Programme information

We live in a world that is becoming ever more digitalised in every aspect of life, including businesses. Our MSc Digital Innovation Management is a unique programme to equip you with highly sought-after skills of entrepreneurship and technologies in setting up and managing technology-based or other businesses and enterprises. Through this programme, you will gain advanced knowledge and develop skills with a focus on the latest advances in digital technologies, such as cloud systems, Internet of Things, application development, content creation, and also tools for market analysis, data analytics and machine learning. Our MSc Digital Innovation Management programme combines essential digital technologies knowledge with business insights and strategy skills, which will enable you to increase business efficiency, reduce operational costs, access wider markets and increase revenues.

This programme is aimed both at individuals looking to operate in digital businesses, and entrepreneurs and innovators of new technology-based enterprises. The programme is delivered by leading digital technology and business experts in their respective areas. Students will benefit from our research-informed teaching accompanied by various bespoke tailored practical sessions including technological workshops and business case studies and enjoy regular guest lectures delivered by our network of fellow industrial experts. Prospective students will also benefit from the highly regarded Loughborough Enterprise Network, which actively supports students and graduates on their business establishment through bespoke coaching and workshops.

Studying MSc Digital Innovation Management will arm you with the frontier knowledge and drill your skills to ladder up your careers in the fields of technology development, management and digital businesses.

Entry requirements

An honours degree (2:2 or above), or an equivalent overseas qualification recognised by Loughborough University.

Overseas qualification equivalencies

English Language requirements

All applicants for admission to Loughborough University must have a qualification in English Language before they can be admitted to any course or programme, whether their first language is English or not.

More on the Loughborough University website

Fees and funding

Tuition fees cover the cost of your teaching, assessment and operating University facilities such as the library, IT equipment and other support services. The tuition fees for 2019/20 entry are:

  • £10,550 (UK/EU)
  • £24,750 (International)

University fees and charges can be paid in advance and there are several methods of payment, including online payments and payment by instalment. Special arrangements are made for payments by part-time students.

View scholarships for 2019 entry

Programme aims

  • Develop students' knowledge and expertise in digital technologies and innovation, through practical application and analysis
  • Develop students' knowledge and understanding of key management and enterprise strategies
  • Develop students' critical thinking in order to evaluate the factors affecting the success of the innovation process
  • Use action-based learning principles to provide individuals with the necessary skills to undertake innovation management positions within the digital technologies sector

Programme modules

This programme covers a wide range of topics; to give you a taster we have expanded on some of the core modules affiliated with this programme and the specific assessment methods associated with each module.

Core modules

Collaborative Project

With a multi-talented group of students, you will work on a brief from a real company looking to solve a real social or business problem.
Together with your student team, you will research and build solutions to a business problem, supported by our project tutors, clients and staff. Previous clients include Foster + Partners, Speedo, The London Legacy Development Corporation as well as many other companies, start-ups and charities.
The Collaborative Project provides a means for you to engage in critical enquiry and to be exposed to project-based teamwork in multicultural and interdisciplinary settings. By undertaking this module, you will strengthen your cooperative and collaborative working skills and competencies, whilst raising your awareness and appreciation of cultural and disciplinary diversity and differences.
The Collaborative Project aims to provide you with a hands-on experience of identifying, framing and resolving practice-oriented and real-world based challenges and problems, using creativity and appropriate tools to achieve valuable and relevant solutions. Alongside the collaborative elements of the module, you will be provided with opportunities to network with stakeholders, organisations and corporations, which will give you the experience and skills needed to connect to relevant parties and potentially develop future employment opportunities.

Learning Outcomes

On completion of this module, you will be able to:
  • Work effectively in diverse and interdisciplinary teams
  • Undertake and contribute towards a project-based development process
  • Apply critical enquiry, reflection, and creative methods to identify, frame, and resolve issues and problems at hand
  • Identify user and stakeholder needs and value creation opportunities, whilst collecting and applying evidence-based information and knowledge to develop appropriate insights, practices and solutions
  • Identify, structure, reflect on key issues and propose solutions to problems in creative ways
  • Enhance your appreciation for diversity and divergent individual and disciplinary perspectives
  • Be able to provide structured, reflective and critical feedback to peers and other stakeholders
  • Plan and execute a project plan including scope, resources and timing
  • Effectively communicate ideas, methods and results to a diverse range of stakeholders
  • Use multiple, state-of-the-art date media and technologies to communicate with collaborators
  • Make informed, critical and reflective decisions in time-limited situations.


