Management Science

The following modules are available to incoming Study Abroad students interested in Management Science.

Alternatively you may return to the complete list of Study Abroad Subject Areas.

MNGT213: Data Analysis for Management

  • Terms Taught: This module is taught in Michaelmas Term only.
  • Also Available: Due to the assessments, this course is only available to students who are spending a full academic year at Lancaster.
  • US Credits: Michaelmas Term: 4 Semester Credits.
  • ECTS Credits: Michaelmas Term: 8 ECTS Credits.
  • Pre-requisites: Pre-requisites: MSCI 100 or equivalent NB: This course is only available to students who are spending a full academic year at Lancaster.

Course Description

The aim of MNGT 213 is to show how data analysis methods can be applied to problems in a management context, making proper use of an appropriate computer package. By the end of the course the students should be capable of undertaking work experience in a non-technical managerial post and carrying out any statistical tasks that might reasonably be expected of them, using computer packages.

The course covers basic data analysis, data presentation, elementary probability, discrete and continuous distributions, data collection, confidence intervals, sample size, correlation and regression. An appropriate computer package is used for these topics.

Educational Aims

The purpose of this course is to provide students with an introduction to statistical techniques and their applications in the context of business and management problems. In addition, the course is designed to develop students' abilities to make effective use of computer software for data analysis.

Outline Syllabus

The course covers the following topics:

  • Summarising information
  • Probability
  • Discrete distributions
  • Continuous distributions
  • Sampling
  • Estimation
  • Hypothesis testing
  •  Regression analysis

 The course consists of two hours of lectures and one hour of workshops per week. In addition, there will be  office hours each week for students who require additional assistance. Tutorials begin in Week 2.

Attendance at workshops is compulsory for all students on the course.

Assessment Proportions

  • Exam: 67%
  • Coursework: 33%

MSCI100: Introduction to Business Analytics

  • Terms Taught: Michaelmas Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: High school mathematics.

Course Description

This country suffers greatly from the fact that large numbers of people, even (or especially) those in senior positions  not just in business and management but also in professions such as the law, journalism and politics do not possess even a rudimentary understanding of data, basic statistics and probability. 

The area of employment most closely linked to the syllabus is called "Business Analysis" or "Business Analytics" (a more modern term).  All major organisations employ several business analysts (though they sometimes are called something different) and it is certain that very many of you will find yourself working as a business analyst in a placement, internship or graduate job.  Your coursework exercise for MSCI 100 will therefore involve you working as a junior business analyst on a simple but realistic case study and reporting results and conclusions to a fictional boss.

Some of you may have previously studied the quantitative techniques involved, but this course covers much more than just techniques.  You will find that the teaching and your learning will be a bit different from that normally encountered in a mathematically-focused statistics course.  Others of you may believe that an understanding of these issues is not relevant ? if you still believe this when you come to apply for graduate  jobs, internships or placements related to business or management you will get a nasty shock.  This course aims to shake you out of these beliefs before they can get you into serious harm.

As well as the rudiments of statistics and probability, you will also be introduced to the use of Excel, which is  in very wide use in all sorts of organisations throughout the world.  Some of you may believe that you know all about Excel already, but it is almost certain that this course will teach you several useful tricks you can use  with Excel that will prove invaluable for you in your future students and employment. We are not trying to turn you into mathematicians far from it.  The level of mathematical ability required is no  greater than that required to get a C grade at Maths GCSE.

Educational Aims

By the end of the course you should have gained a basic understanding of the following and how they relate to management and business:

  • collecting data (sampling)
  • presenting data and understanding data presented to you
  • calculating simple measures of data (measures of location and spread)
  • considering different sets of data together so as to try to spot connections (correlation and simple regression)
  • interpreting the results of analyses
  • how not to be hoodwinked by other people's erroneous interpretations of data
  • how to structure and write a management report
  • basic probability
  • conditional probability
  • decision trees
  • probability distributions - Binomial, Poisson and Normal

You should be able not only to apply the techniques concerned but also to understand when and how to apply the techniques to management problems, and how to interpret the results.

  • Cognitive abilities / Non-subject-specific learning outcomes:
  • Use of Microsoft Word
  • Use of Microsoft Excel
  • Analytical skills
  • Report writing skills

Outline Syllabus

The statistical topics covered are sampling, introductory data analysis and presentation, index numbers, probability, the use of some important probability distributions and an introduction to regression analysis with two variables.  The computing side of the course introduces the use of word processing, spreadsheet software for statistical calculations, PowerPoint for presentations and management reports.

