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Business Intelligence / Data Analytics / Project Management
Business Intelligence and Data Analytics for Project Progress Evaluation
This assessment for the Data Analytics and Project Management for Business Intelligence module requires students to critically evaluate the progress of a live-style project through the application of business intelligence and data analytics techniques. Working as a group of Project Analysts, students select either a Convocation project or Concert project associated with Northumbria University London and prepare a professional presentation assessing its progress, stakeholders, deliverables and performance. The assessment begins with development of a clear project problem or opportunity statement, followed by identification and analysis of the key stakeholders and deliverables associated with the selected project. Students then use Business Intelligence and Data Analytics techniques to examine project progress and communicate findings through dashboards. The assessment permits the use of Microsoft Excel or other suitable software for dashboard development. A central part of the task is the creation and critical evaluation of a project dashboard. Students are expected to use realistic assumed or projected data where necessary, as the assessment is designed to test the ability to design, interpret and critically evaluate dashboards rather than the accuracy of real project data. The data should therefore be internally consistent, relevant to the selected project and capable of generating meaningful management insights. Students must also critically justify their chosen BI and analytics tools, explaining how the dashboard supports project monitoring and informed decision-making. The assessment concludes with recommendations for the successful implementation and use of a Business Intelligence or Data Analytics solution within the selected project. Academic references and relevant examples should be used to support the analysis. The marking criteria place the greatest emphasis on application of BI tools and techniques (30%), followed by stakeholders and deliverables (20%) and justification of BI tools (20%). Project and opportunity analysis, conclusion and recommendations, and presentation and referencing each contribute a further 10%. Higher-performing work is expected to demonstrate critical evaluation, meaningful dashboard insights, strong theoretical or industry justification and professionally presented recommendations. If the file you want to upload is the resubmission report instead Use the same University, Subject and Module Name, but change these fields: Title: Business Intelligence and Project Analytics: Individual Critical Analysis of Project Performance Assignment type: MS Technical and Scientific Writing Word count: 1,500–2,000 words Key topics: Business Intelligence, Data Analytics, Project Management, Stakeholder Analysis, BI Tools, Dashboard Evaluation, Project Opportunity Analysis, Project Deliverables, Critical Analysis, Project Recommendations The resubmission is an individual written report in which the student selects only one area from the original project—Project & Opportunity Analysis, Stakeholders & Deliverables, Application of BI Tools & Techniques, Justification of BI Tools, or Conclusion & Recommendations—and develops it in depth. It should use the same Convocation or Concert project context while demonstrating independent critical analysis, reflection and application of theory.
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Business Management / Business Consultancy / Supply Chain Management
5,000 words
Digital Transformation for Sustainable Supply Chain Transparency at Unilever: Blockchain, IoT and AI
This MSc Business Consultancy Project requires students to undertake an evidence-based consultancy investigation addressing a strategically significant business problem within a selected organisation. The assessment is designed to replicate professional consultancy practice by requiring students to define a focused organisational challenge, critically analyse secondary evidence, apply relevant management frameworks, evaluate stakeholder implications and develop practical recommendations that create value for the client organisation. The final submission is a 5,000-word consultancy report, including a 500-word employability reflection. The reference project examines Unilever Plc and focuses on the challenge of improving transparency and traceability across its complex global supply chain. Particular attention is given to the potential application of Blockchain, Internet of Things (IoT) and Artificial Intelligence (AI) to support real-time traceability, predictive analytics, ethical sourcing, operational efficiency and sustainability performance. The project considers how digital transformation could support Unilever's sustainability objectives while responding to growing regulatory, environmental and stakeholder pressures. The consultancy report requires a structured analysis consisting of an executive summary, introduction, company/client overview, clearly defined business problem and consultancy focus, and detailed stakeholder analysis. Students then undertake an extensive data analysis and framework application section using two or three relevant theoretical models alongside credible secondary evidence, industry reports, company data, tables, charts or Excel outputs. Findings should be interpreted critically and linked back to appropriate strategic or management frameworks while incorporating ethical and sustainability considerations. The project concludes with three prioritised, actionable and evidence-based recommendations, including consideration of implementation risks, barriers and anticipated benefits. Students must also critically reflect on the employability skills developed through the consultancy project, including research, analysis, problem-solving, project management, communication, professional behaviour, ethical awareness and future career development. All academic and professional evidence must be cited using the Harvard Referencing System, with emphasis on credible and current sources.