Assessment consists of 100% coursework which is made up of:
  • Individual Reflective Essay (55%)
  • Team Project Report (40%)
  • Peer Evaluation (5%)

Innovation Management

This module will include: the innovation process and models for innovation; the importance of innovation to the economy; government support for innovation; and the importance of innovation in the contemporary business environment.
The module aims to equip you with an in depth knowledge of the innovation process, its importance to the economy and an understanding of the factors affecting its success.

Learning Outcomes

On completion of this module you should be able to:
  • Explain the complexity of the innovation process
  • Highlight the types and patterns of innovation
  • Understand the interrelationship between an organisations environment and its innovative capability
  • Relate innovation theory to the performance of organisations
  • Interpret company performance in relation to the dynamic environment in which it operates
  • Synthesise information from appropriate sources
  • Demonstrate rational use of business and risk analysis tools to analyse company performance
  • Select and use appropriate investigative and research skills
  • Demonstrate effective report writing skills
  • Demonstrate commercial awareness
  • Recognise ethical dilemmas and corporate social responsibility issues.


Assessment is made up of 1x 3,000 word report (100%).


The Dissertation module will equip you with the relevant skills, knowledge and understanding to embark on your own research project. You will have the choice of three dissertation pathways:
  • A desk based research project that could be set by an organisation or could be a subject of the student's choice
  • A project that involves collection of primary data from within an organisation or based on lab and/or field experiments
  • An Internship within an organisation during which time students will complete a project as part of their role in agreement with the organisation (subject to a suitable placement position being obtained)
  • By undertaking a dissertation at master's level, you will achieve a high level of understanding in your chosen subject area and will produce a written thesis or project report which will discuss your research in more detail.

Learning Outcomes

On successful completion of this module, you should be able to demonstrate knowledge and understanding of:
  • The importance of project planning
  • The importance of a clear hypothesis or research question
  • The ethical implications of research
  • The relevant empirical data and methodologies for data collection or knowledge assimilation for the subject area
  • Methods of data analysis and their suitability for the intended data
  • The areas of expertise or publications of the major individuals or organisations in the subject or business area
  • The previous research or current knowledge in the specific subject or business area
  • Theoretical perspectives relevant to your chosen topic
  • The most effective methods of presentation for data or knowledge
  • Developing a clear, coherent and original research question, hypothesis or business problem in a suitable subject area
  • Synthesising relevant sources (e.g. research literature, primary data) to construct a coherent argument in response to your research question, hypothesis or business problem
  • Analysing primary or secondary data collected by an appropriate method
  • Critically evaluating data collected in context with previously published knowledge or information
  • Engaging in critical debate and argumentation in written work
  • Applying principles of good scholarly practice to your written work
  • Performing appropriate literature searching/business information searching using library databases or other reputable sources
  • Planning a research project and producing a realistic gantt chart demonstrating your intended timelines
  • Synthesising information from appropriate sources
  • Demonstrating rational use of research method tools
  • Selecting and using appropriate investigative and research skills
  • Demonstrating effective project planning skills
  • Finding and evaluating scholarly sources
  • Engaging in critical reasoning, debate and argumentation
  • Demonstrating effective report writing skills
  • Recognising and using resources effectively
  • Successfully managing a project from idea to completion
  • Demonstrating commercial awareness or the impact of knowledge transfer in a business or research environment.


100% Coursework consisting of:
  • Research proposal (10%)
  • Dissertation report (90%)

Optional modules (choose five)

Information Management

This module provides an introduction to information management concepts and frameworks, including ethics data management, document and content management, data storage and operation, information security management, and information quality management. Students will be introduced to big data systems and related technologies, and explore data integration and interoperability between data stores, applications and organisations. The teaching will provide real world examples of how business intelligence enable workers to get value from information, and how digital organisations have established a system of decision rights over data. Students will learn how architecture, modelling, and design are used to discover, analyse, represent and communicate data requirements within the digital industries.