Assessment Proportions

  • Exam: 40%
  • Coursework: 40%
  • Test: 20%

MSCI101: Statistics and Computing for Management

  • Terms Taught: Michaelmas Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: College level Mathematics.

Course Description

The aims of MSCI 101 are to give an introduction to probability and statistics and to impart a familiarity with some useful computer tools. The statistical topics covered are sampling, introductory data analysis and presentation, index numbers, probability, the use of some important probability distributions, confidence intervals and hypothesis tests for means and proportions, regression analysis with two variables. The computing side of the course introduces the use of word processing, spreadsheet software for statistical calculations, PowerPoint for presentations and management reports.

Educational Aims

The module will cover the following topics:

  • Collecting Information and Sampling
  • Describing categorical data
  • Describing numerical data
  • Association between categorical variables
  • Association between numerical variables (correlation and regression)
  • Probability
  • Random variables
  • Probability distributions (binomial, Poisson, normal)
  • Use of Excel

Assessment Proportions

  • Exam: 50%
  • Coursework: 50%

MSCI102: Introduction to Operations Management

  • Terms Taught: Lent / Summer Term only
  • US Credits: 6 Semester Credits.
  • ECTS Credits: 12 ECTS Credits.
  • Pre-requisites:
    • High School Mathematics,
    • MSCI 100 or 101 Statistics and Computing for Management or equivalent.

Course Description

Operations Management is a core managerial discipline for all kinds of organisations, from private sector manufacturing through to public sector services. This course introduces you to the role of operations managers, covering a range of topics including: operations design, capacity planning and control, supply chain management, inventory, forecasting, and quality management. By the end of the course you should be able to:

  • Identify different kinds of operations and predict their attributes
  • Apply basic planning and analysis techniques to particular cases
  • Understand operations problems and find improvement strategies

Educational Aims

The aim of the course is to introduce some of the concepts and types of problems encountered by Operations Managers, within the context of the total management system. Students who think they would enjoy a course like this, but would prefer a slightly more quantitative approach, should consider Management Science (MSCI 103) as an alternative.  It is also possible to take both courses.

Outline Syllabus

This is provisional and subject to change. Several lecture hours will be held in reserve to deal with issues and  problems as they arise.

  • Operations characteristics and objectives 
  • Processes, process mapping and process characteristics 
  • Capacity, demand and forecasting 
  • Inventory, MRP, JIT and OPT 
  • Quality control and management 
  • Project planning and control 
  • Networks and supply 
  • Risk analysis and organisational reliability  
  • Operations strategy  

Assessment Proportions

  • Exam: 50%
  • Coursework: 50%

MSCI103: Introduction to Management Science / Operational Research

  • Terms Taught: This module is taught in Lent Summer Term only.
  • US Credits: 6 Semester Credits.
  • ECTS Credits: 12 Semester Credits.
  • Pre-requisites: Prerequisites: College Level Mathematics, MSCI 100 or 101.

Course Description

Managers and other decision-makers constantly need to solve problems which arise during their day-to-day activities. If a lengthy study is required, or if a problem is very complex, they are likely to seek assistance from consultants. Management Science is a form of management consultancy specialising in the development and application of quantitative methods to decision problems. Another common name forManagement Science is Operational Research.

Management Science is used in all major organisations in industry, commerce, finance and government.

Management Science studies might involve well-defined problems, like reducing the cost of a complex goods distribution network, or more nebulous problems, such as improving the care of patients in hospital.

In the Part I course students work on two challenging case studies based on real problems. They provide the opportunity to apply the concepts and techniques of problem solving, making recommendations and reportingresults. General and specific guidance is given on how to tackle these case studies.

Educational Aims

Subject-specific learning outcomes:   

  • By the end of the course you should:
  • Be able to apply the five techniques to particular cases
  • Understand when to apply each technique
  • Understand the benefits and limitations of the techniques

Cognitive abilities/Non-subject-specific learning outcomes:   

  • Problem structuring and problem solving skills
  • Analytical skills
  • Report writing skills
  • Presentation skills

Outline Syllabus

Management science is used in all major organisations in industry, commerce, finance and government. Its application might involve well-defined problems, such as reducing the cost of a complex goods distribution network, or more nebulous problems, such as improving patient care in hospital. Techniques based on mathematics and statistics can be extremely powerful in helping to solve these organisational problems.

