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Lee Valley Tools: Oversized Challenges

Geoffrey T. Pond, Nicole Bérubé, Nicholas Parsons

Product #:W36174
Supplier:Ivey
Discipline:Management Science, Operations Management
Setting:Canada, 2021
Details:Case (PDF) • 9 pages • 2024-02-20

Subjects:

LogisticsAnalytics and data scienceBusiness managementData scienceOperations and supply chain management

Industries:

Goods, trade, and consumer services

Geography:

North AmericaCanada
Your Price:$10.54

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Nick worked as the weekend shift leader at the fulfillment center of Lee Valley Tools. in Ottawa. The company operated three shifts—a day and night shift on weekdays and a weekend shift on Saturday and Sunday. Reviewing performance statistics, Nick noted that members of the night shifts in the warehouse seemed to be achieving higher performance in order fulfillment and line item fulfillment. On the other hand, the members of the weekend shifts were more aligned with the performance of members of the day shift, which had to deal with deliveries of incoming items and placing these items in the warehouse. Nick wondered why the weekend shift seemed to lag behind. He also wondered whether these differences were significant and meaningful. Nick found that there appeared to be a lag in the picking and packing processes.

Learning Objectives

This case can be used in undergraduate- and graduate-level programs. If used within the context of Lean management —or operations management—it can help to demonstrate the application of the DMAIC cycle, focused on process improvement. In this application, summary statistics (e.g., average productivity by shift) are sufficient to launch a discussion on improving the process. Conversely, if used within the context of a course in management statistics or supply chain analytics, this case is especially useful for demonstrating the pitfalls of utilizing exhaustive paired t tests among several samples and thereby increasing the probability of executing a type-one error with each additional test. After working through the case and assignment questions, students will be able to do the following:
  • Leverage statistical tests to demonstrate significant differences between sample data sets. The opportunity also exists for students to demonstrate the dangers of using exhaustive t tests among sample averages rather than the more demanding ANOVA test paired with posthoc tests (this teaching note uses either Tukey Honest Significant Difference (HSD) or Tukey-Kramer posthoc tests in the “Q1 – Productivity” worksheet of the accompanying Microsoft Excel workbook).
  • Demonstrate the value of applying principles of Lean Six Sigma management (or the Toyota Production System) to reduce process variability. The statistical analysis can contribute to the well-known define, measure, analyze, improve, and control (DMAIC) cycle as the basis for the analyze stage; or the study stage of the plan-do-study-act (PDSA) cycle. This teaching note uses the more contemporary DMAIC cycle.
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Case Study: Lee Valley Tools: Oversized Challenges (English version) | Ivey Publishing