MIS30150 ICT For Strategic Decision Making
MIS30150 ICT For Strategic Decision Making
Module Coordinator Matt Glowatz [email protected] http://www.linkedin.com/in/mattglowatz
When? Semester Two
Credits 5 ECTS
General Structure One 1 hour lecture per week One 1 hour workshop per week (Bloomberg Laboratory) 16 hours online learning throughout the semester
Module Description
Today’s managers are faced with the challenge crafting and implementing timely and accurate strategic decisions utilising both offline and online data, information and knowledge. In doing so, it is essential that managers make optimal use of Information and Communications Technologies (ICT) for data collection and analysis.
This applied module investigates and discusses strategic management decision making utilising ICT. Combining industry standard data collection and analytics tools, such as the Bloomberg Infrastructure, students will gain important insights into sectors, industries and companies in order to draft strategic investment ideas and recommendations.
Another substantial part of this module requires students to complete an online business simulation published by Harvard Business School.
Learning Outcomes
On successfully completion of the module, students should be able to
(i) Demonstrate a deep understanding of the major issues surrounding strategic management decision making.
(ii) Utilise and become proficient using online data collection tools for strategic decision making.
(iii) Evaluate and discuss organisations’ market performance utilising Bloomberg’s infrastructure.
(iv) Investigate and apply strategic decision making theories through an online simulation.
Matt Glowatz [email protected] 1 MIS30150 ICT For Strategic Decision Making
Workload
Lectures 12 hours Computer Aided Lab 12 hours Online Learning 16 hours Specified Learning Activities 24 hours Autonomous Student Learning 36 hours
Prior Learning No prior learning required, however, students should have a genuine interest in the fields of Data and Business Analytics, Decision Making Science and Management
Requirements, Exclusions None
Assessment
This module is assessed combining both individual and group assignment components as outlined below:
Essay (Individual. Strategic Decision Making Online Simulation (Harvard) 30% Online Practical Examination (Bloomberg - BMC) 20% Group Project: Business Analysis Project 30% Essay (Individual: Big Data Project Case Study Analysis) 30%
Learning Outcome Assessment Component
Essay Demonstrate a deep understanding of the major issues surrounding strategic Online Practical Examination management decision making. Big Data Project
Online Practical Examination Utilise and become proficient using online data collection tools for strategic decision Group Project: Business Analysis Project making.
Group Project: Business Analysis Project Evaluate and discuss an organisation’s market performance utilising Bloomberg’s infrastructure.
Investigate and apply strategic decision Essay: Harvard Business School Online making theories through an online simulation Simulation
Matt Glowatz [email protected] 2 MIS30150 ICT For Strategic Decision Making
Resits and Remediation
Students who fail this module are required to sit a repeat examination.
Tentative Module Planner
Week Topic
Week 1 Introduction to strategic decision making in the context of Information and Communications Technologies (ICT)
Week 2 Decision Science and Research, Bloomberg Infrastructure
Week 3 ICT for Decision Making, Bloomberg Infrastructure
Week 4 Management Decision Making using ICT, Bloomberg Infrastructure
Week 5 Bloomberg Infrastructure
Week 6 Harvard Business Online Simulation
Week 7 Harvard Business Online Simulation
Mid-Term Break No lectures
Week 8 Designing and implementing data and business analytics-related initiatives
Week 9 Ethical and legal issues in the context of collecting and utilising data for decision making
Week 10 Project Presentations and Discussion
Week 11 Emerging Trends and Future Outlook
Week 12 Module Review, Exam Preview
Recommended Readings
Readings and study materials for this module will be made available on Blackboard.
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