Five such techniques will be introduced: 

  • forecasting
  • linear programming
  • network analysis
  • simulation
  • stock control 

The module emphasises not only how to apply techniques, but also when (and when not) to apply them. There is a stress on practical examples of using the techniques.

Assessment Proportions

  • Exam: 50%
  • Coursework: 50%

MSCI105: Project Challenge

  • Terms Taught: Lent / Summer Term only.
  • US Credits: 6 Semester Credits.
  • ECTS Credits: 12 ECTS Credits.
  • Pre-requisites:
    • None.
    • This module has a quota. A place is not guaranteed.

Course Description

This is a very practical course that seeks to develop the skills needed to manage on a daily basis, whether managing an operation, project or event. You will work in a team of six to deliver a full day event for a client school, which will require a high level of commitment. You’ll learn to negotiate with the client, plan, procure, and manage risk. We’ll also cover practical subjects such as meeting effectiveness, group decision making, multicultural teamwork, persuading people, etc. The course has limited availability with a maximum of 54 students and early registration is recommended. The course is demanding, but a rewarding and enjoyable experience.

Educational Aims

  • Experience the reality and understand the nature of an event / project and the skills and roles involved in managing a deliverable;
  • Develop the craft skills to practice as a manager, event manager or project manager;
  • Work with stakeholders and teams in a project environment and learn to build team working and  leadership qualities.
  • Deal with the art and craft of 'managing' as a social and political practice. The module focuses on 'how' to manage; Deliver key employability skills; Develop transferable study skills for Part II courses and independent learning.

Outline Syllabus

Some of the topics covered include:

  • Effective meeting management
  • Group decision making
  • Project and Event Planning
  • Risk management
  • Active Listening
  • Creativity & Idea Generation
  • Time Management
  • Intercultural communication
  • Authentic communication
  • Guest speakers

Assessment Proportions

  • Coursework: 100%

MSCI203: Managing Business Information Systems

  • Terms Taught:
    • Michaelmas Term Only
    • Due to the assessment structure, it is only available to students spending a full academic year at Lancaster
  • Also Available: Due to the assessments, this course is only available to students who are spending a full academic year at Lancaster.
  • US Credits: Michaelmas Term: 4 Semester Credits.
  • ECTS Credits: Michaelmas Term: 8 ECTS Credits.
  • Pre-requisites: No pre-requisite NB: This course is only available to students who are spending a full academic year at Lancaster.

Course Description

This module provides an introduction to the use and impact of IT, communication and integrated technology systems on business organisations. It considers the impacts of IT systems upon the business procedures, the services delivered to customers and the working life of those in the organisation. 

From a taxonomy of the different forms of IT system we move to examining the strategic planning and delivery of new systems, the risks to the business, the business advantages to be gained by successful implementations and consider current issues facing business organisations. The course provides the business foundation for other more specialised or technical topics in information systems.

Outline Syllabus

  • conceptual modeling
  • requirements and goal modeling
  • process modeling
  • stakeholder analysis
  • cost-benefit analysis
  • scenarios and personas

Assessment Proportions

  • Coursework: 40%
  • Exam 60%

MSCI222: Optimisation

  • Terms Taught: Michaelmas Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: MSCI103 - Introduction to Operational Research or equivalent.

Course Description

Optimisation is one of the primary techniques associated with Management Science/Operational Research. Linear programming models are used routinely in many industries including petroleum refining and the food industry. Integer linear programming models are increasingly being used in practice for complex scheduling problems such as those that arise in the airline industry where such models have saved large amounts of money. Skills in formulating and solving applied optimisation problems are valuable for anybody interested in a career in Operational Research or business modelling and consultancy.

The course is designed to enable you to apply optimisation techniques to business problems. Four main topics are covered: linear programming; specially-structured linear programs; integer and mixed-integer programming; heuristics for large-scale problems

Educational Aims

By the end of the course you should be able to:

  • formulate problems as mathematical programs and solve them;
  • carry out sensitivity analysis to see how robust the recommendation is;
  • use special methods for transportation and assignment problems;
  • use commercial MP software such as Lindo or the SOLVER add-in for EXCEL.
  • be aware of major heuristic techniques and know when and how to apply them.

Outline Syllabus

  • Formulation of linear programming problems
  • The simplex method
  •  Four phenomena; sensitivity analysis
  • Modelling issues; duality and dual pivots
  • Specially structured LPs: transportation and assignment
  • Integer programming: cutting and branching
  • Integer programming: applications and modelling issues
  • Large scale problems; applications to heuristics
  • Metaheuristic techniques
  • Design and evaluation of heuristics; a case study

This is only a guide and some deviation from this plan may occasionally be necessary.

