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Postgraduate

MSc Fashion Analytics and Forecasting

Course background image

College
London College of Fashion
Start date
September 2022

MSc Fashion Analytics and Forecasting is a unique, fully online offer which combines fashion business expertise with machine learning, forecasting and statistical data analysis. You will be part of an online community of practice that benefits from immersive industry participation. On completion of this course you will be well placed for a wide range of careers where strategic decision making is enhanced by the use of quantitative methods.

Why choose this course at London College of Fashion

  • This MSc is currently the first Master's programme in the world to apply data analytics and forecasting in the context of fashion business.
  • This programme aims to enable graduates to use data analytics to creatively solve complex real-world problems in the fashion industry from design, production and consumption challenges through to considerations of environmental impact.
  • This is the first Master's programme to bring together the expertise of the three schools of London College of Fashion in the application of highly contextualised data analytics to Fashion Design and Technology, Fashion Media and Communication and Fashion Business disciplines across the global fashion industry.
  • This programme offers a premium online learning experience with a focus on the use of live industry briefs to develop problem solving skills.
  • Graduates will gain skills in the use of a variety of industry-relevant software tools for the collection, analysis and visualisation of data. Such tools currently include Qualtrics, R Studio, IBM SPSS Statistics, Microsoft’s SQL Server, Microsoft Power BI, and Adobe In-Design. The list is regularly reviewed with industry partners to ensure currency.
  • This programme has been developed in consultation with our industry partners in response to an identified skills gap and so positions graduates well for employment, consultancy or research futures in the fashion and allied industries.

EDITED

The MSc Fashion Analytics and Forecasting is supported by EDITED, the leader in Retail Market Intelligence. EDITED helps retailers increase margins, generate more sales and drive better outcomes through AI-driven market data, analytics and research.  Brands like Zara, Puma, John Lewis, Marni and Tommy Hilfiger use EDITED’s suite of Market Intelligence products to create retail strategies and make better assortment, pricing and promotion decisions everyday.

Latest news from this course

LCF facilities

  • An image of the LCF library at John Prince's Street
    Credit: © Ana Escobar © Ana Escobar, An image of the LCF library at John Prince's Street © University of Arts London
    Library and archives

    Take a tour of LCF's world renowned fashion library, ideal for research and study.

  • Students in Lime Grove's print workshop with print works on high table tops
    Students in Lime Grove's print workshop with print works on high table tops. Photography by Ideal Insight.
    Media facilities at Lime Grove

    Take a tour of Lime Grove's media facilities from drawing studios to photographic studios to darkrooms.

  • Canteen, Mare Street
    Canteen, Mare Street Photography by: Ideal Insight
    Social spaces

    Explore the social spaces across LCFs six sites to study, relax or meet friends.

Course overview

The global fashion industry is a highly competitive market in which the consumer now demands sustainable, efficient, and inclusive business operations. External shocks create risk and opportunity within the industry so accelerating the need for digital innovation and e-commerce initiatives. The need to harness data to improve fashion business models is at its peak in an industry that has traditionally relied on intuition and creative direction for setting global trends. Data-driven insights and accurate forecasts are needed to support investment decisions, model demand for new products, technologies and business practices. As such, fashion businesses must develop a strategic response to continual global economic change, sustainability agendas and technological developments to retain their competitive advantage. Accordingly, there is a growing need for graduates who are competent and confident in skills of data analysis.

The course is delivered fully online. It is unique in LCF as the first of our taught Master’s courses to bring together the teaching and research expertise of all three schools. The Fashion Business School (FBS) leads the course with specialist units delivered by staff from School of Media and Communication (SMC) and School of Design and Technology (SDT). As an advanced signatory to the UN Principles of Responsible Management Education (PRME), FBS tailors its curriculum to meet the six principles of responsible management education. The curriculum emphasises the development of an understanding of the contemporary global fashion industry coupled with quantitative data literacy and data analytics in a world where unforeseen events have reinforced the importance of data-driven insights. 

The course aims to provide you with a solid grounding in both theoretical and practical approaches to quantitative data analysis and visualisation within the wider disciplines of supply chain management, consumer insights, economics, and research methods as relevant to the contemporary global fashion industry. Our learning approaches encourage you to work autonomously and creatively whilst enabling you to develop confidence in becoming a reflective learner, strategic thinker, and effective decision-maker.

