Transforming Supply Chains Through Analytics
Supply chain management relies heavily on data analysis and real-time decision-making to respond to rapidly changing environments. Large amounts of data are consistently generated at every stage of supply and retail chains. The information extracted from this data is critical to all aspects of planning—from forecasting demand to scheduling production to managing transportation and distribution.
Manufacturers and retailers are under great pressure to leverage this data to make their complex supply chains more responsive, agile and cost-effective. But the decision-making tools commonly used in retail and supply chain industries are out of date, and generally cannot be adapted to make use of the volume of new data or make decisions in real time.
Dr. Yossiri Adulyasak, Canada Research Chair in Supply Chain Analytics, is working to come up with predictive and decision analytics solutions that use operations research and machine learning techniques. By anticipating the conditions that are likely to lead to problems—and promptly proposing responses—these solutions will enable supply chain systems to be much more proactive.
Adulyasak and his research team aim to enable the seamless integration of planning and real-time execution. They also want to provide supply chain resilience through risk mitigation planning and contingency execution and create supply chain intelligence that learns and adapts to dynamic environments.
Their research will contribute to the analytics market, which is projected to be a $200 billion industry by 2020. Ultimately, it will help Canadian businesses compete globally.