Assessment Proportions

  • Coursework: 50%
  • Exam: 50%

MSCI223: Business Modelling and Simulation

  • Terms Taught: Lent / Summer Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: MSCI 103 or equivalent introductory simulation experience.

Course Description

Computer simulation methods are amongst the most commonly used approaches within Operational Research and Management Science. The aim of this course is to teach the skills required to apply simulation successfully to help improve the running of a business.

Modern simulation packages are a valuable aid in building a simulation model and this course will employ the Witness simulation package, which is widely used commercially. However, without the proper approach, the results of a simulation project can be incorrect or misleading. This course looks at each of the tasks required in a simulation project. It emphasises the practical application of simulation, with a good understanding of how a simulation model works being an essential part of this.

Educational Aims

By the end of the course you should:

  • Understand how a simulation model works
  • Understand each of the tasks required for a successful simulation project
  • Be able to build a simulation model using the Witness simulation package
  • Be able to carry out a simulation project successfully.

Improvement in:

  • Presentation skills
  • Report writing skills
  • Analytical skills
  • Creativity

Outline Syllabus

Outline Lecture Plan:

  • Introduction to simulation
  • Discrete event simulation and acticity cycle diagrams
  • Three phase approach
  • Simulating variability and the simulation process
  • Simulation process and conceptual modelling
  • Test
  • Data collection and data modelling
  • Verification and validation
  • Output analysis
  • Managing a simulation project and simulation research issues

Assessment Proportions

  • Coursework: 60%
  • Exam 40%

MSCI224: Techniques for Management Decision Making

  • Terms Taught: Lent / Summer Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites:
    • College Level Mathematics,
    • MSCI 100 or 101 or equivalent.

Course Description

 Techniques based on mathematics and statistics can be extremely powerful tools in helping to solve organisational problems. This module consists of five such techniques. The course will explain the business situations in which the techniques apply, and will show how to use the techniques and interpret the results to make better business decisions. The course is particularly relevant for careers in general management, accountancy, consultancy, and business analysis.

Educational Aims

When you have completed this course you should be able to:   

  • Apply the five techniques to particular cases  
  • Understand when to apply each technique  
  • Understand the benefits and limitations of the techniques

Outline Syllabus

Five quantitative techniques will be introduced on the course: 

  • Forecasting,
  • Simulation,
  • Decision Analysis, 
  • Network Analysis,
  • Linear Programming.

These techniques are part of the scientific discipline known as Management Science / Operational Research and are widely used in practice. Emphasis is put not only on how to apply a technique, but also on when (and when not) to apply it. The course is taught by a mixture of lectures and small group tutorials. It is compulsory to attend the seminars and attendance will be recorded each week.

Assessment Proportions

  • Coursework: 30%
  • Exam: 70%

MSCI231: Introduction to Operations Management

  • Terms Taught: Michaelmas Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: MSCI 100 or 101 or equivalent.

Course Description

Operations Management is the core managerial discipline in all kinds of operation - from private sector manufacturing through to public sector services. It is about the human capacity to organise all the operations that underpin the modern world: transportation, the generation of energy, retailing, the production of goods, the provision of medical and educational services and so on.

Part of this discipline is analytical; being able to map, measure and understand operations problems - such as congestion, error and failure. Part of it is constructive; being able to design processes and put together plans. The course reflects this combination and includes both qualitative and simple quantitative methods.

Educational Aims

By the end of the course students should be able to:  

  • identify different kinds of operations and predict their characteristics
  • apply basic planning and analysis techniques to particular cases
  • understand operations problems and identify improvement strategies  

Outline Syllabus

  • Introduction; Role and Characteristics of Operations
  • Operations Strategy and Objectives; The Design of Operations I (Location)
  • The Design of Operations II (Process, Timing and Layout)
  • Capacity Management
  • Process Flows and Lean Operations
  • Inventory Management
  • Material Requirements Planning (MRP) and Enterprise Resource Planning (ERP) systems 
  • Project Planning and Control
  • Quality Management
  • Supply Chain Management

Assessment Proportions

  • Exam 50%
  • Coursework: 50%

MSCI242: Spreadsheet Modelling for Management

  • Terms Taught: Michaelmas Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: MSCI 100 or 101 or equivalent.

