Data Analytics for Leaders
| Module title | Data Analytics for Leaders |
|---|---|
| Module code | PYCM046 |
| Academic year | 2019/0 |
| Credits | 30 |
| Module staff | Dr Ian Frampton (Convenor) |
| Duration: Term | 1 | 2 | 3 |
|---|---|---|---|
| Duration: Weeks | 10 | 10 |
| Number students taking module (anticipated) | 20 |
|---|
Module description
Traditional business analytics has often struggled to capture the complexity and richness of interpersonal and organisational processes in applied leadership. This module introduces contemporary approaches to applied research and implementation methods, drawing on the evidence-base. Evaluation of a leadership context will afford you a unique opportunity to explore, reflect on and integrate your professional identity and practice.
You will explore how processes of innovation, disruptive technologies and new ways of working impact on infrastructure, processes, people and culture, and sustainability. This module will give you an insight into ways of modelling change and dealing with ambiguity in the context of systems-thinking, knowledge and data management, and oversight of strategic programmes/projects.
Module aims - intentions of the module
The module aims to help you make effective use of horizon-scanning and conceptualisation to deliver long term strategies focusing on growth and sustainable outcomes. You will learn how agenda-setting and support from key stakeholders enable you to critically analyse and integrate complex information, and to communicate a compelling case for change.
Being accountable and making decisions based on relevant information (e.g. KPIs) can challenge the underlying assumptions on which strategies are based and enable you to make decisions based on rich data to ensure effective use of resources.
The module introduces you to current research undertaken by module leads, and module content is updated every year to explore topical research areas, such as organisational processes in applied leadership. You will learn about the tools required to study such issues, and explore how research can inform leadership practice. The module supports you in developing your skills as an independent evidence-based leader by requiring you to present an infographic and conduct your own small-scale research project.
Intended Learning Outcomes (ILOs)
ILO: Module-specific skills
On successfully completing the module you will be able to...
- 1. Integrate and communicate complex data using a wide range of visualisation strategies
- 2. Analyse data using a variety of statistical models to support leadership decision-making
- 3. Use advanced simulation methods to model the impact of innovation and new ways of working on infrastructure, processes, people and culture
- 4. Demonstrate how to apply advanced data analytics to support decision-making, performance improvement and change management, and how to evaluate financial and non-financial information
ILO: Discipline-specific skills
On successfully completing the module you will be able to...
- 5. Operate at a senior level to innovate in complex and uncertain environments
- 6. Critically analyse and integrate complex information, and communicate to diverse audiences
ILO: Personal and key skills
On successfully completing the module you will be able to...
- 7. Demonstrate advanced skills as an imaginative and critical thinker and problem solver
- 8. Exemplify a range of approaches to leading and effecting change, being empowered to make a responsible and sustainable difference as a future leader
Syllabus plan
The module will explore the following topics:
- What’s in a number? Fundamentals of number theory and data analysis.
- A picture tells a thousand words: visualising data.
- Fake it ‘til you make it: using simulation to model the impact of systems change.
- Power mapping: discovering the hidden alliances that promote or inhibit organisational development.
- Big is beautiful, small is sublime: making sense of large scale datasets and single cases.
Learning activities and teaching methods (given in hours of study time)
| Scheduled Learning and Teaching Activities | Guided independent study | Placement / study abroad |
|---|---|---|
| 30 | 270 | 0 |
Details of learning activities and teaching methods
| Category | Hours of study time | Description |
|---|---|---|
| Scheduled Learning and Teaching | 20 | Data analytics workshops (10 x 2 hours) |
| Scheduled Learning and Teaching | 10 | Poster and project presentations (10 x 1 hour) |
| Guided Independent Study | 20 | Online data simulation task |
| Guided Independent Study | 250 | Reading and preparation for assignments |
Formative assessment
| Form of assessment | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|
| Online data simulation task | 20 hours maximum | 2-4, 6-8 | Written |
Summative assessment (% of credit)
| Coursework | Written exams | Practical exams |
|---|---|---|
| 100 | 0 | 0 |
Details of summative assessment
| Form of assessment | % of credit | Size of the assessment (eg length / duration) | ILOs assessed | Feedback method |
|---|---|---|---|---|
| Infographic poster presentation | 30 | 10 minutes | 1-2, 4, 6-7 | Peer evaluation |
| Small scale project report | 70 | 3000 words | 1-2, 4-8 | Written |
Details of re-assessment (where required by referral or deferral)
| Original form of assessment | Form of re-assessment | ILOs re-assessed | Timescale for re-assessment |
|---|---|---|---|
| Infographic poster presentation | Infographic poster presentation | 1-2, 4, 6-7 | Eight weeks after initial feedback |
| Small scale project report | Small scale project report | 1-2, 4-8 | 12 weeks after initial feedback |
Re-assessment notes
Two assessments are required for this module. In all cases re-assessment will be the same as the original assessment. Where you have been referred/deferred for any form of assessment detailed above you will have the opportunity to resubmit within the timescale defined above from the date that feedback was provided.
If you pass re-assessments taken as a result of deferral, your re-assessment will be treated as it would be if it were your first attempt at the assessment and the overall module mark will not be capped.
If you pass re-assessments taken as a result of referral (i.e. following initial failure in the assessment), the overall module mark will be capped at 50%.
Indicative learning resources - Basic reading
- Bryman, A. (2012). Social Research Methods (4th ed). Oxford: Oxford University Press.
- Field, A. (2013).?Discovering statistics using IBM SPSS statistics. Sage.
- Spencer, S. (2010).?Visual research methods in the social sciences: Awakening visions. Routledge.
- Tay, L., Ng, V., Malik, A., Zhang, J., Chae, J., Ebert, D. S., & Kern, M. (2017). Big Data Visualizations in Organizational Science.?Organizational Research Methods, 1-29.
- Wenzel, R., & Van Quaquebeke, N. (2017). The Double-Edged Sword of Big Data in Organizational and Management Research: A Review of Opportunities and Risks.?Organizational Research Methods, 1-44.
Indicative learning resources - Web based and electronic resources
- ELE – All resources will be made available on ELE. This includes additional material covered in the tutorials, the required readings, information about assessment and additional material (e.g., videos).
| Credit value | 30 |
|---|---|
| Module ECTS | 15 |
| Module pre-requisites | None |
| Module co-requisites | None |
| NQF level (module) | 7 |
| Available as distance learning? | No |
| Origin date | 09/12/2016 |
| Last revision date | 07/09/2017 |