Module Description
Digital technology is rapidly transforming business processes, communication processes, and customer activities—disrupting and destabilizing markets, but also enabling the creation of new ones. (Forbes Insights Team, 2018). This easily accessible introductory module to strategic analytics will give students important foundation tools and techniques to support decision making in a new digitally disrupted world.
The module is designed for postgraduate students with a basic knowledge of statistics, spreadsheet modelling and management science. A fundamental purpose of the module is to enable students to become intelligent readers and creators of strategic management analytics.
The module will be applied in a blended learning environment, with a mix of theory-based lectures, interactive workshops, modelling tutorials and real-world case studies. Content is split into 3 phases; (1) Analytics and Modelling in Strategic Management; (2) Interpretive Analytics - making and interpreting strategic decision through a qualitative lens; and (3) Mathematical and Logical Analytics – explores quantitative techniques that are more commonly associated with analytical decision making.
Reflecting on the cross functional/industry nature of strategic management and the Graduate Business School itself, there will be a varied mix of cases, analytical model examples and analogies used during the teaching of the module. Which will include, but not limited to: supply chain management; marketing analytics; financial modelling; consumer segmentation and econometrics, and causal/feedback loops.
The theme of the module is built on 3 pillars; Sustainability; Technology; and Business Intelligence.
Module Aim
The aim of the Analytics for Strategic Decision Making module is to teach the fundamental concepts of the emerging field of data analytics from a strategic management perspective and provides vital tools in understanding how data analysis works in today’s organisations. Students will learn to apply business analytics principles, communicate with data analytics professionals, and effectively use and interpret analytic models, both soft and logical to make better strategic management decisions.
PART I - Analytics and Modelling in Strategic Management
Principles of Problems and making sense of Strategic Vision, Introduction to Descriptive Analytics; Visualizing and Exploring Data.
PART II - Interpretive Analytics – Soft Management Science
Soft Systems methodology, Cognitive mapping, System Dynamics and Decision Analysis.
PART III - Mathematical and Logical Analytics
Predictive analytics, regression analysis, Linear and Integer Optimization, and Computer Simulation – Visual Interactive Modelling.
The module will be applied in a blended learning environment, with a mix of theory-based lectures, interactive workshops, modelling tutorials; site visits, real-world case studies and collaboration with other programme modules. The objective is to ignite students’ prior knowledge in quantitative and qualitative methodologies and execute the module content in a practical environment, placing the student into real world scenarios.
| Module Content & Assessment | |
|---|---|
| Assessment Breakdown | % |
| Formal Examination | 50 |
| Other Assessment(s) | 50 |