Learning Outcomes

On completion of this module students:

Will have gained knowledge of information systems with communication networks and should be able analyse an organisation’s data asset to develop strategies to increase its value, protect the data asset from third-parties via access controls, data modelling and design and comply with data regulations.

  • Best practices in information management
  • Business intelligence activities to achieve maximum benefit from information
  • Context of data management activities
  • Emerging trend in information storage techniques to manage rapidly growing data assets
  • Key elements and operations of Internet and communication networks that enable data management
  • Demonstrate underpinning concepts of information management
  • Apply best practices in data management to comply with data regulations and ethics
  • Familiarise with technical concepts such big data and security management
  • Synthesise necessary information to evaluate data rates for different communication networks that affect the data quality
  • Develop customised data strategies for organisations to maximise the value of information
  • Critically evaluate the existing information management strategies to improve the data usability, comply with regulations and ethics
  • Critically analyse the drawbacks of legacy communication systems that hinder data management
  • Advise an organisation to develop effective information management plans using the latest technologies.


Assessment is made up of an examination and an in-class test.

  • Preliminary Assessment (35%)
  • Final Assessment (65%)

Principles of Data Science

The aims of this module are to;
  • Introduce students to the concepts of data science and their use in Data Analytics Systems.
  • Enable them to gain theoretical and practical experience in simulating complex data systems involved in a variety of industries including, smart digital systems, Internet of Things, financial industries, and entertainment industries.

Learning outcomes

On completion of this module, you should be able to:
  • Critical awareness of the challenges caused by the proliferation of data generation processes
  • Systematic understanding of the process of extraction of actionable knowledge from data to enable decision making
  • Theoretical background in descriptive and inferential statistics for big data
  • Machine learning algorithms for classification and pattern analysis in large data sets
  • Advanced analytical techniques, such as model building, network graph analysis, outlier detection
  • Methods for maximising predictive performance of algorithms and validation techniques
  • Analyse common summary statistics and use statistical tests to determine confidence for a hypothesis
  • Demonstrate ability to fit a distribution to a dataset and use that distribution to predict event likelihoods
  • Examine and evaluate the capabilities of available classification algorithms and be able to select and use suitable for a particular data set
  • Integration of knowledge to critically evaluate different scenarios/problems and design practical solutions to data related problems
  • Application of knowledge to through programming skills to build predictive and descriptive models for a given dataset utilising available labelled data sets
  • Apply creativity and problem solving skills in the industry/research for challenging problems in a timely manner
  • Communicate complex problems and associated solutions to specialist and non-specialist audiences
  • Evaluate problems and design solutions to those problems through scholarship gained through self-directed study.


  • In-class test (30%)
  • Group project report (70%)

Digital Application Development

In this module Python programming tools and environments will be covered in combination with the understanding of programming in C/C++ which are fundamental tools for developing digital systems and applications. Topics include: computer programming, objective foundation, and advanced programming techniques such as class, structure, pointer, and simulation.
The aim of this module is to provide students with an understanding and programming skills for developing digital applications and simulations.

Learning Outcomes 

On completion of this module students should be able to:

  • Demonstrate programming skills in C/C++ and Python
  • Demonstrate necessary programming techniques to develop digital applications and simulations
  • Show knowledge of programming structure and skills in general
  • Understand how to use digital data processing tools and functions
  • Understand the techniques used in developing applications and related computer simulations
  • Understand the use and concept of advanced techniques of class, structure, and pointer
  • Identify, utilise and optimise tools, algorithms and functions for simulation of digital applications
  • Implement functions and algorithms in the programming languages
  • Develop digital media applications and simulations
  • Solve other industrial complex problems involving digital processing algorithms
  • Find solutions for practical problems by reasoning, deduction and implementing from idea to final application
  • Understand the abstract features from complex objects/problems and develop ideas into algorithms
  • Fulfil the research and development requirements in a range of digital systems and digital technologies sectors.


Assessment is made up of 1 x 1,700 word report (60%) and 1 x 1,300 word report (40%).

