Critically reviews theoretical aspects and the utilisation of supply chain analytics, data,

Produce different chart and analysis for your chosen dataset using Microsoft Power BI tool.


Rationale: This individual assignment critically reviews theoretical aspects and the utilisation of supply chain analytics, data, information management and relevant technologies, contributing to sustainability¬-based performance (i.e., social, environmental and financial).
Topic and application scenario

Topics are listed below, and you can choose one topic only. The choice of topic depends on the individual student’s interests.
In EVERY case, you must fully describe a real-world situation in which the chosen topic is to be applied: this is the Application Scenario. You must then produce one or more NotionStructuring models which help to clarify the situation that you are addressing. As a minimum, you should create a NotionStructuring Event Process Data model. 
You should assemble a dataset which is related to logistics and / or to supply chain. This dataset should be substantial, that is, needs a quantitative analytical treatment. You should assemble existing data rather than collect new (which is too time-consuming in one module).By way of guidance we suggest that you will need more than 500 rows (cases) if you are using a quantitative analysis tool. 100 cases would be a strict minimum.
You should address ONE of the following topics: this is the topic:
1.	Produce different chart and analysis for your chosen dataset using Microsoft Power BI tool. 
2.	Produce c-chart, p-chart, x-bar and range chart for your chosen dataset using a spreadsheet such as Microsoft Excel. 
3.	Design and prototype a relational database (five or more tables) and use it to store the contents of your dataset. Devise at least three queries which yield information from the database. Show these queries in SQL format and show also the results of the queries.
4.	Choose and use appropriate data analytics, such as text mining and analytics, cluster analysis, basket analysis, sentiment analysis, time series analysis. Other topics, such as business intelligence forecasting, may also be acceptable – get the module team’s approval in advance, though. Apply your chosen analytic approach to your dataset, and comment on the results.
5.	Learn and make basic use of the R programming language and its data analysis methods. Write a script in R and apply it to your dataset. It is acceptable to reuse an existing script, provided that you acknowledge its source and modify it so that it works with your chosen dataset.
Where applicable, to support your arguments, you should use detailed examples, figures and tables.
Sections, grades and learning objectives: The assignment should be structured in the following sections (see the structure in Table 1below). The detailed description for each section is included in the report template, provided on the next pages. The guidelines for grading and learning objectives (LOs) are also listed in Table 1which follows.You are encouraged to make extensive use of diagrams, models and tables.If you copy or otherwise reuse existing resources, whether from books, software or the Web, you must acknowledge the source and show the reader how to find the resource again. If you do not do this, action will be taken in accordance with University policy concerning plagiarism.
Table 1 Assignment structure, marks and learning outcomes
Section	Details	Weighting	LO
1) Introduction and scenario	Guiding the reader what is included in the assignment; sequence and brief explanation of the sections.	5%	LO2
2) Up-to-date literature review with a critical approach	Significance, breadth of sources, criticality, consistent referencing style, tightly connected with the topic / application and examples, clearly influences the whole assignment.	15%	LO1
3) Description and model of the application scenario	Description of the real-world situation in which the chosen topic is to be applied: this is the Application Scenario. One or more NotionStructuring models which help to clarify the situation that you are addressing. As a minimum, you should create a NotionStructuring Event Process Data model.	20%	LO5
4) Justification for analytical approaches adopted	Define the technological platform (or measures) that you think is the most suitable for the scenario described in section 3, explaining your choices. You will be judged on the appropriateness and effectiveness of your choices.	15%	LO3-LO4
5) 6) Analysis results and Conclusions	Apply your chosen techniques. Summarise your results. What recommendations, based on your analysis, would you make to managers? Critically self-evaluate the effectiveness of your work. What would you do differently if you had to do this assignment again?	35%	LO3-LO4
Overall quality	Logically written, overall tightly connected with the question  /  topic  /  application, high quality of referencing, tables, figures, models, data use and presentation.	10%	LO2

Keys - learning outcomes:
LO1 Demonstrate a systematic understanding of relevant theories at the forefront of the discipline that contribute to supply chain analytics
LO2 Critically and originally assess the role of information management and relevant technologies in supply chains working individually, with high quality of presentation
LO3 Critically debate and analyse how data and analytics create supply chain value through an appropriate management of information and data
LO4 Exhaustively understand capabilities and skills in advanced quantitative methods such as structuring rich data, big data, text mining, social media mining, data quality and cleansing, data visualisation and neural networks
LO5 Demonstrate competence in visual knowledge modelling and in understanding organisational information needs.

