Statusmelding

Kun tilgjengelig på engelsk

EBA 3630 Data driven management accounting

EBA 3630 Data driven management accounting

Course code: 
EBA 3630
Department: 
Accounting and Operations Management
Credits: 
7.5
Course coordinator: 
Elisabeth Plietzsch
Course name in Norwegian: 
Data driven management accounting
Product category: 
Bachelor
Portfolio: 
Bachelor of Business Analytics - Programme Courses
Semester: 
2022 Spring
Active status: 
Active
Level of study: 
Bachelor
Teaching language: 
English
Course type: 
One semester
Introduction

Management accountants have for many years been the drivers of analysis for decision-making in most organisations. Previously using reports from internal ERP systems, management accountants have extracted data, conducted spreadsheets, manual analysis, and arrived at a basis for providing relevant information to key decision-makers.

With the vast increase in available data, the management accountant is forced into a world previously hosted by computer scientists. In many cases, management accountants now have to extract the data themselves from various locations, filter and regroup data themselves, and then perform analysis to shed light on current decisions. This course intends to show how data from various sources within companies can be used to perform such tasks as cost estimation, variance analysis, performance measurement and to conduct forensic accounting.

Learning outcomes - Knowledge

During the course, students should have learned/acquired knowledge of:

  • The importance of external and internal data sources to solve management accounting problems
  • Relevant management accounting tools 
  • How to translate management accounting problems into Python Code and/or other relevant programming languages
  • How to use data for management decision making
Learning outcomes - Skills

After completing the course, students shall be able to:

  • Identify relevant data 
  • Scope a management accounting problem
  • Apply the correct management accounting tool
  • Ttranslate management accounting problems into Python Code and/or other relevant programming language
  • Conduct financial accounting forensic analysis
  • Communicate and interpret the results of using management accounting tools
  • Derive recommendations for actions based on their analysis
General Competence
  • Evaluate the meaningfulness of certain types of data to the problem being analyzed
  • Understand the benefits and limitations of certain management accounting tools
Course content
  • In-house data
  • ERP systems
  • External relevant data
  • Extraction of data
  • Decision analysis
  • Management science
  • Cost estimation for various profitability calculations
  • Customer profitability analysis
  • Accounting forensics
  • Predictive analytics
  • Optimisation techniques 
  • Visualisation of management accounting analytics
Teaching and learning activities

The course will consist of a mix of lectures and workshops where students do on-hand analysis. Students are expected to use Excel, Python and SQL to solve problems.

Software tools
Software defined under the section "Teaching and learning activities".
Qualifications

Higher Education Entrance Qualification

Covid-19

Due to the Covid-19 pandemic, there may be deviations in teaching and learning activities as well as exams, compared with what is described in this course description.

Teaching

Information about what is taught on campus and other digital forms will be presented with the lecture plan before the start of the course each semester.

Required prerequisite knowledge

Students are expected to have a fundamental understanding of Excel, Python and SQL programmes/languages, and had fundamental courses in management accounting and financial accounting.

Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
EBA 36301
Grading scale:
ECTS
Grading rules:
Internal and external examiner
Resit:
Examination every semester
100No72 Hour(s)Individual
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:100
Invigilation:No
Grouping (size):Individual
Duration:72 Hour(s)
Comment:
Exam code: EBA 36301
Grading scale:ECTS
Resit:Examination every semester
Type of Assessment: 
Ordinary examination
Total weight: 
100
Student workload
ActivityDurationComment
Teaching
20
Seminar groups
16
Prepare for teaching
100
Student's own work with learning resources
14
Examination
50
Including exam preparation
Sum workload: 
200

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.