 | | |
| Version 2012-2013 |
|
| INFO0934-8 | Management Information Systems
|
|
| Duration : | 45h Th |
|
| Number of credits : |
|
|
| Lecturer : | Ashwin Ittoo |
|
Language(s) of instruction :
|
| English language |
|
Course contents :
|
| Information Systems (IS) are systems that encapsulate both the technical aspects of Information Technology (IT) as well as the social ecosystem, such as society or companies, within which the technology is embedded. It has been widely established, both from practical experience and from theoretical studies, that the proper management of IS (MIS) is one of the key determinants that enables organizations to acquire a competitive edge.
The aim of this course is to equip students with the fundamental skillsets in MIS for their future professional (e.g. consultants, managers) or academic (e.g. doctorate) careers. It addresses the topic of MIS by adopting both a theoretical and practical perspective. Students will be exposed to classical themes in MIS, such as Enterprise Resource Planning, as well as to novel issues, including Data/Text Analytics, Big Data, and RFID. In addition, practical sessions will enable them to acquire hands-on experience with a real-life Enterprise Resource Planning, Data Mining and Text Analytics.
We will start with a type of IS known as Enterprise Resource Planning (ERP) systems, which are now considered as de-facto in most manufacturing organizations. We will discuss, among others,
- Issues with legacy IS (information silos) and the need for ERP systems
- Opportunities and challenges that organizations face with ERP systems
- Mitigating the failure risks and high costs that are associated with ERP implementations
- Critical success factors and cultural factors that can make or break ERP projects
- Re-engineering existing processes to align them with the ERP system
Relevant examples from (discrete) manufacturing and real-life ERP implementations will be provided to illustrate the topics covered.
Next, we focus on a different type of Enterprise IS, namely Supply Chain Management (SCM) systems. In this regard, we will discuss,
- Supply chains and the need for effective SCM
- The limitations of ERP for SCM
- Advanced Planning Systems (APS)
- ERP-APS integration
- Developments in SCM: e-SCM and RFID
Subsequently, we will move on to Business Intelligence (BI) and Data Mining (DM), which form part of the "hot-topic" of "Data/Text Analytics", and which has received tremendous attention due to the "Big Data" phenomenon. Topics to be covered will include:
- Data Mining techniques, viz. Classification, Association Rule Mining, Clustering
- Data Mining applications, e.g. predicting customer profile and purchasing behavior, market segmentation
- Web Mining and Text Analytics. Students will get the chance to develop a simple text analytics application that crawls the web to extract relevant information (e.g. customer opinions on products).
Finally, in the last section of the course, we will discuss the "future of IS". In this regard, the students will be introduced to novel technologies, their strengths/weaknesses, as well as their associated opportunities/challenges. Specifically, we will focus on:
- Software as a Service (SaaS) and Cloud Computing
- Web 2.0, Social Media and Big Data
- Healthcare Information Systems
Practical Session
In addition to the aforementioned theoretical contents, the course will also have separate practical sessions, for the students to put into practice and reinforce what they have learnt during the lessons. The topics during the practical will be as follows:
- Java programming (incl. database interfacing)
- ERP practical using SAP
- Text analytics practical using Java
|
|
Learning outcomes of the course :
|
| At the end of this course, students should be able to:
- Appreciate the need for integrated Enterprise IS (e.g. ERP) compared to legacy information silos
- Acquire basic hands-on experience with a real-life ERP system, namely SAP
- Implement simple applications/programs using Java and SQL databases (MySQL will be used)
- Describe the ERP implementation process
- Appreciate the risks and challenges of ERP implementations
- Discuss solutions to mitigate the risks and challenges
- Describe the critical success factors of ERP implementation
- Appreciate the importance of user-training and knowledge transfer at the end of the implementation
- Understand the fundamentals of Data Mining techniques (classification, association rules mining, clustering)
- Describe the strengths and weaknesses, and suitable applications for the various techniques
- Appreciate the need for more advanced analytics solution (web mining, text mining)
- Develop a simple analytics program that mines information from the web (in Java)
- Discuss the challenges and opportunities of new trends and technologies in IS
- Discuss how these trends and technologies will affect classical IS like ERPs and society
|
|
Prerequisites and co-requisites/ Recommended optional programme components :
|
| Course candidates should have taken (and passed) IS courses of their earlier years, in particular, INFO0076-1: Informatique pour ingénieurs de gestion |
|
Planned learning activities and teaching methods :
|
| |
|
Mode of delivery (face-to-face ; distance-learning) :
|
|
- Lectures
- Practical sessions in computer rooms
- Please note that attendance is compulsory for lectures and practical. Please contact the lecturer beforehand if you are unable to attend a lecture or practical
|
|
Recommended or required readings :
|
| Selected chapters from
- Enterprise Systems for Management, by Motiwalla and Thompson, Pearson 2012**
- Integrated Business Processes with ERP Systems, by Magal and Word, Wiley, 2012
- Web Data Mining - Exploring Hyperlinks, Contents and Usage Data by Liu Bing, Springer, 2011
- Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, by Linoff and Berry, Wiley 2011
**: main textbook; the others are only recommended readings
- Lecture notes will be provided by the lecturer, and will be available on the LOL@ learning system (http://lola.hec.ulg.ac.be)
|
|
Assessment methods and criteria :
|
| The course will follow a continuous assessment system. The final grade will be based on a series of assignments during the course and a final written examination. Details:
- Java programming assignment (practical)
- Text analytics assignment (practical - project based)
- Small written exercise or practical on SAP (to be confirmed)
- Written examination
|
|
Work placement(s) :
|
| |
|
Organizational remarks :
|
| |
|
Contacts :
|
| Ashwin Ittoo
HEC Management School - University of Liege |
|
|
| |
