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Harvard Case - Outsourcing, Near-sourcing, and Supply Chain Flexibility in the Apparel Industry (A)

"Outsourcing, Near-sourcing, and Supply Chain Flexibility in the Apparel Industry (A)" Harvard business case study is written by Anton Ovchinnikov, Alexander Pyshkov. It deals with the challenges in the field of Accounting. The case study is 5 page(s) long and it was first published on : Oct 14, 2016

At Fern Fort University, we recommend that [Company Name] implement a multi-pronged approach to optimize their supply chain and achieve sustainable growth. This approach involves strategic near-sourcing for key product lines, leveraging digital technologies for enhanced transparency and control, and building a robust risk management framework to mitigate potential disruptions.

2. Background

[Company Name] is a leading apparel manufacturer facing increasing pressure from rising labor costs, fluctuating exchange rates, and evolving consumer demands. The company currently operates a complex global supply chain with manufacturing facilities in Asia and sourcing from various countries. This case study explores the challenges [Company Name] faces in balancing cost efficiency with flexibility and responsiveness to market changes.

The main protagonists are [Company Name]'s CEO, who is concerned about the company's long-term competitiveness, and [Company Name]'s Supply Chain Manager, who is tasked with finding solutions to improve efficiency and agility.

3. Analysis of the Case Study

This case study highlights the need for [Company Name] to re-evaluate its supply chain strategy in light of the changing global landscape. We can analyze the situation using the following frameworks:

a) Porter's Five Forces:

  • Threat of new entrants: The apparel industry is characterized by low barriers to entry, leading to potential competition from new players.
  • Bargaining power of buyers: Consumers have a wide range of choices and are increasingly demanding transparency and ethical sourcing.
  • Bargaining power of suppliers: The availability of raw materials and skilled labor can impact supplier bargaining power.
  • Threat of substitutes: Fast fashion and online retailers offer alternative options to traditional apparel brands.
  • Competitive rivalry: Intense competition exists among established players, further driving the need for differentiation and cost optimization.

b) Value Chain Analysis:

  • [Company Name]'s value chain involves sourcing, manufacturing, distribution, and marketing. Each stage presents opportunities for cost reduction and efficiency improvements.
  • Activity-Based Costing (ABC) can be used to identify cost drivers and allocate costs accurately, enabling better decision-making regarding outsourcing and near-sourcing.

c) Risk Management Framework:

  • [Company Name] needs to develop a robust risk management framework to identify, assess, and mitigate potential risks associated with its supply chain.
  • This framework should consider factors such as political instability, natural disasters, currency fluctuations, and ethical sourcing concerns.

4. Recommendations

[Company Name] should implement the following recommendations:

1. Strategic Near-Sourcing:

  • Identify key product lines where near-sourcing offers significant advantages, such as faster lead times, improved quality control, and better responsiveness to market trends.
  • Establish partnerships with reputable manufacturers in regions closer to its target markets, such as Mexico, Central America, or North Africa.
  • Leverage technology to streamline communication, collaboration, and data sharing with near-shore partners.

2. Digital Transformation:

  • Implement a robust Enterprise Resource Planning (ERP) system to enhance visibility and control over the entire supply chain.
  • Adopt cloud-based platforms for inventory management, order fulfillment, and logistics tracking.
  • Utilize data analytics to identify trends, optimize inventory levels, and improve forecasting accuracy.

3. Risk Management Framework:

  • Develop a comprehensive risk assessment that identifies potential disruptions and assigns risk levels.
  • Implement mitigation strategies for each identified risk, including alternative sourcing options, contingency plans, and insurance coverage.
  • Establish clear communication channels for timely information sharing and decision-making in case of emergencies.

4. Continuous Improvement:

  • Implement a culture of continuous improvement by regularly reviewing supply chain performance and identifying areas for optimization.
  • Encourage employee engagement by providing training and incentives for process improvement initiatives.
  • Utilize benchmarking to compare [Company Name]'s performance against industry best practices.

5. Basis of Recommendations

These recommendations consider the following:

  1. Core Competencies and Consistency with Mission: Near-sourcing aligns with [Company Name's] mission by enhancing its ability to respond quickly to changing market demands and improve product quality.
  2. External Customers and Internal Clients: The recommendations aim to improve customer satisfaction by reducing lead times, enhancing product quality, and increasing transparency.
  3. Competitors: By embracing digital technologies and optimizing its supply chain, [Company Name] can gain a competitive advantage in terms of efficiency, responsiveness, and sustainability.
  4. Attractiveness ' Quantitative Measures: The recommendations are expected to lead to cost savings through optimized sourcing and reduced transportation costs, while also improving profitability through increased sales and reduced inventory holding costs.

6. Conclusion

By implementing these recommendations, [Company Name] can achieve a more agile and efficient supply chain that enables it to navigate the complexities of the global apparel industry. Near-sourcing, digital transformation, and a robust risk management framework will position [Company Name] for sustainable growth and long-term success.

7. Discussion

Alternative options not selected include:

  • Full outsourcing: While this could offer cost savings in the short term, it could also lead to a loss of control over manufacturing processes and quality.
  • Maintaining the current strategy: This would likely lead to continued challenges in terms of cost competitiveness and responsiveness to market changes.

Key risks and assumptions:

  • Risk of disruption: Near-sourcing could be affected by political instability or natural disasters in the chosen region.
  • Assumption of technology adoption: Successful implementation of digital technologies requires significant investment and ongoing training.

8. Next Steps

[Company Name] should:

  • Form a cross-functional team to lead the implementation of the recommendations.
  • Develop a detailed implementation plan with clear timelines and milestones.
  • Allocate resources for technology upgrades, training, and partnership development.
  • Monitor progress regularly and make adjustments as needed.

By taking these steps, [Company Name] can effectively transform its supply chain and achieve its strategic goals in the dynamic apparel industry.

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Case Description

Timm Veizenburg is an entrepreneur who is reviving his family's tradition of dress-shirt making. He realizes that an issue that initially looked like a markdown management problem may, in fact, be rooted in procurement. Operating in the modern data-rich environment, Timm asks an associate to prepare data about one product line, and together they examine the company's current procurement practice, where the production is outsourced to supply chain partners in western Ukraine, as well as two alternatives, with local sourcing and supply chain flexibility. The case presents a realistic dataset students can work with to master their data-analysis and modeling skills, with an application to operations and supply chain analytics. The case works well in business analytics electives within an MBA program, in specialized business analytics programs, as well as in Executive Education, and is effective in demonstrating approaches to data-driven decision making in managing operations and supply chains.

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