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• Case | HBS Case Collection | June 2020

  Vanguard Retail Operations (A)

  Willy C. Shih and Toni Moreno

  The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or specialists who focus on a subset of the overall transaction mix. The objective is to introduce the advantages of demand pooling in reducing the variability associated with the forecasting of highly variable workloads, while also demonstrating the benefits to worker learning and efficiency improvements that can come from specialization.
  
  The case is set at the Retail Investor Group Operations of the Vanguard Group, the mutual funds and ETF giant. Karin Risi, the managing director, is faced with a back-office operation that hasn’t kept up with massive transaction growth, one that is struggling under the weight of mounting client phone call and transaction volumes, client complaints, and buckling employee morale. And worse, the press was taking notice. The (A) case details the complexity in the growing backlog and frames the question of whether they should pursue a specialist model. The (B) case, for distribution in class, details the impact of an initial segmentation of workload into eight categories and poses additional questions for class discussion and analysis.

  Keywords: pooling; generalist model; specialist model; Operations; Service Operations; Management; Financial Services Industry; United States;

  Citation:

  Shih, Willy C., and Toni Moreno. "Vanguard Retail Operations (A)." Harvard Business School Case 620-104, June 2020.  View Details

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• Supplement | HBS Case Collection | June 2020

  Vanguard Retail Operations (B)

  Willy C. Shih and Antonio Moreno

  The first two cases in this series are set in the financial services industry, and explore whether it is better for back-office workers to be generalists who provide the flexibility of being able to handle the complete range of transactions that the company faces or specialists who focus on a subset of the overall transaction mix. The objective is to introduce the advantages of demand pooling in reducing the variability associated with the forecasting of highly variable workloads, while also demonstrating the benefits to worker learning and efficiency improvements that can come from specialization.
  
  The case is set at the Retail Investor Group Operations of the Vanguard Group, the mutual funds and ETF giant. Karin Risi, the managing director, is faced with a back-office operation that hasn’t kept up with massive transaction growth, one that is struggling under the weight of mounting client phone call and transaction volumes, client complaints, and buckling employee morale. And worse, the press was taking notice. The (A) case details the complexity in the growing backlog and frames the question of whether they should pursue a specialist model. The (B) case, for distribution in class, details the impact of an initial segmentation of workload into eight categories and poses additional questions for class discussion and analysis.

  Keywords: pooling; generalist model; specialist model; Service Operations; Management; Financial Services Industry; United States;

  Citation:

  Shih, Willy C., and Antonio Moreno. "Vanguard Retail Operations (B)." Harvard Business School Supplement 620-105, June 2020.  View Details

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• Article | Production and Operations Management | May 2020

  Inventory Auditing and Replenishment Using Point-of-Sales Data

  Achal Bassamboo, Antonio Moreno and Ioannis Stamatopoulos

  Spoilage, expiration, damage due to employee/customer handling, employee theft, and customer shoplifting usually are not reflected in inventory records. As a result, records often report phantom inventory, i.e., units of good not available for sale. We derive an optimal polynomial-time algorithm for the auditing and replenishment problem with phantom inventory, under the assumption that inventory is known immediately after replenishment. Moreover, we numerically show that a projected service-level threshold policy performs comparably to the optimal.

  Keywords: shelf availability; inventory record inaccuracy; optimal replenishment; retail analytics; Performance Effectiveness; Analysis; Mathematical Methods;

  Citation:

  Bassamboo, Achal, Antonio Moreno, and Ioannis Stamatopoulos. "Inventory Auditing and Replenishment Using Point-of-Sales Data." Production and Operations Management 29, no. 5 (May 2020): 1219–1231.  View Details

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