Supply Chain Modelling and Analytics - BUSN8034

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2022 to 2023
Canterbury
Spring Term 7 15 (7.5) Preetam Basu checkmark-circle

Overview

Today's increasingly complex global operations and new digital technologies are giving rise to a sea of data and increased need for modelling supply chain environments with the objective of measuring the performance of various strategies, methods and technologies. Supply chain modelling and analytics skills are in high demand and are a must-have for supply chain management career success. This module will cover the following indicative topics:

1. Supply chain modelling: This part aims to formulate key activities of the supply chain while emphasizing both the need for formulation and implementation. These include Networks and Routing Transportation models, Resource Allocation and Production Scheduling models, Inventory management models, Quality control models, and Project Management.

2. Spreadsheet Modelling: This part will cover the use of basic and advanced spreadsheet tools and functions (e.g., sorting, ranges, look-up tables, formatting, plotting graphs, optimisation tools, statistical functions).

3. Analytics Techniques: This part demonstrate how analytics techniques, such as Forecasting, Regression, Descriptive analytics, Probability and Decision Analysis and Optimisation, can be applied to improve supply chains’ efficiency and effectiveness by enabling data-driven decisions at strategic, operational and tactical levels.

Details

Contact hours

Private Study: 117

Contact Hours: 33

Total: 150

Method of assessment

Main assessment methods:
Group Project: Group presentation (10%), Group spreadsheet model (10%), Group report (1,500 – 2,000 words) (10%) (30% in total)
VLE Test (20%)
Individual computer-based project including spreadsheet model and report (1,500 – 2,000 words) (50%)

Reassessment methods :
100% coursework

Indicative reading

The University is committed to ensuring that core reading materials are in accessible electronic format in line with the Kent Inclusive Practices.

The most up to date reading list for each module can be found on the university's reading list pages.

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes.
On successfully completing the module students will be able to:

- Provide critical awareness of the nature of various modelling methods, stimulating students to appreciate the value of modelling in logistics and supply chain management to solve steady-state and dynamic problems.

- Apply core methodologies used in supply chain analysis and modelling, including statistics, regression, optimization and probability,

- Demonstrate an in depth knowledge of a number of Excel tools and functions that are commonly used in practice including the use of spreadsheet models for complex business decisions.

- Critically evaluate some of the software used in logistics and supply chain management and provide basic understanding and usage of such tools.



The intended generic learning outcomes.
On successfully completing the module students will be able to:

- Communicate findings effectively to specialist and non-specialist audiences.

- Demonstrate integrative capabilities to co-ordinate group tasks or eventually lead a team of multifunctional individuals;

- Write a technical report that incorporates many facets of IT such as presentational and graphical devices

- Effectively employ computer tools including the use of software and coding to provide practical solutions for modern logistical problems.

Notes

  1. Credit level 7. Undergraduate or postgraduate masters level module.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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