Media Design and Production

This module introduces the you to applications containing multimedia design, creation and distribution over networks. In particular, multimedia transmission aspects over the Internet Protocol are covered.
First, the production side is covered, including video and audio capturing, synchronisation, recording and interchange formats, and compression workflows. Fundamental knowledge on sound engineering and audio technology, including the design, manipulation and production of audio, will be given to you.
In the second part, different classes of media applications are presented, such as conversational (e.g., Skype, audio-visual conferencing), streaming applications (e.g., Video on Demand), and broadcast applications (e.g., mobile TV, satellite TV), and how those applications are classified according to their bandwidth requirements, packet loss, latency, jitter, and synchronisation requirements. This is then followed Internet-based transmission methods, protocols, and techniques for robust media application delivery.
In the third part, audio-visual media quality assessment techniques and Quality of Experience (QoE) models are presented, where media quality is studied using the principles of human perception of audio/video. Examples from modern media transport methods (e.g., HTTP adaptive streaming) with a view to maximising the end-users’ QoE. User interfaces for interactivity (e.g., motion and video sensors, touch and gesture interfaces) and emerging interaction technologies and associated examples will also be presented.

Learning Outcomes

On completion of this module, you should be able to:
  • Demonstrate knowledge of media applications that are in use in modern digital systems, media quality assessment and Quality of Experience (QoE) models, user interfaces and multi-modal interaction technologies.
  • The principles of multimedia production and requirements of multimedia delivery over networks, in particular the Internet
  • Quality of Service parameters, classes of multimedia services, Internet Protocol suite
  • Quality of Experience, relations between QoS and QoE, user interfaces
  • Define the streams making up a multimedia application, how they are produced, express their transport mechanisms, and associated QoS requirements
  • Analyse the metrics associated with a transmission environment in terms of their suitability for supporting certain multimedia applications
  • Discuss how quality assessment is performed
  • Formulate multimedia applications with realistic design constraints and associated QoE considerations
  • Extensively use the knowledge gained in practical media application design and implementation work
  • Apply their knowledge on certain statistical analysis techniques learned in this module on other real-world problems
  • Develop skills to recognise, analyse and solve challenging problems with attention to details
  • Present themselves in the areas of digital content creation, streaming media, IPTV, mobile multimedia applications and user experience design.


  • Coursework (30%)
  • Exam (70%)

Internet of Things and Applications

The next stage in the Future Internet is to progressively evolve to a network interconnected with environments including objects. The Internet of Things (IoT) is involved in interaction and communication between objects and furthermore, with the environment to support decision making, improve situational awareness, increase operational efficiency and enable to explore new business models.
This module explores the emerging computing concepts and deployment of emerging IoT platforms and devices. The module will present the usage scenarios of communication and highly scalable consumption of data from geographically dispersed physical objects and sensors and the processing and delivery of such data to end-users. Sensing, tracking, monitoring, actuator, data & control service, data processing, information management, integration methodology, and M2M are among the other topics covered. Students will also be introduced to recent examples of smart cities & smart homes.
The aim of this module is to provide you with the knowledge and understanding of computing concepts related to the emerging IoT platforms and devices and their deployment.

Learning Outcomes

On completion of this module, you should be able to:
  • Demonstrate understanding of the main concepts into the usage scenarios of IoT communication and highly scalable consumption of data from geographically dispersed physical objects and sensors, as well as the processing and delivery of such data to end-users
  • Interaction and communication between objects and with the environment to support decision making, improve situational awareness, and increase operational efficiency
  • Modern applications of smart cities and smart homes
  • Understand the concepts pertaining to the IoT systems
  • Critically analyse and reflect on the limitations and problems faced in those systems and relate some possible solutions
  • Analyse the emerging IoT platforms and devices, and the associated technologies considered in their design
  • Distinguish the requirements pertaining to different contextual information collected and exploited within different IoT scenarios
  • Apply the acquired IoT knowledge in designing future intelligent systems, particularly in sectors that are closely related to smart cities, homes, & eHealth
  • Demonstrate the technologies and research capabilities in the smart systems & Internet technologies areas.


