Hello everybody, welcome to supply chain analytics. This is Dr. Yao Zhao. I’m a professor in supply chain management at Rutgers Business School. This is the overview of the course, where I will discuss two topics. First, “Why Supply Chain Analytics? Second, the takeaways and course requirement. So, what is supply chain analytics? Supply chain analytics in plain words is where analytics meets supply chain management. It is an emerging area that aims to apply data analytics to supply chain management to generate a significant social and / or economic impact. A supply chain is a complex network of companies that meets demand by supplies through many stages from raw material and components factories, to assembly and packaging plants, warehouses and stores. It largely determines customer satisfaction, and thus, revenue and cost of goods sold and operating cost for many firms. Supply chain is always data-rich, the complex flows of materials and money through network often generate a large amount of data every day. Analysis and effectively use of this data can significantly improve revenue and cost efficiency and thus provide the company a long-term competitive advantage. However, a major hurdle for many companies to achieve their potential supply to analytics, is the talent crisis. A significant shortage of talent who have both the supply chain domain knowledge and the data analytic skills. For example, the automotive industry Brief 2015 shows that the demand-to-supply ratio of supply chain jobs to qualified individuals is six to one. Suddenly, supply chain management became more complex than ever. A number of people who handle it were a few. Now, the key drivers, as another article from supply chain dive pointed out are the technology explosion and global expansion. Big Data may put early adopters an advantage but without talented analysts, Big Data is just a pile of numbers. Meanwhile, misinterpreted data or wrong use of the data can do harm to companies. This course is designed to demonstrate the potential of supply chain analytics and train talents with the ultimate goal of filling these jobs. Upon completion of this course, you will be able to first understand why analytics is critical to today’s supply chains. Second, to see the pain points of various domains, that is functional areas, of a supply chain and how analytics may help to address them. Third, to understand the requirements of supply chain analytics jobs and how to prepare for them. Finally, assess one company’s overall supply chain efficiency quantitatively. This course has four weeks including a project at the end. In week one, we shall demonstrate how supply chain management can create a long-term competitive advantage through real-life examples. In week two, we first distinguish various domains of supply chain and then show typical problems in each domain, and how to use analytics to solve them. We shall also discuss job opportunities, requirements, and preparation. In week three, we’ll show inventory measures and cash conversion cycle and how to use them to assess supply chain efficiency. In week four, we’ll put the learnings to test by conducting a project on real data to compare supply chain efficiency between Apple and Samsung. So, this course requires a time commitment of about 2.5 hours a week, and we shall use MS Excel for the analysis. This course can be used for: For those of you who are exploring a career in applying analytics to supply chain and operations management, and those of you who want to understand the pain points of a supply chain and how analytics can help to address them. Also, those of you who are fascinated by the potential of supply chain analytics and hope to understand its social and economic impact. This course is designed for beginners with no prior experiences. However, it will be helpful if you have some knowledge or experiences in the following areas such as: Supply chain management basics, say for instance, the Supply Chain Management Specialization offered by Rutgers University, general business concepts, and basics of spreadsheets.