The Science and Art of Business Analytics
Module Description
Module Announcement
Classes will begin at 9am.
Module Description
Business analytics is a scientific and data-driven approach to help organisations solve problems, make better decisions, and increase productivity. Despite its business origins, analytics has been applied in governments, hospitals, and museums, spurning a $125 billion market. However, a significant number of analytics projects fail due, in part, to poor science (techniques), art (e.g., communication, implementation, change management) or both. Against this background, this module covers the critical success factors that span these topics: Epistemology of analytics, data collection, sample size considerations, psychometrics, statistical and predictive modelling, text analytics, and agile project management. It also discusses applications in human capital management, and healthcare through case studies from the likes of Google.
Topics:
- Introduction to Business Analytics
- Crafting the problem and overview of analytics methodology
- Scoping the engagement, data collection, sample size considerations
- Thinking about data: Categories, evaluation, screening
- Psychometrics and behavioural modelling
- Statistical modelling
- Predictive modelling
- Text analytics
- Program evaluation
- People analytics
- Healthcare analytics
Assessment
Assessment
Individual Assignment: Newspaper Article (25%)
Objective:
Communicate scientific research findings cogently to a lay audience through writing a newspaper article.
Description:
Newspaper articles can be a powerful means of communicating ideas, framing key issues, and proposing change. Translating scientific knowledge to impact practice is central to this course. The willingness and ability to disseminate findings through effective communication is one means for making this happen.
Students are encouraged to select 2-3 scientific journal articles around a topic, synthesise ideas and present it cogently through a 1000-word newspaper article. The piece will be graded on whether a central thesis has been developed, the thesis has been defended conceptually, scientifically or both, and the piece is written in a clear, coherent, and compelling style.
Deliverable:
A 1000-word op-ed.
Individual Project: Analytics Hackathon (30%)
Objective:
Provide students with the experience of working with datasets and writing an analytics report.
Description:
Students are free to choose a publicly available dataset for visualization, analysis and report writing.
Deliverable:
A written response to the analytics hackathon.
Group Project: (35%)
Objective:
Provide students an opportunity to work in multi-disciplinary engagement teams to apply analytics in novel ways. More details will be shared in class.
Class participation: 10%
Note: Classes begin at 9am.
Direct any questions to reuben_ng@hotmail.com