  • Coursework (40%)
  • Exam (60%)

Advanced Big Data Analytics

This module is likely to explore the following topics: big data and associated challenges; machine learning for predictive analytics: generative models, reinforcement learning; neural networks and deep learning; deep learning techniques for dimensionality transformations and reductions; architectures for big data: introduction to Hadoop and map reduce; and visualisation tools for big data systems.
The aims of this module are to: introduce the concept of Big Data systems and the challenges posed by such systems; and introduce the requirement of advanced analytics, processing techniques and architectural solutions to tackle the problems encountered.

Learning Outcomes

On completion of this module you should be able to:
  • Describe the theoretical background of big data, and recognise the need for big data analytics
  • Have a critical awareness of machine learning algorithms for data analytics in big data systems
  • Describe distributed architectures of big data systems including database technologies used in industrial big data systems
  • Understand signal processing techniques for big data systems with advanced matrix manipulation
  • Appreciate various visualisation tools and techniques
  • Select and apply various machine learning algorithms to a given data set to interpret the data and make necessary predictions
  • Demonstrate ability to evaluate and select an appropriate database technology for a given need for big data storage and retrieval
  • Analyse the need for visualisation and employ appropriate visualisation tools
  • Critically analyse building blocks of a practical big data systems for performance improvement
  • Demonstrate programming skills related to data analytics and usage of associated tools
  • Formulate creative data solutions that start with cleaning up raw data sets, to discover new patterns that are underlying, to make necessary predictions, utilizing established state-of-the-art tools and techniques
  • Develop experimental, analytical and problem solving skills in data driven applications
  • Illustrate professional report writing, presentation and communication skills to communicate complex ideas to expert and non-expert audiences
  • Develop creative thinking skills to demonstrate ways of solving problems with existing tools.


Assessment will be coursework based, consisting of:

  • Individual Theoretical Analysis (40%)
  • Group Technical Report / Simulations (60%)

Cloud Technologies and Systems

This module introduces the students to cloud computing paradigm: motivation, key features, and overview of cloud system models. Cloud computing fundamentals are presented, such as scalable computing over the Internet, virtual machines and virtualization of clusters, performance metrics for cloud computing. The module also looks at cloud architecture design (cloud service models, service-oriented architecture, management, data­centre design and interconnection networks, architecture design of computation and storage cloud. Basic cloud programming principles are described.
This module aims to provide students with an in depth knowledge on cloud computing basics and features.

Learning Outcomes

On completion of this module you should be able to:
  • Demonstrate knowledge of cloud computing fundamentals, architectural design specifics of the cloud based computing and communication systems, as well as network virtualisation technologies, and be able to relate their knowledge to real-world examples
  • Understand cloud computing fundamentals
  • Understand virtualisation of operations
  • Understanding of cloud architecture design
  • Comprehend the cloud computing paradigm
  • Formulate scalable computing architectures
  • Know the performance requirements of various cloud architectures
  • Apply basic cloud programming principles
  • Apply the gained knowledge in practical cloud solution design and implementation
  • Demonstrate competitiveness in cloud systems.


  • Coursework (30%)
  • Exam (70%)

Cloud Applications and Services

This module gives a brief overview of the cloud technology and covers cloud applications and challenges, such as energy efficiency in cloud systems, mobile cloud computing, cloud multimedia rendering, streaming, coding, transcoding, caching, adaptation, design etc. Also, cloud networking and related topics are addressed. Privacy and security issues in cloud services are also covered. The cloud case studies and business models are presented.
The aim of this module is to provide the students with an overview of the cloud technology with a special emphasis on cloud applications and the associated challenges.

Learning Outcomes

On completion of this module, you should be able to:
  • Develop an overview of the cloud technology, demonstrate specific knowledge in cloud applications and the challenges that are associated with making such applications available to the end-users via cloud technology
  • Understand the principles of cloud computing technology, cloud applications, and the associated challenges
  • Understand cloud networking and related topics
  • Identify privacy and security issues in cloud services
  • Apply cloud case studies and business models
  • Identify the requirements pertaining to the digital applications used in cloud services
  • Design cloud computing service solutions
  • Apply gained academic knowledge and experience in real world scenarios
  • Apply their critical analysis and problem solving skills in the industry for tackling problems and providing solutions for cloud applications and services
  • Demonstrate the necessary knowledge and skills required by R&D and services providers in the cloud computing and applications/services domain.


