DHL, a global leader in logistics and supply chain solutions, operates one of the most complex and dynamic supply chains in the world. The company manages vast networks of transportation, warehousing, and distribution

DHL, a global leader in logistics and supply chain solutions, operates one of the most complex and dynamic supply chains in the world. The company manages vast networks of transportation, warehousing, and distribution services while catering to diverse industries including healthcare, technology, e-commerce, and manufacturing. DHL has been progressively integrating advanced analytics and digital technologies to enhance its supply chain efficiency, sustainability, and resilience.

In this assignment, you are required to analyze how DHL utilizes analytics to optimize its global supply chain operations. Your analysis should focus on the integration of key supply chain analytics techniques covered in this course and demonstrate how DHL manages supply chain challenges using data-driven strategies.

Your assignment should cover at least 3 of the below key areas.

Key Areas to Address:

Descriptive Analytics for Supply Chain Metrics:
Explain how DHL uses descriptive analytics to monitor supply chain performance. Identify key performance indicators (KPIs) and metrics such as delivery times, warehouse efficiency, and transportation costs. Provide examples of dashboards or reporting tools DHL might use.
Probability and Decision Analysis in Supply Chain Management:
Evaluate how DHL applies probability and decision analysis to manage uncertainties in logistics operations, such as predicting delivery times and managing risks related to supply chain disruptions.
Big Data Driven Supply Chain Management:
Analyze how DHL harnesses big data analytics to gain insights into market trends, customer demands, and operational efficiencies. Explore how data from IoT devices, logistics software, and customer interactions feed into DHLs analytics platforms.
Forecasting Demand and Matching Supply:
Describe the forecasting techniques DHL employs to match demand with supply. Highlight the role of predictive analytics and machine learning in demand forecasting and inventory management.
Supply Chain Network Design and Optimization:
Assess DHLs approach to network design and optimization. Discuss how the company uses optimization techniques to determine the best locations for warehouses, distribution centers, and transport routes to minimize costs and maximize service levels.

Assignment Requirements:

Case Study Approach:Select a specific DHL project or initiative where analytics played a critical role. Examples could include DHLs use of robotics in warehouses, predictive analytics for last-mile delivery, or data-driven strategies for peak season logistics.
Practical Examples and Analytics Models:Include practical examples of analytics models (e.g., regression analysis, simulation models) used by DHL to optimize supply chain performance.
Visual Aids:Utilize visual aids such as charts, graphs, and process flow diagrams to illustrate analytical approaches and outcomes.
Recommendations:Based on your analysis, propose recommendations for DHL to further enhance its supply chain efficiency using advanced analytics.
References:Support your work with academic articles, industry reports, and case studies.

Referencing and Citation:

As part of your academic responsibilities, all submitted work must adhere to the APA 7th edition guidelines for proper referencing. Please refer tothis resourceLinks to an external site.to verify citation and formatting rules before submitting your assignments.

Additionally, make sure to utilize theTurnitin Draft.Coach to review your papersbeforesubmission (not after). Instructions for this can be found on the Program ImmersionCourse page.

AI Use:

You may use AI tools for this assignment as per the myHultAI policy. All AI usage must be acknowledged as per the policys citation framework. If unsure about a tool, consult the professor. Unacknowledged AI work will be treated as an academic integrity violation and referred to the Academic Integrity Committee.

Finally, recommend how Amazon should prioritize these strategies to maximize their sustainable and resilient impact. Develop a Strategic Roadmap that visualizes the sequencing and timing of priorities, ensuring alignment with long-term corporate goals like achieving net-zero emissions by 2040.

Word count: 2000 words (+- 10%) excluding appendices and reference list.

Rubric

Individual Assignment

Individual Assignment

Criteria

Ratings

Pts

This criterion is linked to a Learning OutcomeUnderstanding and Analysis of Sustainable Supply Chains

40to >35.5pts

Demonstrates an in-depth understanding of supply chain analytics within DHLs operational context, including logistics, sustainability, and resilience. Thoroughly evaluates DHLs use of advanced analytics, supported by detailed examples and critical analysis. Discusses a wide range of strategies for optimizing supply chains using analytics and identifies comprehensive challenges, providing insightful solutions and reflections.

35.5to >31.5pts

Shows a good understanding of supply chain analytics with minor gaps. Provides a strong evaluation of DHLs analytical practices with good examples and analysis. Discusses several strategies and challenges with some critical insights but lacks some depth.

31.5to >27.5pts

Displays a basic understanding of supply chain analytics but lacks depth. Offers a basic evaluation of DHLs practices with limited examples. Identifies some strategies and challenges but lacks comprehensive coverage and critical analysis.

27.5to >23.5pts

Shows limited understanding of supply chain analytics with significant gaps. Provides minimal evaluation of DHLs practices with superficial analysis. Discusses few strategies and challenges with little depth.

23.5to >0pts

Lacks understanding of supply chain analytics. Evaluation of DHLs practices is minimal or missing. Discusses few or no strategies and challenges with little to no analysis.

40pts

This criterion is linked to a Learning OutcomeStructure and Coherence

20to >17.5pts

The report is well-organized with a clear, logical flow of ideas. Each section is clearly defined and contributes to the overall argument. Transitions between sections are smooth, and the introduction and conclusion are strong and effectively frame the discussion.

17.5to >15.5pts

The report is generally well-organized with a clear structure. Most sections are well-defined and contribute to the overall argument, but some transitions may be awkward. The introduction and conclusion are solid but could be stronger.

15.5to >13.5pts

The report has a basic structure with some organization. Some sections may be unclear or not contribute effectively to the argument. Transitions may be weak, and the introduction and conclusion are present but lack impact.

13.5to >11.5pts

The report lacks clear organization and structure. Sections may be unclear or poorly defined, with weak transitions. The introduction and conclusion are minimal or ineffective.

11.5to >0pts

The report is disorganized with no clear structure. Sections are unclear or missing, and transitions are poor. The introduction and conclusion are missing or ineffective.

20pts

This criterion is linked to a Learning OutcomeApplication of Course Concepts

30to >26.5pts

Accurately and comprehensively applies relevant supply chain analytics and course concepts, including descriptive analytics, probability analysis, network design, and forecasting. Demonstrates deep understanding by integrating multiple ideas effectively with the effective use of visuals to support.

26.5to >23.5pts

Correctly applies relevant analytics and course concepts. Shows a clear understanding, though integration of ideas may be less comprehensive and less effective visual support.

23.5to >20.5pts

Applies some course analytics and concepts, but with minor errors or omissions. Shows basic understanding but lacks depth and visual execution.

20.5to >17.5pts

Misapplies or inadequately uses course analytics and concepts. Understanding is superficial or incomplete.

17.5to >0pts

Fails to apply supply chain analytics and course concepts, showing little to no understanding.

30pts

This criterion is linked to a Learning OutcomeResearch and referencing

10to >8.5pts

The essay is well-researched with a wide range of high-quality sources. References are used effectively to support arguments, and all sources are correctly cited in the appropriate format.

8.5to >7.5pts

The essay is well-researched with several good-quality sources. References are used effectively for the most part, and sources are correctly cited with minor errors

7.5to >6.5pts

The report includes some research but may lack depth. References are present but may not always effectively support the arguments. Citation format may contain errors.

6.5to >5.5pts

The essay lacks clear organization and structure. Sections may be unclear or poorly defined, with weak transitions. The introduction and conclusion are minimal or ineffective.

5.5to >0pts

The essay lacks research with no or very few sources. References are absent or ineffective in supporting arguments. Citations are incorrect or missing