| Unit name | Digitalisation, Big Data and Value Creation |
|---|---|
| Unit code | EFIMM0152 |
| Credit points | 30 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2D (weeks 19 - 24) |
| Unit director | Dr. Liu |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
none |
| Units you must take alongside this one (co-requisite units) |
none |
| Units you may not take alongside this one |
none |
| School/department | School of Management - Business School |
| Faculty | Faculty of Social Sciences and Law |
Why is this unit important?
Digital technologies like big data, artificial intelligence, automation, and cloud computing are playing an increasingly important role in today’s business and management sphere. Any future business leaders must understand how this transformation plays out, its driving forces, and how to navigate and drive this transformation in order to create more value in an effective and sustainable way.
This unit is important because it will enable students to develop a deeper understanding of digitalisation and the digital economy through an immersive learning experience. Students will be introduced not only to key theories, concepts, and cases of digitalisation but also to a variety of widely-used big data analytics software programmes for them to gain practical knowledge of the use of big data in today’s business world. Upon completion of the unit, students will be able to critically analyse organisations’ digital strategies, develop their own digital strategies and business models, as well as create big data analytics.
How does this unit fit into your programme of study
As the Pathway Unit for MSc Management (Digitalisation and Big Data), this unit offers students a focused learning experience for exploring the impact of digital technologies on today’s business world. Students will have had a solid understanding of the basic business and management issues from other units in their programme, and this unit will provide them with an opportunity to concentrate on studying the impact of digital on business and management and how organisations can better adapt to the digital future.
An overview of content
The taught content will include the following theories, concepts and practical knowledge: the digital economy, digitalisation strategies, business model canvas, adapting value proposition, harnessing customer networks, turning data into assets, platform thinking, innovating by rapid experimentation, big data fundamentals and data analytics software programmes.
How will students, personally, be different as a result of the unit
Upon successful completion of this unit, students will be able to critically analyse organisations’ digital strategies, develop their own digital strategies and business models, as well as create big data analytics. They will be able to do these by applying key concepts and theories of digitalisation to critically appraise and develop digital strategies and by identifying novel digital technologies and unmet market needs to design value propositions and revenue models. They can also choose to use big data analytics to facilitate their evaluation of potential value creation opportunities and develop new business models to create and deliver such value.
Learning Outcomes
By the end of this unit, a successful student will be able to:
This unit takes a balanced teaching approach featuring both student-centred learning activities and teacher-centred lectures. This is designed to deliver all Intended Learning Outcomes and to ensure students learn in a structured and guided environment. Teaching content includes both theories and real-life business cases for students to develop a balanced understanding of digitalisation theories and practices. More specifically, a series of lectorials (3 lectorials/week, over weeks 19-23 in TB2-D) will be provided on the topics and themes such as the digital economy, business model, digitalisation strategies, and big data. Out of these, 9 lectorials will be on ‘digitalisation’, using a mixture of lectures and case studies seminars to deliver teaching on the topics of digital economy, business model and digitalisation strategies. The case studies seminars will be student-centred learning activities, where students will work in groups to discuss real business cases on digitalisation, debate about the strengths and weaknesses of strategies utilised and propose for potential digitalisation strategies based on their online research about the relevant case companies. 6 lectorials will be devoted to ‘big data’, covering big data fundamentals and practical sessions on using data analytics software programmes such as Tableau. On these sessions, students will be provided with real-life datasets to ‘play with’ using the software. The unit offers 45 contact hours in total.
Tasks which help you learn and prepare you for summative tasks (formative):
1. Groups will have the opportunity to present their business models to obtain feedback from the teacher and their peers.
2. Students will be supervised to use one of the big data analytics programmes to develop a data analytics demo.
Tasks which count towards your unit mark (summative):
1. Group project (10-15 min presentation) (40%) [ILO1, 4, 5]:
Students will work in groups to identify a value creation opportunity and digital technologies that can be utilised to explore this opportunity and develop a business model for the identified value creation opportunity. They will use the Business Model Canvas to present their business model and deliver a group presentation to explain the business model orally. Groups can choose to use big data analytics to facilitate their evaluation of potential value creation opportunities and the presentation of their business models.
2. Individual essay (3000 words) (60%) [ILO 2, 3]:
Students will choose from 5 real-world business cases of digitalisation and use the key concepts and theories of digitalisation taught in the lectures to produce a critical appraisal of the chosen company’s digitalisation strategy, analysing the advantages and shortcomings of the digitalisation strategies applied and making suggestions for potential digitalisation strategies taking into account of changing market conditions, new technologies available, and so on.
When assessment does not go to plan
When a student fails the unit and is eligible to resubmit, failed components will be reassessed on a like-for-like basis.
Group project reassessment: if a student fails overall because of a fail mark on the group project, they will need to write a 500-word reflexive analysis of why their group project has failed and how the group could have improved it. (40%) [ILO1, 4, 5]
Individual essay reassessment: if a student fails overall because of a fail mark on the individual essay, they will need to choose a new case from 5 provided cases (they cannot choose the one they selected for the first submission) and write a new essay based on this new case (60%) [ILO 2, 3].
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. EFIMM0152).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
