Using Data to Do Things Better

Posted 15th January 2019

Thanks to a long-term relationship with a respected technology focused collaborative research centre, recent CMU-A graduate Zhaohan Wang (MSIT S18) got to work on a big data project to unlock the mystery of brewing the perfect beer.

As part of the South Australian Government’s Big Data Connect project, Coopers Brewery worked with the team at Data To Decision (D2D) CRC to unearth insights from their data to improve the quality of one of their flagship beer products.

Zhaohan Wang was selected to join the D2D team to provide data analytics support. Zhaohan had completed a Master of Science in Information Technology at Carnegie Mellon University in the Business Intelligence and Data Analytics track.

It’s inspiring what data analytics can do to deliver business improvements…and in our case…a better beer for current and future Coopers beer drinkers

Carnegie Mellon MSIT graduate Zhaohan Wang, D2D CRC lead data scientist Dennis Horton and Coopers supply chain manager Dr Jon Meneses.

Cooper’s Brewing & Supply Chain Manager, Dr Jon Meneses explains that market success is driven by the ability to deliver a consistent product for consumers.

“The bottom line is, we need to understand, manage and control the inputs and processes so as to ensure not just the quality of the product, but that it is always the same, day-in-day out, year-in year out", said Dr Meneses.

“The challenge for all manufacturers is how to do this when there will always be ingredient seasonality and variations to the brewing process.

“Our team came up with the top 10 parametres which can positively and negatively affect the quality of our beer.

“Getting the data is easy, turning it into knowledge and deliverables is the big challenge", said Dr Meneses.

Coopers Brewery plant, South Australia

In mid-2018 Coopers Brewery joined the South Australian Government’s Big Data Connect project to develop an algorithm which would highlight important characteristics of the brewing process to ensure a consistent final product even when elements changed.

The D2D project team, led by D2D CRC’s Lead Data Scientist Dennis Horton, built a model that could estimate important features of final product quality by factoring in characteristics of the raw ingredients and process settings.

“Using various machine learning techniques, we were able to interrogate process settings and ingredient characteristics to highlight which features were most important in the processing cycle", said Mr Horton.

“Given the complexity of the brewing process and the variation in raw ingredients, it can be difficult to know which components have an impact on product quality.

“By applying cutting edge data analysis on routinely collected data, the team were able to formulate valuable insights that will help ensure high quality outputs", said Mr Horton.

The next step is for the Cooper Brewery Continuous Improvement team to assess the model for possible adopt it into the brewing process.

While we have a great product, we are always looking for ways to improve and do things better", Dr Meneses said.

“Being involved in the Big Data Connect project was a great experience and the outcome has the potential to deliver measurable results for Coopers.

“It’s inspiring what data analytics can do to deliver business improvements…and in our case…a better beer for current and future Coopers beer drinkers", said Dr Meneses.

Coopers Wareshouse

  • Category
  • Region