Operations and Supply Chain Management
1,987 words
Supply Chain Analytics and Quantitative Data Analysis for Organisational Decision-Making
This postgraduate individual report focuses on the application of quantitative data analysis to Operations, Logistics and Supply Chain Management decision-making. Students are required to select an organisation from the private, public or third sector and investigate a relevant operational or supply-chain issue using quantitative data. The purpose is to demonstrate how data can be collected, prepared, analysed and interpreted to generate evidence-based insights that may support managerial decision-making. The selected dataset must relate to the organisation's operations or supply chain and may include variables such as revenues, product orders, sales, transportation costs, procurement expenditure, inventory levels or other appropriate quantitative measures. The dataset must contain at least 60 observations, and the analysis must involve at least two variables. Data may be obtained directly from organisations or from recognised secondary-data platforms and databases. The assessment consists of two equally weighted components. Part A – Motivation and Justification for the Analysis requires students to formulate relevant analytical questions and explain their practical importance by linking them to Operations and Supply Chain Management theory and business practice. Appropriate academic, industry and practitioner evidence should be used to justify the selected issue. Research questions may also be translated into testable hypotheses where appropriate. Part B – Execution of the Analysis requires students to answer the identified questions through appropriate statistical techniques. Potential methods include tables, charts, summary statistics, t-tests and regression analysis. Data may first need to be cleaned, transformed and structured before analysis. The results must then be interpreted clearly for a managerial audience such as the organisation's board, owner or CEO. The statistical analysis is expected to be conducted using Stata, with all data-cleaning, manipulation and analytical commands recorded in a reproducible do-file. The report must also demonstrate explicit links between theory and practice and contain a suitable mixture of academic and professional evidence, including at least five academic journal articles. Harvard referencing is required throughout. The resulting work demonstrates practical competence in business analytics, statistical interpretation, supply-chain decision support, reproducible analysis and evidence-based managerial communication. Overview word count: approximately 370 words.
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Cyber Security for Business and Cloud Management
This activity aims to assess your comprehension of the diverse concepts discussed in this module. You must use the frameworks and concepts covered in this module's delivery to respond to all the tasks below. Scenario ShieldSafe Analytics Ltd. is a fast-growing health analytics company specialising in AI-driven patient diagnostics and telehealth platforms. Operating across multiple countries, the company processes high volumes of real-time patient data, including biometric and genomic records. Due to the increased reliance on remote healthcare and IoT-enabled medical devices, their infrastructure has expanded into hybrid cloud environments. Recently, ShieldSafe experienced a suspected data exfiltration incident involving anomalous traffic from one of its diagnostic platforms integrated with third-party cloud APIs. As a result, executive leadership has raised concerns about the company’s vulnerability to adversarial information operations, particularly in relation to data manipulation, misinformation, and insider threats. As a Junior Cybersecurity Strategist, you’ve been recruited to support the lead cyber intelligence consultant in reviewing vulnerabilities within their information environment, exploring offensive and defensive Information Operations (IO) concepts, and crafting robust cyber defence mechanisms. The leadership also wants to migrate a legacy electronic health record (EHR) system used across its African operations to a more scalable and secure cloud infrastructure. However, concerns exist regarding cross-border data protection laws, insider threats, and the strategic use of information in potential cyber warfare scenarios.
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L7 Cyber Security for Business and Cloud Management
This activity aims to assess your comprehension of the diverse concepts discussed in this module. You must use the frameworks and concepts covered in this module's delivery to respond to all the tasks below. Scenario ShieldSafe Analytics Ltd. is a fast-growing health analytics company specialising in AI-driven patient diagnostics and telehealth platforms. Operating across multiple countries, the company processes high volumes of real-time patient data, including biometric and genomic records. Due to the increased reliance on remote healthcare and IoT-enabled medical devices, their infrastructure has expanded into hybrid cloud environments. Recently, ShieldSafe experienced a suspected data exfiltration incident involving anomalous traffic from one of its diagnostic platforms integrated with third-party cloud APIs. As a result, executive leadership has raised concerns about the company’s vulnerability to adversarial information operations, particularly in relation to data manipulation, misinformation, and insider threats. As a Junior Cybersecurity Strategist, you’ve been recruited to support the lead cyber intelligence consultant in reviewing vulnerabilities within their information environment, exploring offensive and defensive Information Operations (IO) concepts, and crafting robust cyber defence mechanisms. The leadership also wants to migrate a legacy electronic health record (EHR) system used across its African operations to a more scalable and secure cloud infrastructure. However, concerns exist regarding cross-border data protection laws, insider threats, and the strategic use of information in potential cyber warfare scenarios.
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