Edward Chuang
About Edward Chuang
Edward Chuang is the Associate Demand Planning Manager at SC Johnson in Sydney, Australia, with extensive experience in demand planning and supply chain management.
Current Title and Role
Edward Chuang currently serves as the Associate Demand Planning Manager at SC Johnson. Based in Sydney, New South Wales, Australia, his role focuses on demand forecasting, enhancing KPIs like MAPE & BIAS, and educating teams on supply chain operations principles. He identifies inefficiencies in the S&OP process and supports regional teams with statistical models for long-range forecasting.
Previous Experience at Diageo
From 2016 to 2019, Edward Chuang worked as a Demand Planner at Diageo in Sydney, Australia. His contributions primarily involved demand forecasting and planning, collaborating with internal teams to drive business efficiency. The role allowed him to build his expertise in managing supply chain demands within a major consumer goods company.
Entrepreneurial Venture
Edward Chuang was an Independent Business Owner at Hyper Whole Foods from 2015 to 2016 in Sydney, Australia. During this period, he managed various aspects of the business, including operations, supply chain management, and customer relations. This venture provided him with a comprehensive understanding of running a business independently.
Educational Background
Edward Chuang holds a Master's degree in Marketing from the University of Technology Sydney, achieved between 2010 and 2012. Additionally, he earned a Bachelor of Commerce (B.Com.) in Accounting and Finance from the University of Technology Sydney, completing his studies from 2004 to 2008.
Achievement in Demand Planning
At SC Johnson, Edward Chuang achieved a 17% improvement on Bias123 within six months. He also led a significant business transition from planning for stock to planning for ex-factory sales by educating the team on supply chain operation principles. Furthermore, his efforts in transforming the mindset of the local sales and marketing teams have led to improvements in demand forecasting KPIs like MAPE & BIAS.