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2014/5 |
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School of Management |
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6 |
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Masters UG & PG (FHEQ level 7) |
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Modular (no specific semester) Semester 2 |
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CW 100% |
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Like-for-like reassessment (where allowed by programme regulations) |
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Before taking this unit you must take MN50339 and take MN50340 and take MN50341 and take MN50342 and take MN50343 and take MN50344 and take MN50345 |
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Aims: This module aims to demonstrate how modern analytics techniques can support and improve business decision making by yielding information and insights and suggesting solutions to multi-faceted problems. Learning Outcomes: By the end of the module students should be able to: * Recognise the role that analytics techniques can play in the solution of management problems and identify problems that are amenable to these techniques. * Apply analytics techniques to problems drawn from a wide range of business activities. * Be able to assess the strengths and limitations of any given analytics application. * Communicate effectively with specialists in management science and operational research. Skills: Intellectual Skills * facility to apply subject-specific knowledge into a range of complex situations, taking into account the overall implications for the other areas of the business (TFA); * the ability to acquire and analyse data, information and situations; to evaluate relevance and validity, and to synthesise it in the context of topical business problems (TFA); * understanding of theoretical concepts and frameworks that enable the student to meaningfully link theory and practice, and the ability to critically appraise both theory and practice (TFA). Professional Practical Skills * deal with complex issues and make sound judgements in the absence of complete information, and to communicate their conclusions clearly and competently to a range of audiences (FA); * apply practical decision-making methods and tools at both tactical and strategic levels (TFA); Transferable/Key Skills * ability to conduct in-depth research into management and business issues (TFA). * ability to recognise ethical corporate/social responsibility issues and to manage in light of these issues (F). Personal/Interpersonal *facility to communicate including presenting and marketing themselves and their ideas; preparation and production of effective management analysis (TFA). Content: The module will cover: * Simulation models to support financial and capacity planning decisions. * Multi-attribute decision models to support decisions involving multiple objectives, such as supplier selection or facility location decisions. * Short term forecasting methods to support purchasing, production planning and human resource planning decisions. * Multivariate statistical methods to support marketing decisions. * Machine learning techniques (e.g. genetic algorithms) to identify potentially optimum solutions to production scheduling problems or pricing strategy decisions. (Note that the application areas given above are intended to be illustrative and may vary from course to course.) |
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MN50496 is Optional on the following programmes:School of Management
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