URL study guide
https://studiegids.vu.nl/en/courses/2024-2025/E_ACC_AMACourse Objective
This course provides an overview how organizations structure and use data-analytics in managerial decision making. During the course we discuss a set of academic papers, and explore a number of empirical data-analytic cases how controllers analyze both financial and non-financial information to improve decision making processes (Bridging theory and practice-knowledge and application; Broadening your horizon – IT). After following the course, you should be able to: -Use data-analytic methods for among others creating prediction and optimization models, analyze leading and lagging relationships, explore different types of cost behavior patterns, and create performance dashboards. -Read and understand academic papers and be able to formulate why results of these papers are informative for practical decision making. -Discuss how controllers play an important role between data-scientist and managers to create valuable insight to improve decision making.Course Content
Business controllers are more and more intermediates between 1) managers that are responsible for making decisions to execute the organization strategy, and 2) data scientists that structure and analyze a broad set of financial and non-financial information from different sources. In the course we therefore focus on analyzing data analytic cases to create insights for managers to improve their decisions. Students will work with pre-specified datasets that include firm data, such as, sales, costs, customer satisfaction, and third party data. In addition we cover questions such as: What skills do controllers need?, How is such big data created and structured?, Which additional data would be valuable to create value?Teaching Methods
After a web lecture that introduces the weekly topic, the literature is discussed during an in class lecture. During the tutorial empirical cases are discussed to explore the data-analytic methods. Python will be used as the main programming tool to execute these analysis. The weekly individual assignments cover the same topics that are explored during the tutorial. Since Python is used during the tutorials and necessary for the individual assignments students should follow the DAAC course first.Method of Assessment
*Digital exam *Individual assignmentsLiterature
A selection of academic papers, to be published on Canvas.Target Audience
This elective course is interesting for students of the accounting and control master that would like to get more hands one experience with data-analytic cases in a management accounting and control context. In addition the elective is open for other master students that have already some experience with data- analytics and want to broaden their knowledge by learning how to use this for management accounting and control decision making.
Entry Requirements
The course assumes an understanding of management accounting at intermediate level. This is usually equivalent to an introductory course (level 100) plus an intermediate course (level 200 or 300) in the area of management accounting. In addition the student is expected to have experience with Python programming language. We will assume basic knowlegde how to re-structure datasets, and execute statistical analysis such as providing descriptives and regression analysis.Recommended background knowledge
The course assumes an understanding of management accounting atintermediate level.Language of Tuition
- English
Study type
- Master