BAN424 Applications of Business Analytics
In the course we study a number of applications of analytics in real-world problems. These applications include works that have been winner or finalists of world class competitions, such as the IFORS Prize for OR in Development, the INFORMS Franz Edelman Award, and the EURO Excellence in Practice Award, well-known for their high impact in practice. As these applications are described in articles published in scientific journals, the course can help students identifying and formulating relevant problems for their master theses, and to position their work within the literature. Also, acquiring background on high-impact applications may serve as inspiration to apply analytics to improve decision making in their future careers.
The impact of applications can be measured, for example, by how much profits have increased or how much cost savings have been achieved by the implementation of an analytics project at a company. Besides these traditional measures of impact, the scope of the applications can have a much broader scope in society. For example, analytics approaches may help overcoming real-world problems in developing countries, such as improving educational conditions in Latin America or improving access to basic services in Africa. There is also a number of real-world cases reporting considerable improvement in healthcare and public safety. For example, the application of analytics can improve the organ allocation from donors to save lives and help protecting inhabitants of big cities from terrorism and crime. Also, analytics can be applied in sports, for example, to improve tournament scheduling and score predictions.
Overall, the focus of the course is on high-impact applications whose scope of action is not only limited to the traditional min cost and max profit criteria. Through these applications the course will focus on what analytics can do and how analytics can do it, rather than on doing it. As such, we will not get to implement the solution approaches described in these applications but aim at getting familiar with them and understanding them.
By the end of this course the students will
- Be familiar with the application and the impact of analytics in real-world problems.
- Have an overview of relevant analytics techniques and its implementation in real-world problems.
- Be able to understand analytics works published in major scientific journals and formulate relevant research questions.
- Be able to critically analyze and present the main features of real-world problems in analytics and the implementation of methodologies to solve them.
- Be able to locate, select, organize, and document information on a relevant problem, formulate it and propose potential solution approaches based on analytics.
- Be able to communicate key features on analytics such as research question, solution method and answer in a clear manner.
- Be able to exchange views and experiences with others in the field of analytics and thereby contribute to the development of good practice.
The teaching sessions will focus on real-world applications of analytics described in scientific articles. We expect to cover two or three articles per session. In total, the course consists of eight teaching sessions (once per week, from late August until middle October). Students are not expected to understand the details in all articles.
No previous courses are required to follow this course, although it is useful to have previous background (or take courses in parallel) in prescriptive, predictive and descriptive analytics.
Requirements for course approval
A presentation (individually or in groups) on an article from the literature during the course.
Term paper (written individually or in groups).
We will not use specific computer tools, but through the applications under study we will get an overview of computational tools that are useful to solve real-world problems.
Articles that will be made available electronically.
Autumn. Offered Autumn 2018.
Associate Professor Mario Guajardo, Department of Business and Management Science.