Contact us

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Course units

The Course is divided into three 15-week ‘blocks’ of study (full-time). The first block is 60 credits and students who successfully complete this block are eligible to progress to the second block. The second block is a further 60 credits and students who complete blocks 1 and 2 are eligible to continue to the third and final block unit, Master’s Project. Successful completion of this 60 credit unit renders you eligible for the award of a Master’s degree. The final award classification is based upon the Master’s Project only.

Postgraduate Block 1

Unit Name: Forecasting & the Global Fashion Economy (20 Credits)

This unit will introduce you to the economic environment of the global fashion industry via an in-depth foundation in fundamental micro and macroeconomic concepts that lead to sustainable economic growth. You will be introduced to the economics of supply chain management and a wide range of advanced univariate forecasting techniques and their application via R Studio for predicting future economic trends relevant to the global fashion industry. The basic coding skills which you learn in this unit will provide a foundation for future units. 

Unit Name: Collaborative Challenge (20 Credits)

This unit is your opportunity to innovate and explore developmental processes and engage with collaborative working practices. You will develop your professional negotiation, teamwork and networking skills that are essential in the cultural, entrepreneurial, and creative industries. The emphasis of this unit is on developing and showcasing your consultancy skills. You can engage with industry or college-based briefs.

Unit Name: Connecting with Global Fashion Consumers (20 credits)

This unit is delivered by LCF’s School of Media and Communication. You will be introduced to the principles of communication with diverse consumer audiences and the role of data in fashion communication. The unit also emphasises data protection, privacy, and the ethical use of data in communications. You will develop your skills for storytelling and engaging global fashion consumer audiences through written and visual narratives. 

Postgraduate Block 2

Unit Name: Quantitative Research Methods (20 Credits)

This unit is designed to support the development of the research design of your MSc Master’s Project and your advanced quantitative research skills for consumer data collection and analysis. You will develop the advanced skills necessary for critically evaluating secondary research, designing reliable and valid quantitative research instruments, and conducting hypothesis tests with parametric and non-parametric statistical tests which will benefit the remainder of this course and your future employability. You will obtain experience in using industry relevant software to design, analyse and evaluate a consumer survey in response to a current fashion business problem of your choice.

Unit Name: Principles of Machine Learning for Fashion Analytics (20 Credits)

This unit aims to develop your understanding of e-commerce led fashion business models and introduce the basic theory underpinning key machine learning and data mining techniques for uncovering hidden insights from Big Data in fashion. The unit will focus on the practical application of supervised learning algorithms and data mining techniques on fashion consumer data with a critical appraisal of the associated ethical issues. You will be exposed to a toolbox of automated machine learning algorithms. The skills you develop will enable you to successfully apply a selected machine learning or data mining algorithm on fashion-related Big Data. 

Unit Name: Data Driven Fashion Product Innovation (20 Credits)

This unit is delivered by LCF’s School of Design and Technology with the aim of challenging traditional assumptions of fashion industry practices by using data in fashion product innovation. Fashion design requires a dynamic supply chain management process to meet contemporary demands for better products. This in turn requires data analytics to inform the development of sustainable business models. The strategic application of complex data from a wide range of sources will validate a concept and situate this in a contemporary context that drives advanced practices in fashion product innovation. You will learn to critically analyse the impact of changing consumer preferences on product life cycles, supply chain strategies, and sustainable business models. The analysis will support you to propose a conceptual framework and/or fashion product innovation idea for a specific market or sector.

Postgraduate Block 3

Unit Name: Master’s Project (60 Credits)

The Master’s Project is an important piece of work central to achieving the course aims, which will provide an opportunity for you to demonstrate your knowledge and skills in relation to the course learning outcomes. Throughout the Master’s Project, you are guided and supported by tutorials and peer and staff evaluation at interim stages. You will be allocated a supervisor for your project and will complete a learning contract outlining how you intend to develop and deliver your project.

The credit framework conforms to the University of the Arts London framework in which the unit of credit is 20 credits (equivalent to 200 hours of student study time). All credits on the MSc programme are at postgraduate level 7.

