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Unit of study_

SMBA6003: Data Analytics and Modelling

Semester 2 Early, 2020 [Normal day] - Castlereagh St, Sydney

One of the most significant developments associated with the digital revolution is the increased availability of data. For managers and leaders in contemporary organisations, the ability to effectively analyse and draw useful inferences from data is critical. It is also important that managers can communicate complex interrelationships found in the data to senior management in a way that maximises the possibility that it can lead to favourable and sustainable change. Access to and use of data is critical to organisations in their need to effectively respond to a more volatile economic and financial environment, and Government intervention and regulation. Superior data analytic and modelling capabilities are increasingly seen as a source of competitive advantage, both for business and for employees working within business. This unit of study can deliver this competitive advantage in at least six distinct ways - (1) it will reveal the type of "internal" data that an organisation must compile for effective decision making; (2) it will identify the "external" data that must be used in combination with the internal data, and where that external data is sourced; (3) it will analyse the tools and modelling techniques that can be used to draw timely and relevant insights from a range of different forms of data; (5) it will examine how these tools and modelling techniques can be practically applied across a range of organisational settings; and (6) it will demonstrate how any findings should be communicated to time-poor senior management. As part of this unit of study, students will be given the opportunity to work with real-world data sets and case studies, and to apply those data sets to their own and other organisations.

Unit details and rules

Unit code SMBA6003
Academic unit Management Education
Credit points 6
Prohibitions
? 
None
Prerequisites
? 
None
Corequisites
? 
SMBA6001
Assumed knowledge
? 

None

Available to study abroad and exchange students

No

Teaching staff

Coordinator Rico Merkert, rico.merkert@sydney.edu.au
Guest lecturer(s) Hassan Swidan, hassan.swidan@sydney.edu.au
Lecturer(s) Rico Merkert, rico.merkert@sydney.edu.au
Type Description Weight Due Length
Assignment group assignment Team presentation
n/a
40% Week 05
Due date: 24 Aug 2020 at 12:00

Closing date: 24 Aug 2020
3 slides & 3 minutes per person
Outcomes assessed: LO1 LO2 LO3 LO4
Assignment Individual Assignment
n/a
30% Week 09
Due date: 27 Sep 2020 at 21:00

Closing date: 02 Oct 2020
5 pages
Outcomes assessed: LO1 LO2 LO3
Final exam (Take-home extended release) Type E final exam Final exam
Essay style answers around two questions/cases
30% Week 13
Due date: 02 Nov 2020 at 18:00
96+ hours
Outcomes assessed: LO1 LO2
group assignment = group assignment ?
Type E final exam = Type E final exam ?

Assessment summary

Group assignment/presentation: Students will be divided into teams of about 5 or 6 before the start of the first class. Your team will be allocated a topic and a company. You tasked with presenting to senior management of your company on the assigned topic. The team will receive a mark as a whole. However, there will be a peer review feedback mechanism. Peer evaluation is a regular task of any leader. It is not set up to punish a person who did not contribute equitably in hindsight. It is intended to encourage equitable contributions during the course of your team work.

Individual assignment: This assessment will be based around an data analysis issue of concern in Australia.

Final exam: This exam will cover all topics of the unit.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range

Description

High distinction

85 - 100

Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Distinction

75 - 84

Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Credit

65 - 74

Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.

Pass

50 - 64

Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school. 

Fail

0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

The standard Business School late penalties apply

Academic integrity

The Current Student website  provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.  

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

You may only use artificial intelligence and writing assistance tools in assessment tasks if you are permitted to by your unit coordinator, and if you do use them, you must also acknowledge this in your work, either in a footnote or an acknowledgement section.

Studiosity is permitted for postgraduate units unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission.

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

WK Topic Learning activity Learning outcomes
Week 01 27 July 2020. Introduction & Bring everyone up to speed data analysis session Seminar (4 hr)  
Week 02 3 August 2020 Topic 1: Macroeconomic variables and data collection/cleaning Topic 2: Macroeconomic linkages, visualization and data presentation Seminar (4 hr)  
Week 03 10 August 2020. Topic 3: Understanding and modelling demand functions and descriptive analysis (What has happened) Seminar (4 hr)  
Week 04 17 August 2020. Topic 4: Demand modelling exercise and Price/Inflation analysis Seminar (4 hr)  
Week 05 24 August 2020. Team presentations. Presentation (4 hr)  
Week 06 7 September 2020. Topic 5: Unit cost modelling and predictive analysis (What will happen in the future) Seminar (4 hr)  
Week 07 14 September 2020. Topic 6: Operational levers and profit Seminar (4 hr)  
Week 08 21 September 2020. Topic 7: Breakeven Modelling, Optimal Prices, Responding to Higher Unit Costs Seminar (4 hr)  
Week 09 28 September 2020. Topic 8: Risk Exposure Quantification, Natural Hedges, Optimization, Simulation and Forecasting (What should we do) Seminar (4 hr)  
Week 10 12 October 2020 Topic 9: Performance measurement and benchmarking analysis. & Revision. Seminar (4 hr)  

Attendance and class requirements

Lecture recordings: Note that MBA classes held at the CBD Campus are not systematically recorded and 100% class attendance is expected for each unit of the MBA program. If there are extenuating circumstances as to why you are not able to attend a particular class, please contact your unit coordinator as soon as possible, and also notify your group members (if the unit has a group work component). A unit requirement is 80% class attendance where some classes are mandatory, so those who drop below this level may not pass the unit.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Students are strongly encouraged to complete the prepatory online course before coming to class. This may involve up to 10 hours of online study depending on your familiarity with Excel.

While we don’t prescribe a textbook, the following provides a nice background reading: Prince, J.T. (2019). Predictive Analytics for Business Strategy: Reasoning from Data to Actionable Knowledge, International Student ed., McGraw-Hill Education (the US edition is 2018)

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. demonstrate and identify (1) the data a business needs to solve complex problems, (2) the key drivers of the demand for a business' product, (3) whether profitability increases in response to an increase in price or output and how this relates to the price elasticity of demand, (4) the key interrelationships between external and internal variables that are pivotal to understanding the business' risk and the management of those risks
  • LO2. quantify the impact of critical drivers that are external to the company, such as GDP, exchange rates, commodity prices and inflation, on revenue and cost streams and use this information for risk management purposes by utilising key statistical tools such as descriptive statistics, regression and simulation analysis
  • LO3. communicate complex ideas more effectively to senior management, determine the communication styles that senior management prefer, draw more effective graphical relationships between variables, construct a more effective powerpoint presentation, deliver a presentation that is more likely to be preferred by senior management and construct the most effective sequence of material in a presentation to generate the maximum amount of positive impression from senior management
  • LO4. collaborate more effectively with colleagues and peers to solve complex data-related problems.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

This section outlines changes made to this unit following staff and student reviews.

An online preparatory course was created for students with less experience with data analytics. Additional simulation exercises have also been created.

Students are encouraged to bring a laptop with Excel to class.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.