Course Description

The aims of this course are to understand general modelling concepts and their role in management analysis; how analytical techniques can add value to management decisions and the role data issues (quality, errors) can play in decision making.  You will learn how Excel models can support research and investigations.  You will also learn how to use a wide range of Excel functions to handle and filter data of different types, produce effective charts and data summaries and understand how Excel models can be applied to a wide range of management decisions.

Educational Aims

  • Understand how to build a dynamic, well-structured spreadsheet model
  • To understand how to use a wide range of Excel functions to handle and filter data of  different types
  • To know how to produce effective charts and data summaries
  • To understand general modelling concepts and their role in management analysis
  • To understand how analytical techniques can add value to management decisions
  • To understand how Excel models can support research and investigations

Outline Syllabus

  • Introduction to modelling principles and basic Excel 
  • Descriptive statistics, basic charting and formatting
  • Data analysis, filtering methods and advanced charting 
  • Case study exercise (Ambulance service modelling)
  • Introduction to VBA using Macro Recorder.
  • General investigative modelling
  • Introduction to VBA programming
  • Optimization modelling
  • Monte Carlo simulation modelling
  • Advance topics (such as custom UserForms) and review

Assessment Proportions

  • Group Coursework: 50%
  • Exam: 50%

MSCI251: Project Management Tools & Techniques

  • Terms Taught: This module is taught in Michaelmas Term only.
  • US Credits: Michaelmas Term: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: This module has a quota.  A space is not guaranteed

Course Description

This course aims to introduce project management methods in a way which links to the life cycle of a typical project from the early project identification and definition stages, through project execution and control, to issues of implementation and change. The coverage of the early stages of the project cycle uses methods emerging from the systems movement and stresses the strategic relevance of project management. The operational management of the project is covered by introducing techniques for the planning, scheduling and controlling of projects. Attention is also given to people management aspects of this process especially to leadership, team working, motivation and direction. This course has limited numbers and availability cannot be guaranteed.

Educational Aims

Subject-specific learning outcomes:

  • By the end of the course you should be able to:  
  • Understand the strategic relevance of projects;
  • Understand the operational management of projects;
  • Understand the planning process for projects;
  • Understand the importance of people management within projects;
  • Integrate your knowledge about project management with your own experience;
  • Apply your knowledge about project management to real projects;

Outline Syllabus

The topics to be covered on the course include:

  • Strategy and projects
  • Project structure and success
  • Project selection
  • Project justification
  • Stakeholders
  • Requirements
  • Planning
  • Estimating
  • Scheduling and resourcing
  • Problem solving
  • Budgeting
  • Project Teams
  • Risk management
  • Project monitoring
  • Project control
  • Quality
  • Change within the project
  • Communications and negotiation
  • Project closure and review

Assessment Proportions

  • Coursework: 40%
  • Exam: 60%

MSCI281: Supply Chain Management

  • Terms Taught: Michaelmas Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: MSCI 102 or MSCI 231 Introduction to Operations Management or equivalent.

Course Description

This course examines the principles and practices of supply chain management, and examines supply chain and logistics management in relatively high-volume industries such as retailing. But it also looks at supply chain management critically, as just one manifestation of the more general issue of trans-organisational operations management. Most of the time will be spent considering inter-organisational relationships from various perspectives, but it will also be necessary to understand how they relate to matters within the organisation. For example, adopting Just-in-Time supply requires Just-in-Time approaches to be adopted within the firm, and vice versa.

Educational Aims

On successful completion of the module students should be able to:

  • understand and critically evaluate the principles of supply chain management
  • understand how a supply network should be organised and effectively managed, taking account in particular of supply strategy, inter-organisational relationships and logistics issues
  • appreciate the wider societal implications of supply chain management including public sector implementation, environmental impact, and globalisation.

Outline Syllabus

  • Introduction to Supply Chain Management: Firms, Chains, Networks
  • The Value Chain and Performance Objectives
  • Demand, Supply and the Management of Inventory in Supply Networks
  • Designing and Managing Logistics Operations in Product Supply Chains
  • MRP/ERP, JIT and Lean Supply
  • Capabilities in Supply Networks
  • Outsourcing and Supplier Relationships
  • Theorising Inter-organisational relationships
  • Purchasing Strategy and Practice in Private and Public Sectors
  • International, Green and Ethical issues in supply

Assessment Proportions

  • Exam: 50%
  • Coursework: 50%

MSCI282: Quality and Risk Management

  • Terms Taught: Lent / Summer Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: MSCI 102 or MSCI 231 Introduction to Operations Management or equivalent.