Learning and teaching methods

The following teaching and learning methods are employed to support the integrated aims of the course outcomes: 

  • Online asynchronous (pre-recorded) and online synchronous (live) lectures and briefings (large group)
  • Online synchronous seminars (small group) 
  • Online asynchronous and online synchronous practical workshops and demonstrations (small group)  
  • Online academic skills workshops including library induction (small group) 
  • Online synchronous tutorials (individual or small group)
  • Online asynchronous and online synchronous peer-to-peer and/or tutor feedback sessions (individual or small group)
  • Presentations (live or pre-recorded)
  • Independent learning (individual or small group)

Assessment methods

The following assessment methods are employed to support the integrated aims of the course outcomes: 

  • Formative assessment opportunities are provided within each unit to enable you to check the progress of your learning.
  • A range of varied summative assessment methods are used including:
    • Project portfolio comprising of technical prototypes and presentations
    • Essays and reports
    • Time-constrained analysis exercises
    • Master’s project, which requires the production of a body of work through independent study that demonstrates a high level of quantitative research, advanced critical and analytical skills, an innovative approach to problem-solving and an ability to work in collaboration with the fashion industry. 

Staff

James Clark is course leader for both MSc Fashion Analytics and Forecasting and Executive MBS. He is a senior lecturer in buying and merchandising for a number of courses at London College of Fashion. He is the author of Fashion Merchandising: Principles and Practice (Palgrave). James Clark has lectured in buying and merchandising since 2007 and prior to that worked in numerous roles within UK fashion retail businesses such as Debenhams, Viyella and House of Fraser, with his last substantive position being that of head of merchandising. He has consulted with a number of brands including Gant and House of Fraser. Read James Clark's full profile here.

Dr. Lan Wang is Lecturer in Economics and Finance at the Fashion Business School. Lan is a member in Centre for Business and Climate Change at University of Edinburgh Business School. She completed her PhD in climate finance at University of Edinburgh, MSc in Carbon Finance from University of Edinburgh (2013), and MSc in Corporate Finance from ICMA Centre, University of Reading (2010). Lan also completed two years of financial industrial work experience at Bank of China and participated in consulting and research projects granted by World Bank and British Consulate Guangdong General in China. Lan’s research interests are in green finance, sustainable investment, climate policy, and carbon market design.

Dr. Roberto Murcio is an Associate Lecturer in Data Analytics attached to the Fashion Business School. He is also a Senior Research Associate at the Centre for Advanced Spatial Analysis, UCL. Roberto completed his PhD in Applied Mathematics and an MSc in Computer Sciences at Mexico's National University. He regularly collaborates with different local authorities in the UK to advise on various sociodemographic projects. Roberto's research interests are in Urban Analytics, with a focus on urban networks and he models large Time-Series datasets to forecast future trends in transport, employment, and housing.

Angela Buttolph is a journalist, broadcaster and author, and Associate Lecturer for MA Fashion Journalism at the School of Media and Communication. A fashion journalist for over twenty-five years, she has worked at Elle, Vogue, i-D, InStyle and Grazia, contributing to many more. She has covered the shows worldwide and interviewed fashion’s greatest luminaries including Anna Wintour and Karl Lagerfeld. Angela has presented fashion series on ITV, BBC and C4 and is author of Kate Moss: Style, and co-author of Phaidon’s Fashion Book. She is currently a contributing editor at Grazia and also writes for The Telegraph and Google’s Think With Google blog.

Dr Liang Lu is Senior Lecturer in Economics and e-Commerce at the Fashion Business School. She is Course Leader MSc. (integrated) Strategic Fashion Management. Liang is also a Research Member at the Centre for Competition Policy at the University of East Anglia (UEA), where she previously held a Post-Doctoral Research Fellowship. Before her post-doc, Liang graduated through a fully funded Ph.D. in Economics at UEA (2017), an MSc in Economics from the University of Warwick (2013) and a BSc in Business Economics from UEA (2011). Liang researches and publishes on Industrial Organisation, Competition and Consumer Policy and Behavioural and Experimental Economics, with applications to e-commerce, fashion and regulated sectors such as energy and water. Read Liang's full profile here.

