Although International Financial Reporting Standards (IFRS)

Global adoption of International Financial Reporting Standards (IFRS) is thought to increase financial statement reliability and comparability. Although IFRS is required or allowed in over 130 nations, some countries modify IFRS as issued by the International Accounting Standards Board (IASB). This study is designed to closely examine each country that modifies IFRS in an effort to determine whether these modifications impair financial statement comparability. First is that countries lack the resources to implement the newest version of IFRS or ensure proper translation of the standards. Second is that countries make specific changes to allow IFRS to better meet the needs of their financial reporting environment. I categorize the first set of countries as default countries and the second set as design countries. The study results in several interesting and useful contributions. First, I develop a new typology for future IFRS research that includes not only the locally adopted category, but also the default and design categories. Second, the details of how countries modify IFRS make it clear that differences can exist in financial statements prepared in different countries both using IFRS. The users must be careful to understand how comparability may be impacted by these modifications.

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Using materials from PwC’s data analytics case study with a fictitious company, Pixystems Toy Company, Inc. (PwC, 2017), henceforth Pixystems Toys, the authors developed a comprehensive, multi-part data analytics project applicable in a variety of accounting courses.  The project follows the common data analytics framework (ask the right questions, extract, transform and load (ETL) the data, perform appropriate analyses and present the results).  Students apply this framework to the sales and purchases cycles.  For each students develop relevant questions, build a data model and perform other ETL procedures, perform analytics and prepare a presentation to convey insights and recommendations.  For the sales cycle, Microsoft Excel is the analytics tool; for the purchases cycle, Tableau is used. This project provides an opportunity for students to gain experience with two analytics tools, understand the process of building a data model, and wrestle with how to convey the results of their analysis.

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