This week’s topics
Big Data Analytics in Supply Networks
- Descriptive, predictive, and prescriptive analytics
- IoT telematics and real-time visibility
- AI-driven demand sensing
- Data governance and algorithmic ethics
- From Data to Decisions: Advanced Analytics & AI in Supply Planning
- Week 07: Lecture 31: Role of AI/ML in Forecasting & Demand Analytics
What you will be able to do
- 3.2 Explain the use and relevance of big data analytical techniques in each of the key areas of supply chain management.
Activity
Start with this week’s 2 videos, then: Seminar, guided reading and a short written task: explain the use and relevance of big data analytical techniques in each of the key areas of supply chain management.
Study materials
Videos
- From Data to Decisions: Advanced Analytics & AI in Supply Planning · YouTube · MIT Center for Transportation & Logistics · 45 min · for registered students
- Big Data Challenges and Opportunities · YouTube · MIT Center for Transportation & Logistics · 63 min · for registered students
- Enterprise Analytics: Achieving Supply Chain Visibility at Scale · YouTube · MIT Center for Transportation & Logistics · 50 min · for registered students
Further resources
- Foundations of Information Systems, ch. 8: Data Analytics and Modeling · PDF · OpenStax, textbook chapter; pp. 297–338 · for registered students
- What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets · PDF · Reading, article · for registered students
- Using Big Data to Estimate Consumer Surplus: The Case of Uber · PDF · NBER, article · for registered students
Materials marked “for registered students” open in the student portal, which is set up as soon as you receive final acceptance.