How to apply

Information for disabled applicants

UAL is committed to achieving inclusion and equality for disabled students. This includes students who have:
     
  • Dyslexia or another Specific Learning Difference
  • A sensory impairment
  • A physical impairment
  • A long-term health or mental health condition
  • Autism
  • Another long-term condition which has an impact on your day-to-day life
Our Disability Service arranges adjustments and support for disabled applicants and students. Read our Disability and dyslexia: applying for a course and joining UAL information.

Entry requirements

The standard entry requirements for this course are as follows:

  • An Honours degree at 2.1 or above in a related discipline (e.g., any Fashion Business School undergraduate course, or undergraduate courses from other institutions in Business, Marketing or Management, or with a Product, Enterprise or Quantitative focus). 
  • OR equivalent qualifications.
  • OR applicants with a degree in another subject may be considered, depending on the strength of the application. We welcome applications from graduates with qualifications in broader fashion and creative subjects who can demonstrate an aptitude for using data and data analytics to support effective decision making.

1. APEL (Accreditation of Prior (Experiential) Learning)

Applicants who do not meet these course entry requirements may still be considered in exceptional cases. The course team will consider each application that demonstrates additional strengths and alternative evidence. This might, for example, be demonstrated by:

  • Related academic or work experience (minimum of three years)
  • The quality of the personal statement
  • A strong academic or other professional reference
  • OR a combination of these factors

Each application will be considered on its own merit but we cannot guarantee an offer in every case.

2. English Language Requirements

IELTS level 7.0 with a minimum of 6.0 in reading, writing, listening and speaking. Please check our main English Language Requirements.

Selection criteria

  • Sufficient prior knowledge and experience of and/or potential in a specialist subject area to be able to successfully complete the programme of study and have an academic or professional background in a relevant subject for the Master’s.
  • An aptitude for, or clear interest in, quantitative research, applied statistics, data analytics, data mining, machine learning, big data analytics, or forecasting from a fashion business context. 
  • A willingness to work as a team player.
  • Good language skills in reading, writing, listening and speaking.
  • The ability to work independently and be self-motivated.

Making your application

This section includes all the information you need on how to apply, how your application is considered and what happens next.

UK/EU students can apply to a postgraduate course at LCF by completing a direct application.

Deferring your place

This course accepts requests from offer holders to defer their place for one academic year. Deferral requests are granted on a first-come, first-served basis until all deferral places are filled, or a deadline has been reached, whichever is sooner. Read our Admissions Policy for details, including how to request a deferral and by when.

External Student Transfer Policy

If you are currently studying at another institution and if you have successfully completed 60 credits in the equivalent units/modules on your current PG course and wish to continue your studies at London College of Fashion, you can apply to transfer. The Admissions Tutor will consider applications on a case by case basis, subject to places being available. You must apply directly to the course via the course webpage as early as possible.

Please check our Student Transfer Policy for more important information and be ready to provide us with your current course handbook and transcripts.

Please be ready to provide an official document (translated into English if necessary) from your current university, explaining the learning outcomes of the units you have completed.

Additional information required to apply to this course

Curriculum Vitae

A Curriculum Vitae (C.V.) in support of your application. This should include your full education and employment history.

Motivational statement

You should communicate your motivation for studying this course in no more than 500 words. You should use the following questions as a guide:

  • Why do you want to study for this MSc?
  • What are your main areas of research interest and how do they fit with the structure of this course?

What happens next

All application forms, personal statements and relevant documents are read and considered by the course team against the selection criteria listed in the Entry requirements and Selection Criteria sections.

How we notify you of the outcome of your application

The result of your application will be communicated to you through your UAL Portal. If your application has been successful, you will receive a full offer pack including details of accommodation, fees, and other important information.

Applications for this course can only be accepted for this year of entry. Applications for deferred entry cannot be accepted.

Application deadline

12 January 2022 or 13 April 2022

The equal consideration deadline has now passed. However, this course will remain open to applications until places have been filled. We recommend you submit your application as early as possible to allow the Admissions team to quickly resolve any queries.

If this course requires a portfolio, we will request this separately after initial processing of your application is complete. Once we request your portfolio, you will have 7 days to submit it.

