. By being able to gather the necessary data and analyze it in Alteryx, GC engineers discovered they could extend the life of their catalysts by up to 40%. The result of this discovery allows for GC engineers to effectively save business resources while still producing high quality products.
After working with Alteryx automation for over a year, GC’s team of engineers have begun to leverage the insights powered by Alteryx to drive organization-wide advantages. Olefin and phenol production, GC’s area of expertise, require large amounts of chemical feedstock. Chemical feedstocks are raw, untreated petroleum oil materials. Using their learnings from over the year and Alteryx’s predictive suite of tools, engineers have been able to predict their chemical output, or “yield” as it is more commonly known in the scientific community, to make better feedstock purchasing decisions.
The process was as follows: Leverage sales, production, pricing data, and plant conditions from disparate systems like CRM’s and ERP’s to create a better algorithm that is user-friendly and allows for advanced analytics reskilling and upskilling, and provides deeper insights. The objective was to create a model to predict the price of phenol, which is an organic compound used as an intermediate for industrial synthesis. The team embarked on a year-long proof-of-concept period encompassing:
Leveraging 19 parameters overall, the team evolved from utilizing one Python-driven Linear Regression Model to building an Alteryx driven Random Forest model which allows them to leverage up to 50 parameters with a high confidence interval above 0.95 and an error rate of 2.6%.
Prior to Alteryx, feedstock was purchased when needed and not in a strategic manner. The team now knows when it is best to purchase feedstock and how much, predict their yield, and drive value back to the business while doing so in an innovative and environmentally friendly way. This new process has driven $1.5M to the phenol businesses’ bottom-line.
“ Alteryx makes predictive analytics and the use of machine learning more accessible and agile by switching between many different methods and algorithms with a simple switch icon. You can do this directly on the platform instead of spending time coding an algorithm that does it. ”
Ruj Purnariksha, Digital Transformation Lead
Global Chemical
The GC team is looking forward to making innovations in methanol and propane production, expanding the Alteryx footprint across its different functions, and officially launching the phenol predictive model in September 2021. Driving towards a holistic data-driven culture remains the goal at GC, and the team plans on continuing to upskill their engineers by holding “data days” and “data use case showcases.”