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Product cover image for Regina Food Bank: Client No-Shows Challenge

Regina Food Bank: Client No-Shows Challenge

Eman Almehdawe, Mehmet A. Begen, Nour Ben Said

Product #:W49644
Supplier:Ivey/Hill
Discipline:Management Science, Operations Management
Setting:Canada, 2026
Details:Case (PDF) • 5 pages • 2026-06-08

Subjects:

Analytics and data scienceBusiness managementData scienceOperations and supply chain management

Industries:

Public administration and nonprofits

Geography:

CanadaNorth America
Your Price:$9.71

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The Regina & District Food Bank Inc. (RFB), one of Saskatchewan’s largest charitable organizations addressing food insecurity, faced a persistent operational challenge: a significant number of clients who booked appointments failed to collect their food hampers. No-shows created a cascade of operational inefficiencies. Perishable food spoiled, while non-perishable items required time-consuming restocking. This disrupted the work of staff and volunteers, and other clients had to wait longer for appointments. RFB’s chief executive officer and operations manager needed to determine the scope of this problem and develop strategies to address it.

Learning Objectives

This case is appropriate for undergraduate or graduate courses in business analytics, operations management, non-profit management, or social-sector innovation. It is ideally positioned within a course module on predictive analytics or classification methods, following foundational instruction in descriptive statistics and data visualization. The case may also serve as a capstone exercise integrating multiple analytical techniques, or as an applied project illustrating data-driven decision-making in a mission-driven organizational context.

After working through the case and assignment questions, students will be able to do the following:
  • Conduct exploratory data analysis to identify patterns, trends, and anomalies in operational data, and effectively communicate findings through appropriate visualizations and summary statistics.
  • Develop and interpret models (e.g., logistic regression) to identify key factors associated with client no-shows and assess model performance using appropriate evaluation metrics.
  • Translate analytical insights into actionable recommendations by proposing evidence-based intervention strategies that balance operational efficiency with the mission-driven constraints of a non-profit organization.
  • Evaluate the trade-offs inherent in operational decisions within a resource-constrained environment, considering factors such as cost, equity, client dignity, and organizational capacity when recommending solutions.
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Case Study: Regina Food Bank: Client No-Shows Challenge (English version) | Ivey Publishing