2014/2015  KAN-CCMVV4000U  Decision Support and Analysis for Supply Chain Management

English Title

Decision Support and Analysis for Supply Chain Management

Course information
Language	English
Course ECTS	7.5 ECTS
Type	Elective
Level	Full Degree Master
Duration	One Semester
Course period	Autumn
Timetable	Course schedule will be posted at calendar.cbs.dk
Max. participants	40
Study board	Study Board for MSc in Economics and Business Administration
Course coordinator
Arisa Shollo - DIGI Aseem Kinra - Department of Operations Management (OM)
Teachers: Arisa Shollo, Claus Varnes, John Christiansen, Aseem Kinra
Main academic disciplines
Information Systems Supply Chain Management and Logistics Organization
Last updated on 25-04-2014

Learning objectives

At the end of the course the students should be able to: Identify supply chain problems requiring decision support and analysis in the enterprise Identify and use appropriate mechanisms and tools for problem solving in supply chains Use cutting-edge IT tools to analyze supply chain problems and utilize this information in decision-making processes Identify and reflect on the challenges of organizational decision-making in supply chains Reflect on how to make supply chain decisions involving multiple stakeholders, uncertainty and ambiguity

Examination

Decision Support and Analysis for Supply Chain Management: Exam ECTS 7,5 Examination form Home assignment - written product Individual or group exam Individual Size of written product Max. 15 pages Assignment type Case based assignment Duration 48 hours to prepare Grading scale 7-step scale Examiner(s) One internal examiner Exam period Winter Term and December/January Make-up exam/re-exam Same examination form as the ordinary exam

Course content and structure

The aim of this course is to develop the students’ understanding of the organizational challenges when making and implementing organizational decisions in a supply chain context, as well as improve their skills in using IT tools to support their decision-making processes. Which supplier should a company select for a specific order?  Should a company outsource its operations or not? Should a company launch an aggressive marketing campaign that will require substantial resources with no guarantee of success? Which business model is most suited to support the long-term survival of our supply chain? What information technology will best serve the needs of our customer service department? Managers face many important and far-reaching decision situations in their professional life.  Situations where substantial resources need to be committed, where many different stakeholder groups are involved in or affected by the decisions that they make, and where a variety of potential consequences are at stake. Although pure rational models give a simple prescriptive solution to reaching optimal solutions, most decisions to be made in real life, involve humans and their subjective considerations. The aim of this course is to especially bring these considerations out.  To make good decisions fast is becoming ever more important in a world where information is ubiquitous and technologies change at an incredible pace. This class will provide the students with information technology (IT) tools and the conceptual framework to approach these situations with clarity and confidence and improve their decision making skills. Most firms have reached a point where the utilization of IT to support strategic/tactical/ operational decision-making surfaces as more vital than ever. Thus, the course will provide the students with the opportunity to have hands-on experience with cutting-edge software tools and learn how to analyse data and solve supply chain problems. Yet, leveraging benefits from IT systems and tools depends less on possessing and using the technology and more on the ability to best utilize the information in decision-making processes. Therefore, it is important the students understand how decisions happen in organizations and are able to reflect on theories of decision-making and their limitations in practice.

Teaching methods

Research and theory based lectures are mixed with exercises and cases. We will also focus the content of exercises and cases on situations where advances in information technology have led to fundamental changes and new opportunities in supply chain management. In addition, we will hear from guest speakers who are actively involved in applying decision-analytic ideas and tools in the business environment. Several learning methods are blended (general talks, formal lectures, case studies, teamwork onto project development, computer lab sessions, and technical visits) in a set of topics that will promote student engagement.

Further Information

This course is a part of the minor in: IT.Based Management of suppkly Chains and Implementation Changes in course schedule may occur Monday 09.50-13.20, week 45-48 Wednesday 09.50-13.20, week 45-47 Wednesday 09.50-14.15, week 48

Expected literature

Davenport, T.H. 2010, Business Intelligence and Organizational Decisions, International Journal of Business Intelligence Research, 1: 4, pp.1-10. Goodwin P, Wright G. 2010. Decision Analysis for Management Judgment, 4th Edition March, J. 1994. A primer on decision making: How decisions happen. New York: Free Press. Pfeffer, J., & Sutton, R. I. 2006. Hard facts, dangerous halftruths, and total nonsense: Profiting from evidence-based management. Cambridge, MA: Harvard Business School Press. Rousseau, D. M. 2006. Is there such a thing as evidence based management? Academy of Management Review, 31, 256–269. Sahay, B.S., J. Ranjan, 2008. Real time business intelligence in supply chain analytics, Information Management & Computer Security, (16:1), 28–48. Trkman, P., McCormack, K., Valadares de Oliveira, M., & Ladeira, M. 2010. The impact of business analytics on supply chain performance. Decision Support Systems, 49, 318-327. Vaidyanathan, Ganesh & Sabbaghi, Asghar, (2010), “Supply Chain Intelligence and Value Creation: A Framework”. Issues in Information Systems, (9: 1) pp. 570-576. Wixom B., and Watson H., 2010. The BI-Based Organisation. International Journal of Business Intelligence Research (IJBIR) (1:1), pp. 13-28.