Attend our upcoming webinar and explore our Manufacturing Systems and Management course portfolio and find the perfect course for you. Hear from our Management and Information Systems MSc Course Director, and learn more about the course structure and gain an insight into some of the modules and content that will be covered. Register now.
The Management of Information Systems (MIS) MSc prepares students who want to pursue a career in the management of technology-based Information Systems (IS) solutions. It focuses on developing an understanding of complex relationships between people, information, processes and technology in order to support organisations and industries. The course covers key topics in digital transformation, operations management, supply chain, business process analysis, change management and enterprise systems.

These topics have carefully been selected to provide students with the skillset necessary to thrive in the management of information systems aligned with innovative application of digital technology. The course has accreditations with the Institute of Engineering and Technology, and the Institute of Mechanical Engineering, graduates secure exciting roles with globally renowned companies around the world.

Overview

  • Start dateFull-time: October, part-time: throughout the year
  • DurationOne year full-time, Three years part-time
  • DeliveryTaught modules 40%, Group project 20% (dissertation for part-time students), Individual project 40%
  • QualificationMSc, PgDip, PgCert
  • Study typeFull-time / Part-time
  • CampusCranfield campus

Who is it for?

MIS has a long history of attracting high quality students to solve practical problems. Graduates from the course will be equipped with multidisciplinary skills and practical knowledge to become business leaders of the future.

This course is designed for graduates and early-career professional looking to develop information systems and managing technological transformation within organisations, across a broad range of sectors including aerospace, automotive, rail, energy and defence. This diversity offers many possibilities by providing the core competencies for employment in many areas including research, engineering, manufacturing, production and design, alongside careers in the business, consulting and finance.


Why this course?

MIS is the backbone of information for a company. It helps to understand complex relationships between people, information, processes and technology, and to help businesses make decisions to coordinate and analyse information. Students have the opportunity to:

  • work in teams and collaborate on real industrial projects
  • learn through industry case studies and discussions to acquire an appreciation of significant challenges and opportunities for businesses
  • develop management and consultancy skills through critical thinking, appraisal and analysis
  • receive a high-quality learning experience at a prestigious institution which aligns it teaching to real-life industry challenges
  • access to industry software/systems (SAP etc)

Informed by Industry

Our courses are designed to meet the training needs of industry and have a strong input from experts in their sector. Students who have excelled have their performances recognised through course awards. The awards are provided by high profile organisations and individuals, and are often sponsored by our industrial partners. Awards are presented on Graduation Day.

Course details

The course comprises eight assessed modules, a group project and an individual research project. The modules include lectures and tutorials, and are assessed through practical work, written examinations, case studies, essays, presentations and tests. These provide the 'tools' required for the group and individual projects.

Course delivery

Taught modules 40%, Group project 20% (dissertation for part-time students), Individual project 40%

Group project

The group project experience is highly valued by both students and prospective employers. Teams of students work to solve an industrial problem. The project applies technical knowledge and provides training in teamwork and the opportunity to develop non-technical aspects of the taught programme. Part-time students can prepare a dissertation on an agreed topic in place of the group project.

Industrially orientated, our team projects have support from external organisations. As a result of external engagement Cranfield students enjoy a higher degree of success when it comes to securing employment. Prospective employers value the student experience where team working to find solutions to industrially based problems are concerned.

Individual project

A key element of the Master's programme is the project work undertaken.

The individual research project is either industrially or Cranfield University driven. Students select the individual project in consultation with the Course Director. It provides students with the opportunity to demonstrate independent research ability, the ability to think and work in an original way, contribute to knowledge, and overcome genuine problems in manufacturing. The projects are sponsored by industrial organisations.

Companies that have recruited and sponsored project work include 3M Health Care, Airbus, Aston Martin, BAE Systems, BT, Chubb Security, Ford Motor Company, GEC, GlaxoSmithKline, IBM, Jaguar, Johnson & Johnson, Motorola, Pfizer, Philips, Rolls-Royce and Unilever.

Modules

Keeping our courses up-to-date and current requires constant innovation and change. The modules we offer reflect the needs of business and industry and the research interests of our staff and, as a result, may change or be withdrawn due to research developments, legislation changes or for a variety of other reasons. Changes may also be designed to improve the student learning experience or to respond to feedback from students, external examiners, accreditation bodies and industrial advisory panels.

To give you a taster, we have listed the compulsory and elective (where applicable) modules which are currently affiliated with this course. All modules are indicative only, and may be subject to change for your year of entry.


Course modules

Compulsory modules
All the modules in the following list need to be taken as part of this course.

Enterprise Systems

Aim

    The module aims to provide a systematic understanding and knowledge of the enterprise systems principles and how to use these systems to manage an enterprise. The course will also provide hands-on experience using SAP as a leading industry-standard software application.


Syllabus
    • Introduction to business functions, processes and data requirements within an enterprise.
    • Enterprise wide IT systems. Managing Enterprise through ERP.
    • Enterprise Resource Planning (ERP): concepts, techniques and tools.
    • ERP selection and implementation issues.
    • An Introduction to IoT and Cyber Security.
    • SAP based hands-on case studies.