  • Coursework (30%)
  • Exam (70%)

Strategy and Planning

This module will explore the fundamentals of business planning and scenario planning for strategy development. Students will use and understand frameworks for running business ventures, including: operations management and financial statements. Students will develop an understandinf of business simulation software and how they can be used to run a business. Investigation techniques for trend forecasting will also be part of the module teaching.

Learning Outcomes

On completion of this module students should be able to:

  • Appraise the relevance of forecasting and scenario creation for strategy development.
  • Critique and select appropriate techniques for future forecasting
  • Demonstrate scenario development as a technique for strategic planning
  • The complexities involved with starting up and running a business venture
  • Critical assessment of a potential product or service
  • Compare and contrast a range of design techniques for generating key insights to inform future strategy
  • Demonstrate rational use of business tools/frameworks to analyse company performance
  • Demonstrate effective communication to persuade and influence stakeholders
  • Critique different business tools/frameworks used to analyse company performance
  • Develop and demonstrate a range of presentation techniques which could include storyboarding, video, UX simulation, rendering and animation, as appropriate to the design concept
  • Develop skills related to the use of business simulation software
  • Develop and communicate insights gained from research in a credible and convincing manner suitable for specialist and non-specialist audiences
  • Work effectively in a team and demonstrate recognition of an individual’s contributions to a group activity
  • Successfully manage a project from idea to completion.


Assessment is made up of two pieces of group project courseworks:

  • Foresight and strategy scenarios (50%)
  • New business planning (50%)

Marks will be adjusted according to peer feedback.

Digital Technologies for Market Analysis

The aims of this module are to familiarise students to the importance and practices of market research and analysis and equip them with skills to design, perform and present effective and creative market research projects powered by modern digital technologies.

Topics covered include:
  • Market research and analysis within the landscape of technological influence
  • Planning and designing market research utilising digital technologies for value-added effects
  • Fundamentals of digital tools for market research: research gamification, online communities, eye tracking, visual attention detection, crowdsourcing, mobile surveys, IoT/Sensor networks, and mobile ethnography
  • Advanced data analytics for market research: Media analytics, text analytics, facial expression analysis big data analytics
  • Data visualisation techniques for effective market research delivery
  • Ethical issues surrounding market analysis techniques and digital mechanisms to overcome those issues such as privacy preserving analytics

Learning outcomes

On completion of this module, you will be able to:
  • Demonstrate knowledge of commonly used methods for market research and analysis utilizing digital technologies;
  • Critically analyse methodological issues in different research techniques, and ethical issues surrounding those techniques
  • Evaluate the relative importance of various emerging forms of research tools for data collection
  • Compare and contrast various methods for analysis of collected data to gain relevant insights
  • Use market research as a tool for generating insight and informing business decisions
  • Independently design and conduct market research utilizing a multitude of digital tools
  • Critically select appropriate methods of research among various digital tools suitable for a given scenario
  • Use relevant data visualization techniques to present information to various audiences
  • Research and organise information from a range of sources relating to a given subject
  • Present one’s work in professional and technical reports targeting specialist and non-specialist audiences
  • Articulate arguments effectively under timed conditions and in assessed coursework.


  • Individual Theoretical Analysis (30%)
  • Market Research Group Report (70%)

Optional modules (choose one)


This module will include: entrepreneurship and the economy; the theories of entrepreneurship; recognizing and measuring entrepreneurial tendencies; and entrepreneurship in different organizational contexts.
The aims of this module are to introduce you to the field of entrepreneurship; to examine the role entrepreneurship plays in modern economies; to analyse the different types of activity contained within the definition, and the main theoretical and analytical approaches used to understand the concept; to consider entrepreneurial innovation at different stages of a business, from start-up to more mature firms; to enable you to assess their own entrepreneurial tendencies; and to enable you to test their theories in a mini research project.