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Business Intelligence / Data Analytics / Project Management
Business Intelligence and Data Analytics Dashboard for Project Progress Evaluation
This group assessment requires students to act as Project Analysts and critically evaluate the progress of a university project using business intelligence, data analytics and project management techniques. The scenario is based on Northumbria University London planning two major events: a Convocation and an associated Concert. Students must select one of these projects and assess its progress through a professionally structured presentation. The assessment requires students to begin by defining the main problem or opportunity associated with the selected project. They must then identify and analyse the project's key stakeholders and deliverables. A major component of the work involves evaluating project progress using suitable business intelligence and data analytics techniques and developing an appropriate dashboard, which may be created using Microsoft Excel or other suitable software. Students must not only present the dashboard but also critically analyse and justify its design, selected metrics, analytical methods and usefulness for project monitoring and decision-making. Because the projects are treated as already being in progress, students are permitted to create assumed or projected data to demonstrate their dashboards. The assessment does not primarily evaluate the accuracy of real project data; instead, it assesses students' ability to design, present and critically evaluate meaningful dashboards. Any assumed data should therefore remain realistic, internally consistent and relevant to the selected project. The presentation should conclude with evidence-based recommendations for the successful implementation and use of the proposed business intelligence or data analytics solution. Academic references and relevant examples must support the presentation, and a single reference list must be included. Assessment weighting places particular emphasis on application of BI tools and techniques (30%), followed by stakeholders and deliverables (20%) and justification of BI tools (20%). Project and opportunity analysis, conclusions and recommendations, and presentation/referencing are each worth 10%. The final assessment is a 15-minute group presentation followed by a 5-minute question-and-answer session. Every group member must contribute to the presentation. The PowerPoint submission is made electronically through Turnitin. Do not select Harvard automatically for this one. Unlike the previous Roehampton brief, this Northumbria brief requires academic references and a reference list but does not state a specific referencing style in the uploaded document.
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Computing / Artificial Intelligence / Digital Transformation / Management Consultancy
7,000 words
AI Readiness and Programme Adoption Strategy for the NewFutures: AI Programme at Northumbria University London
This postgraduate consultancy project focuses on developing an AI readiness, skills-development and programme-adoption strategy for students and recent alumni at Northumbria University London. The project supports the university’s participation in NewFutures: AI, a funded AI skills and career-readiness programme offering a four-week online course covering responsible AI foundations and specialist pathways in Marketing and Communications, Finance and Accounting, Business Operations and Logistics, Administration, and ICT and Technical Support. The central consultancy challenge is to understand the AI literacy, confidence, readiness and training needs of Northumbria University London students and alumni and translate that evidence into a practical implementation and outreach strategy. The client aims to reach approximately 12,000 students and recent alumni and support a target of 6,000 LMS registrations during the 2026–2027 programme period. The project requires primary and secondary research into AI readiness, demand for different AI-skilling pathways and barriers to participation such as awareness, time, perceived value and accessibility. The consultancy team is also expected to benchmark comparable initiatives and use research evidence to develop recommendations appropriate to different academic disciplines and student and alumni groups. The implementation component focuses on designing an evidence-based outreach and adoption campaign, including appropriate communication channels, messaging, timing, incentives, faculty engagement and stakeholder participation. Recommended channels may include email campaigns, newsletters, social media, student services, events, learning platforms and alumni communications. The project also requires an implementation timeline and indicative budget for the 2026–2027 programme period. The wider assessment develops professional consultancy capability through business and requirements analysis, research methodology, ethical research practice, practical implementation, testing and strategic recommendations. The project charter additionally establishes milestones for research design, data collection, analysis, report development, review and presentation, together with defined responsibilities for project management, data analysis, AI expertise and stakeholder communication. The individual component complements the consultancy work through critical reflection on personal contribution, skills development, decision-making, problem-solving, communication, collaboration, technical capability, innovation and continuous professional development.
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