This case study, developed by the KPMG Master of Data and Analytics Program Team, has been designed to give instructors a meaningful way to introduce both ESG topics and data and analytics into their accounting classroom. In addition to the need for emerging accountants to be experienced with data and analytics, more companies are reporting on their ESG figures than ever before. As ESG reporting and the corresponding regulations continue to evolve, the need for university faculty to expose students to ESG topics in their classes is at an all-time high. To expand the breadth of this case study offering, there are two versions available. One option necessitates beginner Alteryx and Power BI experience, while the second option focuses on using Excel with an optional data visualization element. It has been designed to provide a meaningful learning experience for students while remaining tool agnostic.

This ESG case is focused on a hypothetical engagement team’s assurance procedures surrounding their client’s carbon emissions figures, specifically their greenhouse gas (GHG) emissions. Students are introduced to the GHG emissions calculation, as well as several relevant files containing the necessary data inputs. The materials include a complete set of facilitator notes and a slide deck to assist with an introduction of GHG emission to the classroom.

The primary target audience for these cases is an undergraduate or graduate level accounting class.

Learning objectives

The learning objectives of this ESG-related case study are as follows:

1.       Explain the concepts related to measuring and reporting a corporation’s carbon emissions.

2.       Identify the three different levels (scopes) of carbon emissions.

3.       Identify the standard calculation and its related inputs used to calculate carbon emissions.

4.       Perform several basic aspects of the work of an engagement team providing assurance over a company’s greenhouse gas (GHG) emissions. 

5.       Construct Excel workflows that will calculate and verify a company’s carbon emissions calculations using the company-supplied data.

6.       Construct Excel workflows that will provide independent estimates of a company’s carbon emissions and compare those to the company-supplied data.

7.       Develop a Power BI (or Tableau) visualization that will describe the aggregated and disaggregated carbon emissions for a company.