Intended learning outcomes

On successful completion of this module you will be able to:

1. Describe the principles of business functions, processes and data infrastructure.

2. Explain the concepts, tools and techniques of Enterprise Resource Planning (ERP) and its related subjects such as IoT and Cyber Security.

3. Evaluate issues and challenges in ERP implementation and the importance of Enterprise-wide systems to business operations.

4. Identify the various criteria for ERP selection.

5. Demonstrate working/application knowledge on the use of SAP tool through hands-on case studies.

Operations Management

Aim

    To introduce you to core factors of managing operations.


Syllabus
    • An introduction to manufacturing and service activities.
    • Capacity, demand and load; identifying key capacity determinant; order-size mix problem; coping with changes in demand.
    • Standard times, and how to calculate them; process analysis and supporting tools; process simplification.
    • What quality is; standards and frameworks; quality tools; quality in the supply chain.
    • Scheduling rules; scheduling and nested set-ups.
    • Roles of inventory; dependent and independent demand; Economic Order Quantity; uncertain demand; inventory management systems and measures.
    • Information systems – at operational, managerial, and strategic levels; bills of material; MRP, MPRll and ERP systems.
    • Ohno’s 7 wastes; Just-in-Time systems (including the Toyota Production System, and Kanbans).
    • Class discussion of cases, exercises, and videos to support this syllabus.
Intended learning outcomes On successful completion of this module you will be able to:

1. Assess the key capacity determinant in an operation, and carry out an analysis to develop the most appropriate approach in response to changes in demand.
2. Select and apply appropriate approaches and tools to determine standards and improve processes.
3. Determine the information needed to support businesses, in particular manufacturing operations.
4. Assess and select appropriate Just-in-Time (JIT) tools to improve operations.
5. Develop appropriate quality systems for the whole of their supply chain – from supplier, through operations to customers – and ensure these systems are sustained and a culture of continuous improvement prevails.

Data Analytics

Aim
    To develop your understanding and practice of business data analytics to describe, predict, and inform business decisions.
Syllabus
    • Big Data and Business decisions.
    • Basic Data Analytics.
      • Usage of Tools for Data Modelling, Management and Analysis.
      • Data quality and system interoperability.

Intended learning outcomes

On successful completion of this module a student should be able to:

  

  1. 1. Distinguish the types of data typical in business management.

  1. 2. Construct data models from datasets representative of data extracted from business IT systems.

  1. 3. Evaluate reliability of datasets and devise ways to enhance trustworthiness of data extracted from business IT systems.

  1. 4. Analyse and investigate patterns from datasets representative of data extracted from business IT systems.

  1. 5. Present data analysis results to support management decisions.



Enterprise Modelling

Aim

    To extend your ability to evaluate integrated knowledge systems within the context of the wider enterprise environment through the application of modelling and simulation tools, techniques and methodologies.


Syllabus
    • Introduction to modelling: taxonomy, overview of methods and techniques;
    • Enterprise Modelling and lean concepts and architecture
    • Structured Systems Analysis methodology, Process description capture tools and techniques, Object state transition network;
    • Discrete-event simulation, Systems dynamics and Agent-based simulation techniques and methodologies;
    • Case study analysis, use of industry-based software tools
Intended learning outcomes On successful completion of this module you should be able to:
1. Distinguish the concepts of modelling approaches and architecture.
2. Analyse challenges in the capture and representation of business knowledge for the purpose of modelling.
3. Critically evaluate the opportunities in a business where modelling and simulation can add value.
4. Construct and apply different modelling & simulation tools used in producing enterprise models.

Supply Chain Management

Aim

    To introduce you to the wider issues surrounding the management and optimisation of supply chains.


Syllabus
    • Supply chain concepts

    • Supply chain strategy

    • Relationship management

    • Supplier Selection and Evaluation

    • Supplier Sustainability

    • Supply chain Planning

    • Design & Operating SC

    • Outsourcing Product Design and Manufacturing


Intended learning outcomes

On successful completion of this module you will be able to:

1. Evaluate issues surrounding the development of the right supply chain strategy for the business / product groups.
2. Create strategies for managing the information flows in a supply network in order to reduce the bullwhip effect and the challenges of accurate demand and forecast planning.
3. Evaluate the challenges with improving performance of supply networks and gain familiarity with the application of a variety of supply chain tools to help in the re-design of the SC.
4. Organize the complexities in managing and designing distribution centres so that they support the overall SC strategy and customer value proposition in the market place.
5. Integrate procurement and supplier management for the supply chain to function effectively.

