BUSINFO 705 : Decision Analytics

Business and Economics

2024 Quarter Four (1248) (15 POINTS)

Course Prescription

Explores how business analytics can be used to improve business processes and decisions. The link between quantitative models and qualitative processes is explicitly explored. Decision biases are considered in the context of decision modelling. Monte Carlo simulation and optimisation are among the decision tools taught.

Course Overview

Decision modelling is a core competency in today’s competitive business environment. The course will focus on teaching key analytical modelling techniques for decision making, considering the main trade-offs among different modelling tools. In addition to being familiar with specific modelling tools (including optimisation and Monte Carlo simulation), students will be able to apply these tools to model an open-ended situation, explain the key decision biases encountered in practice, and use models for decision making and guiding business intuition.

The course’s specific toolset of Monte Carlo simulation and optimisation is fundamental for business decision-making. Simulation is widely used in many fields such as operations and finance, for market analyses and behaviour models. Optimisation is a key methodology that is crucial in daily operations. Both tools are readily available and accessible through the use of software such as Excel and Analytic Solver. This course aims to guide its students towards a proper understanding of such tools and software, to ensure that good models are created to facilitate effective business decision-making.

Course Requirements

No pre-requisites or restrictions

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity

Learning Outcomes

By the end of this course, students will be able to:
  1. Apply key analytical modelling techniques for decision making, considering the key trade-offs between different modelling tools (Capability 1)
  2. Manage and assess the trade-off between modelling assumptions and tractability in authentic case studies (Capability 1 and 2)
  3. Formulate , justify, and evaluate models for decision making (Capability 2 and 3)
  4. Present and articulate your own opinions both in class exercises and for your models on key modelling assumptions and likely decision biases in using the models (Capability 1, 2, 3, 4.1, 4.2, 4.3 and 5.1)
  5. Contribute to a team to complete an open-ended modelling project (Capability 3 and 4.3)

Assessments

Assessment Type Percentage Classification
Quizzes 35% Individual Test
Project 30% Group & Individual Coursework
Case Study 25% Individual Test
Interactive Assesment 10% Individual Coursework
Assessment Type Learning Outcome Addressed
1 2 3 4 5
Quizzes
Project
Case Study
Interactive Assesment
Since assignments will be discussed in class, no late submissions can be accepted. Students must pass the final test in order to pass the course. 

The in-class participation mark depends on you contributing in class related activities (both online and in person); the quality of your participation matters. 

Workload Expectations

During a typical teaching week, the class will meet for 2 hours of interactive lectures and 2 hours of tutorials. For the 10 teaching weeks of a quarter, this totals to 40 hours. Since the course as a whole represents approximately 150 hours of study, that leaves a total of 110 hours for independent work, including reading, reflection, preparing for and completing assessments/exams.

Delivery Mode

Campus Experience

Attendance is required at scheduled activities including tutorials to complete components of the course.

Lectures will be available as recordings along with online learning aids throughout the quarter, as noted as helpful from students in past semesters. Due to the classes' interactive nature, however, in-class attendance is expected. 

Attendance on campus is required for the test.

The activities for the course are scheduled as a standard weekly timetable.

Learning Resources

Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).

Please remember that the recording of any class on a personal device requires the permission of the instructor.

There is no required textbook but the following texts are recommended as useful reference resources.

Camm, J.D., J.J. Cochran, M.J. Fry, and J.W. Ohlmann (2020) Business Analytics (4th Ed.). Cengage. Note: This text may also be useful for BUSINFO 700 as it covers material needed for both courses.

Powell, S.G., and K.R. Baker (2017) Business Analytics: The Art of Modeling with Spreadsheets (5th Ed.). Wiley, NJ. This text adopts a philosophy similar to this course. 

Student Feedback

At the end of every semester students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback and respond with summaries and actions.

Your feedback helps teachers to improve the course and its delivery for future students.

Class Representatives in each class can take feedback to the department and faculty staff-student consultative committees.

Information received about the course's contents, structure, and delivery will be considered for continuous improvement purposes for the current and future semesters. For example, the updates in this course's delivery mode (above) is based upon student feedback from last year's surveys.

Academic Integrity

The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed for potential plagiarism or other forms of academic misconduct, using computerised detection mechanisms.

Class Representatives

Class representatives are students tasked with representing student issues to departments, faculties, and the wider university. If you have a complaint about this course, please contact your class rep who will know how to raise it in the right channels. See your departmental noticeboard for contact details for your class reps.

Inclusive Learning

All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.

Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website http://disability.auckland.ac.nz

Special Circumstances

If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.

If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.

This should be done as soon as possible and no later than seven days after the affected test or exam date.

Learning Continuity

In the event of an unexpected disruption, we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and course assessment continues to meet the principles of the University’s assessment policy. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator/director, and if disruption occurs you should refer to the university website for information about how to proceed.

Student Charter and Responsibilities

The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html.

Disclaimer

Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.

In this course students may be asked to submit coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. In exceptional circumstances changes to elements of this course may be necessary at short notice. Students enrolled in this course will be informed of any such changes and the reasons for them, as soon as possible, through Canvas.

Published on 26/10/2023 09:40 a.m.