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Mastry Maltings: Data Modelling

Derrick Neufeld, Alexander Brown, Harsh Soni, Sandeep Jangir

Product #:W41376
Supplier:Ivey
Discipline:Information Systems, Management Science
Setting:Canada, United States, 2024
Details:Exercise (PDF) • 3 pages • 2024-12-05

Subjects:

Technology and analyticsAnalytics and data scienceInformation systemsData science

Industries:

Fabrication and manufacturing

Geography:

North AmericaCanadaUnited States
Your Price:$10.54

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Mastry Maltings, founded in 1990 in rural Saskatchewan, Canada, supplies malt to brewers, distillers, and food manufacturers. As the company expands, new regulatory traceability requirements challenge its reliance on Excel spreadsheets for data management. The malting process—from grain procurement to blending—requires detailed documentation for quality control and compliance purposes. This case focuses on designing a scalable data model to track grain lots, malt batches, machinery, operators, and customers while integrating quality control. Students will develop a database system to ensure compliance and efficiency and support business analytics.

Learning Objectives

This exercise is suitable for undergraduate or master’s level courses in data analytics, information systems, and operations management, offering angles such as system design, implementation, and strategic analytics. After working through the exercise and assignment questions, students should be able to do the following:
  • Develop a comprehensive data model that captures the data elements and relationships involved in Mastry Maltings’ operations, from grain procurement to final malt production and blending.
  • Identify key production, quality, and compliance metrics needed to track performance and meet regulatory standards within the malting industry.
  • Apply business analytics insights to improve operational efficiency, enhance product quality, and support competitive positioning for Mastry Maltings in the market.
  • Evaluate the implementation challenges associated with transitioning to a centralized data system, including data migration, integration with legacy systems, and employee adaptation.
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Exercise: Mastry Maltings: Data Modelling (English version) | Ivey Publishing