Course Description

The purpose of this course is to introduce the concepts of Quality Management and Risk Management and to teach in depth some aspects that are of particular relevance to Operations Managers.  The course will put the ‘quality revolution’ in context, discussing the developments that have taken place, with reference to some of the ‘gurus’ that have emerged, and give a basic understanding of some of the analytical issues associated with the management of quality. The course will also deal with the two main strands of risk management - the technical analysis of risk and our understanding of societal perceptions of risk.

Educational Aims

On completion of the module you should be able to:

  • Demonstrate a strong understanding of the role and importance of quality and risk management.
  • Carry out quantitative analyses of quality and risk problems.
  • Reflect critically on concepts of quality and risk as they are used in different kinds of operation

Outline Syllabus

The main themes of the course are as follows:

  • Statistical process control
  • Total quality management
  • Broader themes in the quality movement
  • Catastrophic failure and organizational reliability
  • Quantitative risk analysis
  • Social risk perception

Assessment Proportions

  • Coursework: 40%
  • Exam: 60%

MSCI304: Developing Business Information Systems

  • Terms Taught: Lent / Summer Term only.
  • US Credits: 4 Semester Credits.
  • ECTS Credits: 8 ECTS Credits.
  • Pre-requisites: MSCI203

Course Description

In this course we look at how we may study business operations, analyse the situation and develop appropriate information systems designs. The same techniques can be of value whether you develop them further and become an IS professional or use them in general management or consultancy. There is an emphasis on practical application and extensive use of class exercises.

Educational Aims

This course is aimed at providing the basis for a critical appreciation of the subject and relevant vocational skills for analysis and design. The intention is that you should be able to analyse business operations, identify information needs and design appropriate computerised information systems. By the end of the course you should :  

  • Understand the importance and connective role of information systems in modern organisational activity
  • Have a critical understanding of the processes undertaken to develop information systems, the organisational imperative that have affected these in the past and current best practice
  • Carry out an analysis of business operations, representing current and planned activities in the form of process models.
  • Define the logic of operations in decision tables.
  • Represent existing data stores as un-normalised relations and move to 3NF.

No previous knowledge of business, systems analysis or business computing is required

Outline Syllabus

Theme 1: Information systems and organisation,

  • Introduction to the topic.
  • Changing approaches to development

Theme 2: Process Analysis,

  • Dataflow diagramming
  • Decision Tables

Theme 3: Data focussed development,

  • The database approach - the problems it solves, background and key concepts

Theme 4: Database development and design

  • E-R modelling
  • Normalisation for relational data bases

Assessment Proportions

  • Coursework: 40%
  • Exam: 60%

MSCI331: Data Mining for Direct Marketing and Finance

  • Terms Taught: Lent / Summer term only
  • US Credits: 4 semester credits
  • ECTS Credits: 8 ECTS credits
  • Pre-requisites: MSCI212 or MNGT213

Course Description

Leading on from basic statistics - and leading into combining decision making in a business and management context using statistical analysis - this course develops further your statistical modelling skills on synthetic and empirical data. You are introduced to an advanced set of statistical modelling skills, including regressions, classification, clustering, association rule mining, and text mining using software such as R or SAS Enterprise Miner. Such a development significantly increases the scope of knowledge on statistical methods, software and knowledge on how to apply models in a real world scenario to support management research and decision making. 

Educational Aims

When you have completed this course you should be able to understand:

  • General modelling concepts in relation to complex models.
  • How to use a wide range of advanced data mining methods to handle and filter data of different types and for different applications.
  • How to structure a model to deal with complexity and large datasets.

Outline Syllabus

The module will cover a wide range of data mining methods including decision trees, artificial neural networks, support vector regression, k-nearest neighbour methods, and develop appropriate software skills techniques.

Outline Lecture Plan

  • Introduction to Data Mining Applications
  • Classification methods I (Discriminant Analysis, Logistic Regression)
  • Classification methods II (Decision rules, Decision Trees)
  • Classification methods II (Artificial Neural Networks)
  • Clustering methods I (k-means clustering)
  • Association rule mining & Text Mining
  • The SEMMA Process of Data Mining
  • Methods for data exploration & data manipulation
  • Methods for data reduction & feature selection
  • Evaluating Classification Accuracy

Assessment Proportions

  • 50% Group Coursework
  • 50% Individual Coursework

MSCI354: Structuring Complex Problems

  • Terms Taught: Michaelmas term only
  • US Credits: 4 semester credits
  • ECTS Credits: 8 ECTS credits
  • Pre-requisites:
    • none.
    • This module has a quota, and it is likely that there will be few places available to visiting students.

