Course - Introduction to Industrial Economy and Data Analytics - TLOG1015
Introduction to Industrial Economy and Data Analytics
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About the course
Course content
The subject is compulsory in the first year of the study program INGLOG (Program subject 1 identity subject). It should help to provide a good understanding of basic business economics and data analysis. The course consists of a module in managerial economics (50%), and a module in data analysis (50%). The academic content (see the section for learning outcomes) is adapted to logistics engineers' needs for knowledge and skills in business economics and data analysis. Several subjects further on in the study program build on this subject.
Learning outcome
The course conveys the following knowledge to the candidate
- General knowledge of economics and managerial economics
- General knowledge of financial accounting
- Specific knowledge of cost structures and calculations, accounting analysis, investment analysis and transport economics
- Specific knowledge of performance measurement in value chains and logistics
- General knowledge of data types and data acquisition, both quantitative and qualitative
- Specific knowledge of business modelling, break-even analysis, sensitivity analysis, regression and trend analysis, random data, data visualization and interpretation.
- Applications in logistics: Warehouse management (ABC analysis), procurement (EOQ modellen), transport network (From-to Analysis), Quality Management (Pareto analysis, process control), sales and demand analysis.
The candidate must be able to:
- Apply acquired knowledge on managerial economics in analyses and discussions
- Carry out accounting- and investment- analyses using relevant methods and theory
- Assess the choice between different qualitative and quantitative data analysis methods and apply them
- Build simple models in Microsoft Excel, and use techniques to analyze and visualize data
- Carry out break-even analysis, Pareto analysis, trend analysis in a logistics context
- Solve other real problems in logistics with examples from inventory management (EOQ) and planning
Other important learning objectives: The candidate should be able to
- Understand the role of logistics in an overall managerial economics perspective
- Be able to apply data analysis in logistics and value chain management in general and in particular with a view to continued development in digitalization
- Understand the role of digitalization, sustainability and ethics in business operations
Learning methods and activities
Lectures and assignments
Compulsory assignments
- Exercise
Further on evaluation
Written, digital school exam.
6 exercises. At least 5 must be passed to be able to sit for the exam.
Compulsory activity from previous semesters can be approved by the department.
The continuation exam can be changed to an oral exam.
Specific conditions
Admission to a programme of study is required:
Logistics - Engineering (FTHINGLOG)
Recommended previous knowledge
None.
Required previous knowledge
None.
Course materials
To be specified by the start of semester.
Subject areas
- Engineering
Contact information
Course coordinator
Lecturers
Department with academic responsibility
Department of Industrial Economics and Technology Management