Introduction
Are there caring, analytical ways of making decisions that are persuasive, both individually and corporately?
This module will not be able to address this issue anywhere near comprehensively. In any case, some persuasive decisions are not caring. The narrower focus will be on data-analytic and microeconomic approaches to decision making, with as little use of formulas as practicable. Rather, grasping of broad concepts, and, where appropriate, use of information technology to arrive at decisions, will be emphasized.
Extensive use will be made of Microsoft Excel in illustrating how to distil intelligence for decisions making. A very quick introduction to Excel will be conducted during the first lecture and tutorial. It will sometimes be desirable to bring a fully-charged notebook computer to class.
With corporate data-mining in perspective, the fabric for decision-making will be examined through the study of managerial data models and analytics. Analyses of real-life problems through case studies will form a central part in the exploration of the business intelligence framework.
Focus will be on the assimilation of decision-making concepts, their applications in management as well as their limitations. Students will gain exposure to decision and risk analyses, financial modelling, linear and nonlinear optimization tools, effective extraction and communication of information from data, deductive inference, margins of error, hypotheses testing, comparison of group averages, multi-linear regression, and forecast modelling. Pre-configured Microsoft Excel spreadsheets will be promoted as practical analytical tools.
Objectives
This module aims to sharpen students’ analytical mind in general, and to develop skills for decision making such as might be useful in management consulting. Students will appreciate the general decision framework and be familiar with some decision models in this quick and challenging survey.
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