Course Description

Issues and problems in the complex world of management do not necessarily arise in a well structured form. People often do not know what they want or what is possible. Further, they may disagree about what they are trying to achieve and the means for arriving at their goals. Much thinking needs to be done in order to define an appropriate framework within which a useful analysis or project can be carried out.

Various approaches have been developed in recent years to assist in this task, often referred to as problem structuring methods (PSMs). They are very practically oriented methodologies that typically involve the management team to help facilitate the structuring of complex situations. They place emphasis on dialogue to think through strategic problems, identify the salient issues, formulate goals and negotiate action plans.  This course will introduce you to several PSMs and some of the process skills to use them.

Educational Aims

By the end of the course you should be able to:

  • Understand how problem structuring aids decision making;
  • Understand and discuss how various problem structuring methods work;
  • Understand the differences between various problem structuring methods and how these differences affect their use;
  • Identify appropriate situations in which to use problem structuring methods;
  • Choose between particular problem structuring methods when analysing a problem situation;
  • Apply problem structuring methods to problem situations.

Outline Syllabus

  • Introduction to Problem Structuring Methods
  • Cognitive Mapping technique
  • Introduction to Decision Explorer software for Cognitive Mapping
  • Using Cognitive Mapping for problem structuring
  • Strategic Options Development & Analysis methodology using Cognitive Mapping
  • Multi methodology
  • Workshop facilitation: Oval Mapping Technique
  • Facilitation case review
  • Strategic Choice Approach
  • Strategic Choice Approach case study
  • Introduction to Soft Systems Methodology (SSM)
  • SSM: Rich Pictures & understanding the problem situation
  • SSM: appreciating and analysing different stakeholder worldviews
  • SSM: designing for change with conceptual modelling
  • SSM: understanding how to use SSM in practice

Assessment Proportions

  • Exam: 30%
  • Coursework: 70%

MSCI375: E-Business Management and Technology

  • Terms Taught: Lent / Summer term only
  • US Credits: 4 semester credits
  • ECTS Credits: 8 ECTS credits
  • Pre-requisites: No Pre-Requisites

Course Description

Digital or 'e' business is today’s leading form of doing business. One of the largest companies in the world, Apple, is an e-business; the fastest growing business ever Groupon is an e-business; the largest social network platform ever, Facebook, is an e-business; and the largest information search and retrieval system ever, Google, is an e-business. Indeed, any 'going concern' needs to understand how to "enhance the digital" if it is to survive and thrive in today’s fast-moving world. To this end, the module presents a variety of frameworks that help the student formulate a comprehensive understanding of e-business management and technology in theory and practice.

Educational Aims

At the end of the course, you should have a sound appreciation of the theoretical and practical concepts that inform the e-business domain. In particular students should be able to:

  • Demonstrate an understanding of e-business models
  • Apply selected e-business model theory to develop a business case
  • Demonstrate a critical understanding of e-business service provision, e.g. cloud computing
  • Demonstrate an appreciation of how businesses can use e-business to gain advantage

 By the end of the course you should be able to:

  • Work in groups in order to clearly present ideas
  • Demonstrate the application of the theoretical concepts of e-business

Outline Syllabus

The course runs over 10 weeks with lecture sessions concentrating on the core theory, concepts, applications, and technologies relating to e-business. This will be supported by one-hour seminar sessions for each student group that occur every other week. The seminar sessions are semi-structured, including case studies’ discussions and hands-on technical practice. In order to complement the lectures, it is very important that students attend all the classes.

The module features guest lectures from tech giant IBM; indeed the module has a significant 'tech' orientation which some business-focused students may find challenging. The module covers a range of e-business topics: some fundamental concepts of e-business (e.g. e-business models, e-business ethics), e-business technology infrastructures (e.g., cloud computing, data analytics), and social computing and social commerce.

Assessment Proportions

  • Exam: 80%
  • Coursework: 20%

MSCI381: Business Forecasting

  • Terms Taught: Michaelmas term only
  • US Credits: 4 semester credits
  • ECTS Credits: 8 ECTS credits
  • Pre-requisites: MSCI103 or MSCI224 or equivalent.

Course Description

The course aims to give students an appreciation of modern business forecasting methods. More explicitly, it  aims to ensure that the successful student is capable of developing a validated quantitative set of forecasts using both extrapolative and causal forecasting methods.  By the end of the course students should be able to apply a simple forecasting method to support demand and revenue management. Students will also develop an appreciation for the use of spreadsheets in forecasting.

