MGMT6016 Strategic Supply Chain Management Individual Assessment 2 Brief Sem 1, 2025

Assessment Type	Individual Assessment 2

MGMT6016 Assignment Overview

This is an individual assessment covering the following learning outcomes:

• Analyse and evaluate business environments to prompt strategic supply chain decisions to assist an organization’s performance.
• Assess and communicate supply chain business strategies based on conceptual frameworks and case studies.

MGMT6016 Assessment Brief

The assignment is based on the historical Fresh Connection Company dataset.

Your tasks are:

• Identify data quality issues and clean the data (10 marks): Highlight and resolve issues like missing values, inconsistencies, and formatting errors.
• Explore the data (30 marks): Use descriptive statistics, visualizations, and relationships between variables to understand data distribution.
• Identify patterns, outliers, and significant trends.
• Documentation: Submit a Word document through Turnitin that includes screenshots and details of your steps using appropriate tools.

MGMT6016 Marking Criteria

Criteria	80-100% (High Distinction)	70-79% (Distinction)	50-69% (Pass/Credit)	0-49% (Fail)
Data Quality – Identification of Issues (5 marks)	Accurately identifies all major issues with clear explanations.	Identifies most major issues with mostly clear explanations.	Identifies some issues with unclear or incomplete explanations.	Fails to identify significant issues or provides inaccurate explanations.
Data Quality – Cleaning Techniques (5 marks)	Applies appropriate techniques with clear documentation and rationale.	Applies most techniques with partial documentation or rationale.	Applies some basic techniques but lacks effectiveness or clarity.	Fails to apply techniques or provides incorrect solutions.
Data Exploration – Descriptive Statistics (7.5 marks)	Calculates and interprets relevant statistics with clear explanations.	Calculates statistics but may not fully interpret them.	Calculates limited statistics with unclear interpretations.	Fails to calculate or interpret statistics.
Data Exploration – Visualizations (7.5 marks)	Creates informative and well-designed visualizations with clear explanations.	Creates some visualizations but may lack clarity or relevance.	Creates limited or poorly designed visualizations.	Fails to create meaningful visualizations.
Data Exploration – Patterns and Outliers (7.5 marks)	Identifies and interprets patterns with explanations of their impact.	Identifies some patterns but lacks full explanations.	Identifies limited patterns with unclear explanations.	Fails to identify significant patterns or outliers.
Data Exploration – Relationships between Variables (7.5 marks)	Explores relationships using appropriate techniques and interprets results.	Explores relationships but lacks clear explanations or appropriate techniques.	Explores limited relationships with unclear findings.	Fails to explore relationships or uses inappropriate techniques.