STRATEGY AND BIG DATA
2018/2019, Semester 1
School of Business (Strategy and Policy)
Modular Credits: 4
The application of computing power to the collection and analysis of detailed information relating to wide variety of processes and issues – summarized as big data – has the potential to change how business problems are evaluated and solved. In turn this has the potential to change how organizations operate and succeed. This module introduces students to big data constructs and uses in strategy and decision making. It will focus on the implications of big data for all aspects of business strategy, focusing primarily on customer interactions, competitive advantage, capabilities development, and how these influence the content and implementation of strategy.
Data is the new electricity. Data is the new currency. Buzzwords like Machine Learning, AI, IOT and Blockchain dominate conversations, news stories and furrow the brow of directors in the boardroom. FAANG companies stocks go through the roof even while large scale adoption is still a question mark. The course explains current capabilities of disruptive technologies as well as predicts the likely future of business, jobs and implications for all of us. A few truths that the course uncovers = Data-backed decision making is here to stay. Prediction is best done using Big Data. AI is here to augment humans, not to replace them.
The course takes students through a 13 week journey of exploration on how an industry leader can be disrupted, and challenges them to think about a proactive strategy to stay ahead, embracing technology before a competitor does.
Learning is augmented by in-class exercises, guest speakers, panel discussions and optional visits to AI and IOT labs. The visits will be during office hours, and are purely optional.
Workload Components : A-B-C-D-E
A: no. of lecture hours per week
B: no. of tutorial hours per week
C: no. of lab hours per week
D: no. of hours for projects, assignments, fieldwork etc per week
E: no. of hours for preparatory work by a student per week