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.

PRM7007 Project Analytics

PRM7007 Individual Case study Presentation

PRM7007 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.

PRM7007 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.

PRM7007 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.