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Over the past three years, the MIT Center for Transportation & Logistics has convened a number of roundtables to explore different aspects of Machine Learning and how it impacts the supply chain. Most recently, we explored the challenges of acquiring, preparing and managing the right data as well as the work needed to turn data into the fuel that will run machine learning models effectively and efficiently.
Our most recent roundtables include:
- Data Management: Preparing for Machine Learning (October 15-16, 2019)
- Supply Chain Digital Transformation hosted by Dell (February 26-27, 2019)
- AI/Machine Learning in Supply Chain Planning: Current Applications, Future Possibilities (November 27-28, 2018)
- Blockchain Applications in Supply Chain Management (October 9-10, 2018)
At the upcoming Data Analytics roundtable (March 10-11 in the Boston area and March 24-25 in Singapore), we advance to the application of the data in analytic models, specifically in three main areas:
- Robotic process automation (RPA)
- Predictive analytics
- Prescriptive analytics
Each session will start with a short briefing from an MIT researcher to level-set the topic, followed by a specific example highlighting the industrial application, and then a facilitated, open discussion between all roundtable attendees. Through these sessions, we intend to understand the current practice and challenges, as well as explore what may be expected for the future of analytics and automation.