Learning Outcomes

On completion of this module, students should be able to:
  • Identify the varying and pervasive roles of entrepreneurship within economies
  • Understand the different contexts in which entrepreneurs operate
  • Appreciate the approaches developed by researchers in attempting to understand the entrepreneurial process
  • Posess a firm academic and empirical understanding of the dimensions and role of entrepreneurship in different entrepreneurial settings
  • Have the ability to interpret data and contextualize commentary and analysis relating to the field
  • Implement and demonstrate argumentation and research skills
  • Demonstrate effective report writing and presentation skills
  • Demonstrate resourcefulness and initiative to choose topics of interest and carry out data interpretation.


  • Coursework (80%)
  • Research presentation (20%)

Intellectual Property

This module will include aspects of intellectual property law, the types of intellectual property, using intellectual property for commercial advantage, how to apply for intellectual property, and intellectual property database searching.

The aim of this module is to equip students with a knowledge of the various types of intellectual property, searching intellectual property databases, the legal basis of intellectual property rights, the application process for obtaining intellectual property and its importance to the innovation process and the entrepreneur.

Learning Outcomes

On completion of this module students should be able to:

  • Explain the importance of intellectual property as an asset
  • Understand the complexity of IP law and the protection process
  • Know the commercial value of the various types of intellectual property
  • Interpret data and information in order to make effective decisions
  • Perform intellectual property searches
  • Provide advice on company strategy
  • Select and use appropriate investigative and research skills
  • Demonstrate effective report writing skills
  • Work effectively in a team
  • Demonstrate good oral communication and presentation skills
  • Recognise and use their resources effectively
  • Demonstrate problem solving capability
  • Demonstrate a creative approach to communication.


  • Group Presentation (25%)
  • Case study (75%)

Understanding Organisational Failure

You will look at the innovation process and risk assessment methods for avoiding failure. We will also look at the risk taking traits of entrepreneurs and the attitude towards failure in society.
The aims of this module are to:
  1. Examine organisational failure, the threat of failure, and their effects at various levels of analysis and key stages in the organisational life cycle
  2. Identify the underlying logics and social, economic and political contexts that define and shape organisational success and failure
  3. Analyse the role, responsibility, and accountability of various organisational stakeholders in contributing to or preventing organisational failure

Learning Outcomes 

On completion of this module you should be able to:
  • Identify the multiple causes of failure and interconnectedness of these;
  • Identify the ways in which organisations and individuals can learn from failure;
  • Recognise the value of failure as a positive step;
  • Recognise the need for resilience in the case of failure;
  • Demonstrate rational use of business and risk analysis tools to analyse company performance;
  • Select and use appropriate investigative and research skills;
  • Demonstrate effective report writing skills;
  • Demonstrate commercial awareness;
  • Demonstrate problem solving capability


  • Peer reviewed tutorial participation (10%)
  • Case study (90%)

What makes this programme different?

  • You will develop key skills in innovating and realising new digital enterprises
  • You will combine advanced knowledge in latest and emerging digital technologies with innovation, business and management concepts
  • You will be in the best position to start or advance a career in technology development, technology management, digital enterprises or relevant fields

Who should study this programme?

Our Digital Innovation Management MSc programme is most desirable for technologists with business aspirations and people with business or entrepreneurship backgrounds who want to acquire key skills in enabling digital technologies and practices.

Future career prospects

Taking this programme will equip students with key technologies and skills on how to combine Internet technologies to create services with viable business management. Graduates are likely to develop their own start-ups by applying their strong technological background and entrepreneurial knowledge. Others may join new SMEs or work at established Internet technology and telecommunication companies with accelerated career development prospects.

Your personal development

The careers and employability support on offer at Loughborough University London has been carefully designed to give you the best possible chance of securing your dream role.

Loughborough University London is the first of its kind to develop a suite of careers-focused activities and support that is positioned as the underpinning of every student’s programme. Opportunities include employability assessments, group projects set by a real businesses and organisations, company site visits and organisation-based dissertation opportunities.


Modules are assessed by a combination of essays, group exercises, presentations and time constrained assignments. Subject to your choices, there may also be exams. Take a look at our modules to see what assessments you can expect to undertake.

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