ØAL119 Supply Chain Management - Innkjøp og Distribusjon

Contents and structure

This course covers the management and coordination of activities related to procurement, distribution, and data-driven decision support within the supply chain.

The course provides an introduction to how data analysis, business intelligence (BI), and basic machine learning methods can be used to understand and improve decision-making in procurement, transportation, and inventory management.

Through practical work in Python, Jupyter Notebooks, and Power BI, students learn to collect, analyze, and visualize data to support evaluations of supplier selection, demand, and quality within the supply chain.

Learning Outcome

Knowledge

Upon completion of the course, the student should be able to:

• Explain key concepts related to procurement, distribution, and data-driven logistics in supply chains.

• Describe how basic machine learning and statistical methods can be used to support decision-making in procurement and distribution.

• Explain how data collection, analysis, and visualization contribute to efficiency and quality in the supply chain.

• Describe how BI tools and data governance support decision-making and reporting.

• Reflect on ethical and sustainable perspectives related to the use of data and technology in supply chain management.

Skills

Upon completion of the course, the student should be able to:

• Use Python and Jupyter Notebooks for basic analysis and visualization of procurement and distribution data.

• Perform basic data cleaning and preprocessing (data preparation) to improve the analytical foundation.

• Develop simple models for demand forecasting and risk assessment using linear regression or classification.

• Build a Power BI dashboard displaying relevant KPIs for procurement and distribution.

• Collaborate in teams on data-driven case studies and present results in a clear and action-oriented manner.

General Competence

Upon completion of the course, the student should be able to:

• Understand how data-driven analyses contribute to more efficient and sustainable decision-making in procurement and distribution.

• Reflect on ethical and societal implications of using data and algorithms in operational practice.

• Contribute to digital improvement and innovation in supply chains through the application of simple analytical tools.

• Develop awareness of lifelong learning and the need to continuously update digital competence in response to technological developments.

Entry requirements

Passed ØAL118 and ØAL121.

Recommended previous knowledge

Prior knowledge in business economics is an advantage.

Teaching methods

Classroom teaching and assignment seminars combined with group work. Group-based guidance as needed.

Compulsory learning activities

• 1 group-based compulsory work requirement (semester assignment) must be passed before an examination can be taken.
• 1 group-based oral presentation of the compulsory work requirement (semester assignment) must be passed before an examination can be taken.
• Mandatory attendance at assignment seminars

A total of 3 compulsory work requirements

Assessment

Written school exam, 4 hours

The time and place for the exam will be announced on Studentweb.

Grade scale A-F, where F corresponds to fail.

Examination support material

None

More about examination support material