Syllabus

Title
1614 Course II - Strategic Business Analytics and Investment Decisions
Instructors
Stefan Edlinger-Bach, Ph.D.
Contact details
  • Type
    PI
  • Weekly hours
    2
  • Language of instruction
    Englisch
Registration
09/16/21 to 09/19/21
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Dates
Day Date Time Room
Thursday 10/28/21 09:00 AM - 12:30 PM TC.1.01 OeNB
Thursday 11/04/21 09:00 AM - 12:30 PM Online-Einheit
Thursday 11/11/21 08:00 AM - 11:30 AM TC.0.04
Thursday 11/18/21 08:30 AM - 12:00 PM TC.4.27
Thursday 11/25/21 09:00 AM - 12:30 PM Online-Einheit
Thursday 12/02/21 08:00 AM - 11:30 AM Online-Einheit
Thursday 12/16/21 04:00 PM - 05:30 PM Online-Einheit

Contents

In recent years, the role of managerial accountants has expanded from performing traditional tasks such as classic investment analyses towards providing value-adding insights by tapping into a much broader and diverse set of data. In this course we will mirror this development. More concretely, we will start off by focusing on the traditional role of managerial accountants and deepening our understanding of how investment decisions are made in organizations. We will dig deeper into the assumptions, use cases and (potentially also problematic) consequences of employing several classic instruments for investment decisions. From there, we will explore how data analytics can be fruitfully used to solve a diverse set of problems in managerial accounting. In doing so, we will learn how data preparation, modelling, and visualization can be applied in an accounting context to help create meaningful and value-adding insights in order to prepare and make managerial decisions. We will cover these topics along the following preliminary course structure:

  • Session I: Roles of managerial accountants; investment decisions 1 (foundations of investment decisions, static approaches (recap), dynamic approaches: NPV)
  • Session II: Investment decisions (dynamic approaches: repeating payment, IRR; investment decisions under uncertainty and risk)
  • Session III: Data analytics in accounting; data preparation (fundamentals of relational databases; data dictionaries; extraction, transformation, and loading of data)
  • Session IV: Modelling (common data analytics approaches, regression)
  • Session V: Data visualization (determining the purpose, choosing the right chart, refining the chart, communication)
  • Session VI: Integrated perspective and further application: KPIs (identify the question, master the data and perform a test plan)
  • Session VII: Final exam

Learning outcomes

Overall, this course aims at creating a basic understanding of some core tools in managerial accounting – spanning from classic investment decision approaches to modern data analytics techniques. Regarding the latter, the course is not intended to be a pure analytics/statistics course. It will cover core concepts in data analytics, but always with a focus on applications in managerial accounting.

After completing this course, you should…

  • … have a solid understanding of the theoretical foundations for making investment decisions and a good grasp of how to articulate business problems, identify required data, draw appropriate conclusions, and communicate them.
  • … possess applied knowledge gained from employing the theoretical concepts in case studies.
  • … have acquired useful hands-on skills for managerial accountants (including Excel, querying databases, RStudio, Tableau)

Attendance requirements

Attendance is mandatory in this class. You may miss one class (please let me know in advance!). This also applies to all online units.

Teaching/learning method(s)

This class will make use of a mix of several teaching methods, including

  • Lecture components
  • In-class case studies (each class will incorporate at least one hands-on example/case study – please bring your laptop or share with a partner)
  • Clicker-quizzes
  • Option for individual and group coaching sessions
  • Bonus content (e.g., Excel-tip of the day, etc.)

Note: We will use several different software packages in this course (most of which are free to use for students). I will let you know in advance (two weeks before the start of the course) which software to install.

Assessment

Your final grade will consist of both individual and group components:

  • Final Exam (40%)
  • Group Assignment Case Study (40%)
  • Individual Component (e.g., take-home or classroom quizzes, tbd) (20%)

Grading scheme

  • Excellent ≥87,5%
  • Good ≥75,0%
  • Satisfactory ≥62,5%
  • Sufficient ≥50,0%
  • Fail <50,0%

Prerequisites for participation and waiting lists

Successful application for the specialization “Strategy and Managerial Accounting” (Bachelor in “Business and Economics”) or “SBWL Unternehmensführung & Controlling” (Bachelor in “Wirtschafts- und Sozialwissenschaften” or “Wirtschaftsrecht”); Registration to “Course I - Introduction to Strategy and Managerial Accounting”

Readings

1 Author: Richardson, V., Terrell, K. & Teeter, R.
Title:

Data Analytics for Accounting


Publisher: McGraw-Hill
Edition: 1st Edition
Year: 2019
Type: Book

Availability of lecturer(s)

Last edited: 2021-05-20



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