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Art of Modelling

  • MSc >
  • Art of Modelling

Course Description

Many major corporations now see analytics as a source of competitive advantage. This course will attempt to familiarize you with the modelling of analytical models for decision making. Since most firms now have access to mountains of information and data, an important differentiator is the skill to this data with models to arrive at great business decisions.

The objective of the Art of Modelling course is to train our students to approach business decisions in a logical, quantitative and systematic way. The course is concerned with processing and visualization of data, conception and development of statistical and mathematical models, evaluation of outcome and decision uncertainty, interpretation of analysis, and business insights guided by data analysis by managers in the process of creating value. The case settings, rather than replicating traditional exercises, are opportunities for students to select from an unstructured environment the appropriate analytics techniques and to organize the data, develop models, and interpret model output so as to either make better decisions, or respond more intelligently to the decisions of others. In summary, the course objective is to provide the student with the capability to use data and mathematical models to inform managerial decisions. The applied research articles will complement cases by showing best practices and new methods.

The major segments of the course are as follows:

  1. Modelling and model building
  2. Decision making under uncertainty and analyzing sequential decisions
  3. Data‐driven decision making
  4. Decision making under uncertainty and simulation
  5. Simultaneous decision problems and optimization
  6. Combined applications

Learning Outcomes

  • Construct a suitable model (conceptual and/or spreadsheet) of a business decision problem;
  • Identify the need for and make reasonable and justifiable assumptions to abstract a complex business problem into a model;
  • Manipulate model inputs to evaluate the influence of specific values and assumptions on outcomes. Perform sensitivity analysis;
  • Develop reasoned recommendations based on quantitative analysis of decisions;
  • Combine concepts from each module to construct a model of a complex decision problem;
  • Articulate analysis and conclusions in class discussions, written exams and reports; and,
  • Develop evidence, analysis, and data‐based decision-making skills.