 


Digital Engineering

Aim
    This module aims to provide a systematic understanding and knowledge of key concepts and principles for digital engineering and its current practices, tools and processes and future development. The course will also provide hands-on experience using digital engineering tools and methods to facilitate product and service development.
Syllabus
    • Introduction to digital engineering concepts.
    • Digital engineering tools and methods to support zero physical prototyping.
    • Internet of Things (IoT), Virtual and Augmented Reality (VR & AR).
    • Digital twins for product development.
    • Artificial intelligence and machine learning.
    • Digital engineering industrial case studies.
Intended learning outcomes

On successful completion of this module, you will be able to:

  1. Evaluate the principles of digital engineering, its applications and benefits in product and service development
  2. Critically evaluate the selection of digital engineering tools and methods.
  3. Evaluate the application of digital engineering tools and techniques to support product and service development.
  4. Manage the application of  using Virtual and Augmented Reality (VR & AR) tools to support zero physical prototyping.
  5. Evaluate the challenges in digital engineering implementation in industry.
 

Data Analytics and Artificial Intelligence​

Aim
    This module will provide the processes to design and develop artificial intelligence (AI) based approaches to be trained for data analytics on a spectrum of data types (e.g. messy data, data gaps or big data), whilst also considering the ethical implications. 
Syllabus
    • Theory of data analytics, AI, ML, data mining, statistics and supervised learning, e.g., probability, decision trees, regression and classification.   
    • Experience of real-world AI/ML applications, in areas such as engineering, business, social media, medical data and financial data  
    • Evaluate alternative ethical considerations including human-machine collaboration that are related to the use of AI/ML.  
    • The opportunity to work on industry problems that can benefit from AI/ML approaches. 
Intended learning outcomes

On successful completion of this module you should be able to:

  • Compare and contrast data analytics methods including machine learning (ML) in terms of its current and future concepts, principles and theories. 
  • Construct ML concepts and methods to impart innovative problem-solving skills in a variety of data maturity scenarios. 
  • Evaluate value creation opportunities from ML, develop value propositions and revenue models for businesses and organisations 
  • Construct data analytics-based methods for real world problems with the changing nature of digital technology infrastructure and varying volume and quality of data; 
  • Appraise ethical responsibility considering human-machine collaboration in data analytics by reflecting on intelligent systems that benefit society. 

Integrated Data Management

Aim
    This module provides the skills to design and develop integrated data management approaches and systems to address data related challenges. This includes managing large volumes of data from disparate sources, identifying and resolving data quality issues, handling disparate data lacking integration and generating insights for agile decision making that are integrated in terms of their data, models and visualisation for agile decision making.
Syllabus
    • Introduction to software programming with a view to developing data management systems
    • Evaluate existing standards related to data management
    • Apply methods for data needs analysis
    • Establish mechanisms for enabling connectivity of data acquired from alternative sources – e.g. people, sensors, 5G, IoT
    • Develop data structures and approaches to data modelling using ontologies and reference architectures
Intended learning outcomes

On successful completion of this module you should be able to:

  • Assess the system requirements for the integration and accessibility of data to deliver value in complex systems
  • Critically evaluate existing approaches to acquire data from fixed and mobile sources
  • Appraise strategies and techniques to measure and optimise the quality of data
  • Construct efficient data structures enabled by ontologies and reference architectures to allow continuous and standardised data flow
  • Justify mechanisms for allowing connectivity of data to enable links to models and visualisation platforms

Teaching team

You will be taught by leading academics and experienced practitioners in change management and IT drawn from Cranfield’s network of partners. The course is directed by an industrial advisory committee comprising senior representatives from leading manufacturing and business organisations. This means the skills and knowledge you acquire are relevant to employer requirements. The Course Director for this programme is Dr Samir Khan.

Cranfield University really helps you explore what you don't know and the support that the academic professors have given has been fantastic. The industrial partners you will be engaging with are also fantastic. 


The exceptional academic staff, state-of-the-art facilities and additional resources provided throughout the course highly contributed to an amazing academic year with top-level education services.

Accreditation

The Management and Information Systems MSc is accredited by the Institution of Mechanical Engineers (IMechE), the Royal Aeronautical Society (RAeS)Institution of Engineering & Technology (IET)on behalf of the Engineering Council as meeting the requirements for further learning for registration as a Chartered Engineer (CEng).

 

Candidates must hold a CEng accredited BEng/BSc (Hons) undergraduate first degree to show that they have satisfied the educational base for CEng registration.

 

Please note accreditation applies to the MSc award, PgDip and PgCert (if offered) do not meet in full the further learning requirements for registration as a Chartered Engineer.




Your career

Successful students go on to a wide-range of careers in manufacturing, logistics, IT, business systems analysis, manufacturing management consultancy, research and development, and academia. Opportunities are diverse and international, with graduates progressing to senior positions in industry.

Cranfield Careers and Employability Service

Cranfield’s Career Service is dedicated to helping you meet your career aspirations. You will have access to career coaching and advice, CV development, interview practice, access to hundreds of available jobs via our Symplicity platform and opportunities to meet recruiting employers at our careers fairs. Our strong reputation and links with potential employers provide you with outstanding opportunities to secure interesting jobs and develop successful careers. We will support you in the job application process for up to three years after graduation.



How to apply

Applications need to be made online. Click the 'Apply now' button at the top of this page. 

Once you have set up an account you will be able to create, save and amend your application form before submitting it.