 In the second part of the course, you learn to identify and exploit opportunities for revenue optimization in different business contexts. You review the main methodologies that are used in each of these areas, discuss legal issues associated with different pricing strategies, and survey current practices in different industries. As the course outline reveals, most of the topics covered in the course are either directly or indirectly related to pricing issues faced by firms that operate in environments where they enjoy some degree of market power.

Within the broader area of pricing theory, the course places particular emphasis on tactical optimization of pricing and capacity allocation decisions, tackled using quantitative models of consumer behavior (e.g. captured via appropriate price-response relations), demand forecasts and market uncertainty, and the tools of constrained optimization -- the two main building blocks of revenue optimization systems.

Educational Aims

On successful completion of the module students will be able to:  

  • Produce reliable and accurate business forecasts and design reliable implementations for real applications.
  • Identify the different forecasting objects and relate to the forecasting process and the notions of uncertainty, stochasticity and forecastability.
  • Understand, develop and use univariate and multivariate forecasting methods for business applications.
  • Evaluate forecasts and develop monitoring and continuous improvement schemes for forecasting applications.
  • Identify external drivers that affect your forecasting target and quantify their impact. 

Outline Syllabus

  • Introduction to forecasting and demand management
  • Extrapolative Modelling - the forecasting process, naïve models, measuring forecast error, decomposition, exponential smoothing and damped trend  
  • Workshop topics: Naïve models, Error measures & Exponential smoothing
  • Evaluating and choosing between extrapolative methods 
  • Workshop topics: Exponential Smoothing and Method comparison
  • Establishing Demand curves 
  • Workshop on Regression
  • Foundations of Pricing and Revenue Management
  • Pricing Analytics and Demand Curve Modelling 
  • Workshop: Modelling Demand Curves (I)
  • Price Optimization
  • Workshop: Modelling Demand Curves (II)
  • Capacity Rationing
  • Overbooking
  • Workshop: Optimizing Pricing and Capacity Allocation Decisions
  • Pricing Strategies

Assessment Proportions

  • Coursework: 100%

MSCI382: Innovative Developments in Operations Management

  • Terms Taught: Lent / Summer term only
  • US Credits: 4 semester credits
  • ECTS Credits: 8 ECTS credits
  • Pre-requisites: MSCI102 or MSCI231 Introduction to Operations Management or equivalent.

Course Description

There have been a number of innovative developments in Operations Management that have sought to organise resources in a significantly new manner in order to make a big step change in performance. This course discusses these key innovative developments in detail, including those that have led to extensive modernisation in the service sector as well as those that have revolutionised manufacturing management. There will be an emphasis on the importance of successful innovation in the current competitive environment, and the key role of Operations Management in sustaining a competitive advantage and bringing about service improvements.

Educational Aims

On successful completion of the module students should be able to: 

  • Discuss the advantages and disadvantages of each of the innovations covered, indicating a clear understanding of the impact of the approach on company performance.
  • Apply innovative Operations Management ideas to specific case study examples, hence showing an understanding of when each idea is or is not appropriate, and also a clear perception of issues of best practice implementation.  
  • Cognitive abilities/Non-subject-specific learning outcomes:  
  • In addition to the above subject specific skills, the following cognitive skills will also be further developed and consolidated:
  • To think critically to determine applicability of the approaches covered.
  • To read selectively, identifying suitable source material from the library.   

Outline Syllabus

A number of key innovative developments will be discussed during the course, including the following:

  • Modularisation and customisation - methods of innovative process design which ease the more detailed decision levels in all sectors.
  • Lean Thinking from Lean Production through to Lean Consumption and other issues of waste reduction in the service sector - for example, covering issues that have caused companies such as Tesco to reconsider their inventory control systems.
  • Theory of Constraints, as applied to a variety of settings including the radical 'critical chain' ideas applied to project management.
  • Performance Management/Measurement - with a particular focus on after sales service, product and process development and the use of the balanced scorecard in the context of operations innovations.  The behavioural aspects of the use of performance measurement will also be explored.
  • Manufacturing planning & control innovations with an emphasis on issues relating to SMEs - including kanban, CONWIP, POLCA and Workload Control.

The course will be completed by looking at the need for continuous improvement, as required to drive further innovative developments in the future.

Assessment Proportions

  • Exam: 60%
  • Coursework: 40%