| Unit name | Supply Chain Analytics |
|---|---|
| Unit code | MGRCM0017 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Professor. Holland |
| 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
The expanding availability of data and computational power means that analytics approaches have become pervasive in business decision making. This is especially true in supply chain management. A knowledge of what analytical approaches are used and how they are employed is essential for the supply chain manager. Analytics subdivides into three branches: (1) descriptive – summarising data to extract meaning. This is especially important in supply chain management in the context of identifying whether target metrics are being achieved; (2) predictive – techniques to allow measures for which future forecasts are required to support planning e.g. demand; (3) prescriptive – using models to analyse available data for advice on best, or optimal, decisions.
How does this unit fit into your programme of study?
The programme MSc Global Operations and Supply Chain Management provide you with strategic and operational insight into how operations and supply chain can be designed and managed. As part of this process, whether to consider performance of various options, or as information to support the strategic or operational choice process, analytical information will be essential. This unit provides you with the tools to produce and understand that technical information to support informed supply chain and operations management.
An overview of content
This unit introduces you to some important methods relevant to supply chain management from the fields of analytics, namely descriptive, predictive and prescriptive analytics. Some principal descriptive analytical methods for understanding data related to various aspects of management a supply chain are investigated e.g. exploratory descriptive statistics, correlation analysis. For predictive analytics, causal (regression) and time series forecasting methods will be considered. For prescriptive analytics, inventory optimisation, service provision and resource allocation are crucial elements in the design of efficient and effective supply chains. This unit introduces you to the analytical techniques from the discipline of management science required to be able to do this.
How will students personally be different as a result of this unit
On completion of this unit, you will realise that knowledge of analytics plays a key role in supply chain management. You will be able to select appropriate techniques for different situations and then implement and interpret the result of the analysis into useful information for key stakeholders.
Learning Outcomes
On successful completion of this unit, students should be able to:
The teaching method will be centred around a 3-hour lectorial session each week for ten weeks. The lectorial contains a combination of lecture, computer workshop and case study analysis. Post lectorial you wlll be required to work independently on problem-based study. Lecture elements are aimed at communicating the main methods, techniques and ideas of the unit. Computer workshop elements demonstrate the implementation of important calculations and provide an opportunity to discuss interpretation of output. You will also be expected to spend a significant number of hours on independent study, practicing formative problems that require implementation of covered techniques in order to fully develop your understanding of the material. These will be provided each week with solutions made available the following week. Office hours provide an opportunity to receive feedback on solutions that are not clear.
Tasks which help you learn and prepare you for summative tasks (formative):
Each week you will be provided with questions to practice the tools and techniques introduced in that week. Solutions to these problems will be available the following week. Office hours are available to clarify elements on solutions that are not clear. In week 4 the class will be a formative exercise in analysing and reporting on a case study, in preparation for the summative case study task.
Tasks which count towards your unit mark (summative):
There will be two equally weighted individual case studies, 1500 words each.
The first will be based on predictive analytics. It covers all learning outcomes from the perspective of prescriptive analytical models.
The second will be based on the application of descriptive and predictive analytics. It covers all learning outcomes from the perspective of descriptive and predictive analytics.
When assessment does not go to plan
If students do not pass the unit in aggregate across the two assessments and they are eligible for a reassessment, they will be reassessed in like-for-like assessments of the components for which they have not achieve the pass mark.
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. MGRCM0017).
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 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.