When you'll hear from us

Once you’ve sent in your application, this will be sent through to our course teams for review. Find out more about what happens after you apply.

This section includes all the information you need on how to apply, how your application is considered and what happens next.

There are 2 ways international students can apply to a postgraduate course:

Read our immigration and visa information to find out if you need a visa to study at UAL.

You can only apply to the same course once per year. Any duplicate applications will be withdrawn.  Read the UAL international application advice for further information on how to apply.

Deferring your place

This course accepts requests from offer holders to defer their place for one academic year. Deferral requests are granted on a first-come, first-served basis until all deferral places are filled, or a deadline has been reached, whichever is sooner. Read our Admissions Policy for details, including how to request a deferral and by when.

External Student Transfer Policy

If you are currently studying at another institution and if you have successfully completed 60 credits in the equivalent units/modules on your current PG course and wish to continue your studies at London College of Fashion, you can apply to transfer. The Admissions Tutor will consider applications on a case by case basis, subject to places being available. You must apply directly to the course via the course webpage as early as possible.

Please check our Student Transfer Policy for more important information and be ready to provide us with your current course handbook and transcripts.

Please be ready to provide an official document (translated into English if necessary) from your current university, explaining the learning outcomes of the units you have completed.

Additional information required to apply to this course

Curriculum Vitae

A Curriculum Vitae (C.V.) in support of your application. This should include your full education and employment history.

Motivational statement

You should communicate your motivation for studying this course in no more than 500 words. You should use the following questions as a guide:

  • Why do you want to study for this MSc?
  • What are your main areas of research interest and how do they fit with the structure of this course?

What happens next

All application forms, personal statements and relevant documents are read and considered by the course team against the selection criteria listed in the Entry requirements and Selection Criteria sections.

How we notify you of the outcome of your application

The result of your application will be communicated to you through your UAL Portal. If your application has been successful, you will receive a full offer pack including details of accommodation, fees, and other important information.

Applications for this course can only be accepted for this year of entry. Applications for deferred entry cannot be accepted.

Application deadline

12 January 2022 or 13 April 2022

The equal consideration deadline has now passed. However, this course will remain open to applications until places have been filled. We recommend you submit your application as early as possible to allow the Admissions team to quickly resolve any queries.

If this course requires a portfolio, we will request this separately after initial processing of your application is complete. Once we request your portfolio, you will have 7 days to submit it.

When you'll hear from us

Once you’ve sent in your application, this will be sent through to our course teams for review. Find out more about what happens after you apply.

Fees and funding

Home fee

£9,240

This fee is correct for 2022/23 entry and is subject to change for 2023/24 entry. Tuition fees may increase in future years for new and continuing students on courses lasting more than one year. For this course, you can pay tuition fees in instalments.

Home fees are currently charged to UK nationals and UK residents who meet the rules. However, the rules are complex. Find out more about our tuition fees and determining your fee status.

International fee

£18,890

This fee is correct for 2022/23 entry and is subject to change for 2023/24 entry. Tuition fees may increase in future years for new and continuing students on courses lasting more than one year. For this course, you can pay tuition fees in instalments.

Students from countries outside of the UK will generally be charged international fees. The rules are complex so read more about tuition fees and determining your fee status.

Scholarship search

Careers and alumni

We are in discussion with several of our current industry partners as collaborators and providers of live industry projects for this course. These partnerships are currently pending validation and legal approval.

"This course is going to provide us with future industry leaders capable of both staying ahead of fashion trends but also anticipating changing customer behaviour and how to react fast.”

Nishi Overton (Head of Marketing and Scaling at Amazon)

“Data analytics is crucial in retail. The technical proficiency this course teaches is a great opportunity for someone that has a retail background and wants to expand their skill set to make better insights with data.”

Rosie Hood (PhD, Senior Data Scientist at EDITED)

"Talented analysts are a sought after resource in retail. One of the main challenges is finding analysts who are skilled at the quantitative elements but are also tuned into the bigger picture of the business needs and the impact their number crunching has as part of a profit making venture. So, the idea of this (course) whereby you’re taking a business student and teaching the ways of data and analytics, I think that would equip your students with quite a valuable skillset to get themselves hired.”

Matthew Walsh (Director of Data and Retail at IMRG)