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- A practical guide to SEC ï¬nancial reporting and disclosures for successful regulatory crowdfunding
- Quality shareholders versus transient investors: The alarming case of product recalls
- The Health Equity Accelerator at Boston Medical Center
- Monosha Biotech: Growth Challenges of a Social Enterprise Brand
- Assessing the Value of Unifying and De-duplicating Customer Data, Spreadsheet Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise, Data Supplement
- Building an AI First Snack Company: A Hands-on Generative AI Exercise
- Board Director Dilemmas: The Tradeoffs of Board Selection
- Barbie: Reviving a Cultural Icon at Mattel (Abridged)
- Happiness Capital: A Hundred-Year-Old Family Business's Quest to Create Happiness
Outsourcing, Near-sourcing, and Supply Chain Flexibility in the Apparel Industry (B)
內容大綱
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.