PRM7007 Project Analytics Individual Case study Presentation 2026 | Arden University

PRM7007 Individual Case study Presentation

Task summary:

As part of the formal assessment for the programme you are required to submit a Project Analytics assignment. Please refer to your Student Handbook for full details of the programme assessment scheme and general information on preparing and submitting assignments.

Assignment instructions:

The purpose of this assessment is to enable students to critically analyse and apply project analytics concepts, techniques, and tools in a real-world context. The focus will be on demonstrating how advanced analytics can enhance decision-making, performance, and strategic alignment in projects, while also highlighting the role of digital literacy in leveraging data-driven solutions. You are required to individually research and Present a case study on the application of project analytics in a real-world scenario. The case study must involve a specific project within an organization where decision- making, data collection, and analytics played a critical role.

Detailed Guidance

• Select an Organization and Project
  • Choose an organization that aligns well with project analytics topics. This can be an organization you are familiar with or one with publicly available data.
  • Select a project where data analytics significantly influenced project decision-making, execution, or outcomes.
  • Obtain tutor approval for your choice, providing a brief justification highlighting its relevance.
• Research and Analyse
  • Collect sufficient background information on the organization and project.
  • Analyse how analytics techniques were applied to decision-making processes and project outcomes.
  • Evaluate the strategic alignment of these analytics efforts with organizational goals.
• Present Your Findings
  • Your Presentation should:
    • introduce the organization and project.
    • Demonstrate the application of advanced analytics techniques (e.g., descriptive, predictive, prescriptive, machine learning, or AI).
    • Highlight methods of data collection and validation and how they ensured data integrity.
    • Critically evaluate how project analytics contributed to strategic decision-making and sustainable competitive advantage.
    • Showcase digital tools or technologies used in the project and reflect on opportunities for enhancing digital capabilities.
• Conclusion and Recommendations
  • Provide insights into what was achieved through the use of analytics.
  • Suggest improvements or novel approaches for future projects.