OPERATIONAL ANALYTICS - 2023/4
Module code: MANM304
Management Science is used to solve operations problems analytically. Techniques examine the supply chain's underlying transportation network which connects suppliers via transhipment nodes to its demand locations. Decision Science is used for in rational decision making under uncertainty. For instance optimal inventory levels are determined for warehouses and manufacturing. All kinds of business activities are optimised to give businesses a competitive advantage by maximising profit and minimising costs.
Surrey Business School
HILL Andrew (SBS)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
JACs code: N530
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 94
Lecture Hours: 22
Tutorial Hours: 4
Laboratory Hours: 18
Captured Content: 12
Prerequisites / Co-requisites
The module content will focus on a selected set of critical areas in Management. As an indication of the kind of issues that will be covered, please find below an indicative set of topics.
- Decision Analysis (e.g. Utility theory)
- Linear Programming (e.g. transportation optimisations)
- Network Analysis (e.g. Shortest Route, minimal spanning tree)
- Inventory Systems (e.g. Economic Order Quantity model)
- Simulations and Waiting Line Models (e.g. Multiple Server Waiting Line)
|Assessment type||Unit of assessment||Weighting|
|Examination Online||EXAM SET DATE AND TIME (120 MIN)||50|
In order to achieve the threshold standard for the award of credits for this module, the student must meet the following criteria related to the learning outcomes:
- apply the theories, conceptual frameworks and methodologies that underpin operational research;
- prove the ability to synthesise Management Science concepts within an analytical context;
- demonstrate evidence of background reading and research of the academic and practitioner literature relevant to Management Science.
Formative assessment will be provided throughout the course, i.e. students demonstrate ability to solve problems during the course of the semester. They will be given a range of business problems to solve as homework, typically in the form of 2-4 exercise sheets over the course of the module. Tutorials and group exercises will be used to test the application of the methods they have been taught in a more practical setting.
Summative assessments are covered by a coursework and an exam. Both are linked to the learning outcomes. They require to:
- analyse the efficiency and productivity of business firms;
- evaluate and define “challenges” in a concise, precise and logical manner;
- apply a selected number of classical and state-of-the art Operational Research methods and tools to solve supply chain problems analytically;
- create solution models and algorithms that offer competitive advantage to the businesses;
- provide results to the management for decision making and implementation.
- Solve operational problems analytically
- Develop timely, useful solutions to business problems
- Understand how quantitative analysis is used to make business decisions
|001||Analyse the efficiency and productivity of business firms.||CPT|
|002||Evaluate and define “challenges” in a concise, precise and logical manner.||CPT|
|003||Apply a selected number of classical and state-of-the art Operational Research methods and tools to solve operations problems analytically.||KCPT|
|005||Create solution models and algorithms that offer competitive advantage to the businesses.||CPT|
|004||Provide timely, useful results to the management for decision making and implementation.||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Methods of Teaching / Learning
The teaching and learning strategy is designed to: cultivate an understanding of the main issues and challenges; provide a coherent conceptual framework; develop a critical awareness of the various approaches of operational research in business firms.
The teaching and learning methods include: a lecture every week as well as several student exercises. Web-based learning support and electronic resources will be provided.
Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.
Upon accessing the reading list, please search for the module using the module code: MANM304
Programmes this module appears in
|Business Analytics MSc||2||Compulsory||A weighted aggregate mark of 50% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2023/4 academic year.