Assignment: Investigating Analytical Levels for Optimal Decision-Making
Weighting: 30%
Due: Week 4, Sunday
Assignment Objectives
- Demonstrate an understanding of descriptive, diagnostic, predictive, and prescriptive analytics.
- Develop critical thinking skills in evaluating the decision-making process for selecting the most appropriate analytical level.
- Apply analytical levels within real-world case studies to maximise analytical performance and outcomes.
Assignment Instructions
Part A - Research and Define Analytical Levels (20%)
Define and describe:
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
Requirements:
- Provide at least 2, real-world examples (not from lectures or textbooks) of how each level is used in business decision-making.
- Give relationship between all the analytics.
- Examples must be drawn from recent news, industry reports, or publicly available datasets.
Part B - Decision-Making Framework (20%)
- Create a decision-making framework or flowchart that outlines the key factors to consider when selecting the most appropriate analytical level.
- Justify the inclusion of each factor and discuss its importance.
- Apply your framework to one unique business scenario of your choice.
Part C - Case Study Selection (10%)
- Identify two (2) relevant case studies that demonstrate the application of different analytical levels.
Case studies must:
- Be published within the last two years
- Comes from academic sources
Additional Requirements:
- Provide a summary of each case study and the business problem addressed.
Part D - Case Study Analysis (35%)
For each case study:
- Identify the analytical level(s) applied.
- Explain how and why the chosen level(s) fit the scenario.
- Analyse the effectiveness of the applied analytical level(s) in driving decision-making.
- Propose alternative levels or hybrid approaches and justify your proposals.
- Reflect on: "If this problem occurred in a different context (e.g., smaller business, different industry, or resource constraints), which analytical level(s) would you use and why?"
Part E - Conclusion and Recommendations (15%)
- Summarise your findings on the importance of matching analytical levels to specific business problems.
- Develop general recommendations for how organisations can optimise analytical performance by carefully selecting analytical approaches.
- Provide a short personal reflection: "How will the knowledge of analytical levels influence the way you approach problem-solving in your future studies or career?"
Report Requirements
Word Count: 1500 words (+/- 10%)
Diagrams: Include flowcharts, frameworks, or visualisations.
References: APA style, minimum of 8 academic or industry references