| Unit name | Behaviour, Decision Making and Analytics |
|---|---|
| Unit code | MGRCM0035 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Zhang |
| 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?
Organisations that use analytics create value by supporting data-driven decision making. While descriptive, prescriptive and predictive models are constantly improving, an important consideration in the production and consumption of business analytics models is the role and impact of decision-making behaviour. Indeed, it is not enough to have a technically correct model; it is also important to understand how actual behaviour is captured in models, and how behaviour can affect their use in practice. This unit will provide students with a grounding in behavioural decision research relevant to a business analytics context.
How does this unit fit into your programme of study?
The unit complements other units in the course by offering a behavioural lens that can be adopted in the conduct of analytics projects.
An overview of content
At the start of the unit, students will explore critical factors affecting decision making at individual, group and organisational levels. Next, students will learn about a range of analytical approaches to model decision making behaviour in various contexts. In the final part of the unit, students will examine issues related to the role and impact of emergent technologies to support business decision making.
How will students, personally, be different as a result of the unit
On completion of this unit, students will be able to ground their analytics knowledge and skills on state-of-the-art behavioural decision research, and use it to design or evaluate analytics projects from a behaviourally-informed perspective.
Learning Outcomes
On completion of this unit, students will be able to:
1) Explain how cognition and heuristics impact managerial judgement within a business analytics context and recognise biases in others. (ILO1)
2) Evaluate how users of decision-making technologies deal with incomplete and imprecise information, subjective boundaries, and uncertainty. (ILO2)
3) Develop an appreciation of analytical modelling for developing theories of decision making. (ILO3)
4) Analyse the role and impact of emerging technologies to support business decision making. (ILO4)
The learning process will be based on a combination of asynchronous activities and in-person lectorials. Some of these sessions may be hosted by guest speakers from industry or other academic institutions. Emphasis will be placed on research, case studies and other learning activities. Students will interact and communicate in lectorials enhancing practical leadership skills, including team, negotiating and influencing skills. Students will also be expected and directed to read from a range of sources including academic journals.
Scheduled contact hours: 30 contact hours in total, to be split into 10x1-hour asynchronous activities and 10x2-hour lectorials. The remaining 170 learning hours will be spent in independent study and in the preparation of assessment.
Tasks which help you learn and prepare you for summative tasks (formative):
Tasks which count towards your unit mark (summative):
Individual Assignment (100% of the overall unit mark):
Students will write a 3,000-word individual essay and submit it at the end of the term. This assessment will evaluate the students’ understanding of core concepts in behavioural decision-making by testing their ability to formulate business problems using appropriate analytical techniques to identify the optimal decision-making strategy. This assessment is related to ILOs 1-4.
When assessment does not go to plan
When a student fails the unit and is eligible to resubmit, then the re-assessment weighting on the unit is the same as the original assessment. This means if the student does not pass the unit overall, then they will be reassessed with a single 3,000-word individual assignment weighted at 100%, covering all intended learning outcomes (ILOs 1-4) for the unit. The resit will consist of an individual essay covering the various topics of the unit.
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. MGRCM0035).
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 assessment methods listed in this unit specification are designed to enable students to demonstrate the named learning outcomes (LOs). Where a disability prevents a student from undertaking a specific method of assessment, schools will make reasonable adjustments to support a student to demonstrate the LO by an alternative method or with additional resources.
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.