Guidelines and examples:
1.	Introduction and scenario
[Insert section 1]
Example: This assignment aims to address the application of clustering and sentiment analysis in client evaluations of the products and services of ABC Manufacturing. After the introduction, the second section provides literature review and critical analyses of the application. The choices of technique which were made are discussed in section three. The  assignment is concluded by section four, which presents and discusses the findings and provides recommendations for managers.
2.	Critical and up-to-date review of selected topics
[Insert section 2]
The solution is problem dependent, see examples and solutions we solved during tutorials.
The literature review should focus on industrial reports, case studies and research articles from reputable journals. The literature should also justify the application/topic. Criticality is important in this section: advantages, disadvantages and your own defensible views.
Additionally, you should use Harvard referencing style (see programme handbook or university website for the detail, given below).
https://libguides.hull.ac.uk/harvard
Alternatively you can watch this video

You should also use EndNote (available at the University, it is a commercial software) or Mendeley (free and can be used from home) for referencing. The following videos can help to learn how to use them. You can also use other relevant videos available on YouTube (for example, how to install Mendeley on your system etc]
https://www.youtube.com/watch?v=riqPfPvBCPU(EndNote)
https://www.youtube.com/watch?v=xLtk6n8cFdk(Mendeley)
Or use Zotero:

3.	Description and model of the chosen scenario
[Insert section 3]
4.	Justification for analytical approaches adopted
[Insert section 4]
5.	Analysis results and conclusions
[Insert section 5]
Present the results of your analytic techniques, etc.
6.	Discussion and conclusions
[Insert section 6]
You should provide a summary, theoretical implications, practical implications and future research or improvements possible.
Appendix: [Insert appendix here, if there is any. You should only include very relevant material that is cross referenced in the body/text.]
References:
[Include references here, Harvard Style]
Re-sit Note:
This assessment significantly focuses on examining contemporary concepts. A choice of various topics is provided. In the case of re-sitting, the student will NOT be allowed to work on the same topic, although the structure will remain the same. The student will have to select a new topic for his/her re-sit. Therefore, the assignment descriptor is also appropriate for the re-sit if required.
Specific Assignment Criteria
(Level 5 Generic assessment criteria and grading descriptors at the Programme handbook)
90+	A+	First	Outstanding in all respects	Subject to Module BoardAgreement & Before any penaltyapplied
This assignment counts 50% towards
your overall module grade.
80-90	A	First	Outstanding in most respects	
70-79	A-	First	Outstanding in some/one major respect	
60-69	B	2:i	Many very good features	
50-59	C	2:ii	Average; satisfactory evidence of overallgrasp	
40-49	D	Third	Adequate evidence of understanding	
35-39	E	Com Fail	Weak in some minor/one major area	
0-34	F	Fail	Weak in many/most areas	

	A+	A	A-	B	C	D	E	F	
1. Introduction
Guide the reader on what is included in the assignment; sequence and brief explanation of each section									No structure, sequence and brief explanation of the sections
2. A critical review of the topic and its contributions
High quality and broad range of literature sources for the arguments, reflects a critical literature review approach for the justification of the selected application, proving that it contributes to achieve sustainability-based performance in supply chain chains and its relevant domains (e.g., logistics, manufacturing, transportation and distribution)									Few (or no) relevant sources are used for the arguments or they are used in a confused, uncritical or superficial manner for the justification, not discussing how the topic contributes to achieve sustainability-based performance in supply chain chains and its relevant domains (e.g., logistics, manufacturing, transportation and distribution)
Sources/references are frequently explained individually so the reader can easily detect the findings of the study presented									References are often mixed up and they confuse the reader when they seek to find the past findings
Accurately & completely list all sources used, logically written and connected, software used for referencing as explained in the template									Missing list or inaccurate referencing, sloppily presented; typos & avoidable errors; no structure; jargon ridden; repetition & padding
3. Description and model of the chosen scenario

Clear, credible, well-researched scenario. 
How do we assess the quality and relevance of a NotionStructuring model? What is a good model?
•	Clear understanding of the principal notions – concept, procedure, event, operator, actor
•	Model which accurately represents the chosen scenario
•	Creative model with strong visual impact
•	Appropriate level of abstraction – just the right level of detail in each model
•	Exceptional models will use hierarchy, make appropriate use of notion types and include rich pictures or other appropriate images									The description of the scenario is incomplete, confused or not credible.

The models are very incomplete, inaccurate and / or make very poor use of the NotionStructuring notion types.
4. Justification for analytical approaches adopted

Excellent justification for the choice of analytical tool(s) made									Missing or very poor justification.
5. Analysis results and conclusions


Excellent application of the analytical tool(s) made									Missing or very poor application.
6. Discussion and conclusions									
Excellently summarises the findingsand discusses practical and / or theoretical implications									Not summarised or connected with the key findings and theoretical implications
Evidence-based recommendations for managers that are excellently connected with the literature and justified									Lack of evidence-based recommendations and loosely connected with the literature
Discussion with insightful and specific analysis									Lack of insightful analysis, only generic discussion included
 
Overall quality
Highly effective style of writing - All sentences/paragraphs/sections are logically written and connected									Repetitive, unclear writing, disjointed sentences/paragraphs/sections and they do not strongly intersect with assignment aims and create confusion
Tables, figures and latest data appropriately used									No tables, figures or out-dated data
Appropriate length									Under/over appropriate length
Grammar/spelling correct									Many grammar/spelling errors
Accurate referencing									Inaccurate or missing references