Data Analytics in Management Accounting

Overview

Course description

From financial statements to operating performance, the environment we are living in is “data rich, information poor.” With the decision-making pressure on accountants and managers, it is crucial to gather available data quickly, provide accurate analysis, and present financial information to stakeholders in a meaningful way.

This course covers the basic concepts and techniques of management accounting and combines it with current trends in data analytics as they pertain to management accounting. Topics include: critical thinking, financial modelling, cost behaviour, relevance for decision-making, and budgeting. Students will learn how to analyze both financial and operational data by designing financial models and dashboards, making reasonable financial forecasts, and monitor operational performance using data analytics tools.

Course content

1. Introduction to critical thinking

2. Introduction to managerial accounting

Management information and decisions
Cost behaviour (fixed vs. variable vs. mixed)
Introduction to cost systems (e.g., work-in-process vs. raw materials vs. finished goods, contribution margin, breakeven analysis)

3. Introduction to ratio analysis and data visualization (utilizing PowerBI or similar data visualization tool)

Evaluate existing data
Create visualization/dashboard for key ratios/to cater to different users of the financial statements
Define and calculate key ratios for a business owner
Design charts and graphs for different users of the financial statements
Present dashboard

4. Interpretation and analysis of pre-generated reports (e.g., developed through generative artificial intelligence tools) on a company’s financial health and assess its accuracy.

5. Forecasting, budgeting, and financial modelling

Why do we budget?
Introduction to the master budget
Critical areas of focus for a budget
Limitations and challenges with budgeting
Design and create an interactive financial model using an appropriate data analytics tool
Design the layout of the model clearly and logically
Create clearly defined inputs and assumption sections
Build powerful scenarios
Incorporate all related schedules

6. Flexible budgets and standards for control, operational dashboards

Use data visualizations to assess results and company performance compared to budget.
Define and calculate Key Performance Indicators (KPI)
Design charts and graphs for KPIs

7. Relevant information and decision-making

Evaluative criteria for decision-making, including quantitative and qualitative considerations (e.g. make vs. buy, sell or process further, keep or drop a business segment).

Learning activities

Lecture and/or seminar

All methods of instruction apply to in class, hybrid and/or online modes of learning.

Means of assessment

Assessment will be based on course objectives and will be carried out in accordance with the Douglas College Evaluation Policy. An evaluation schedule is presented at the beginning of the course. This is a graded course.

Group Project(s):

A minimum of one group data analytics 30%

Individual Activities:

In-class activities, homework assignments, and data analytics projects 30%
Final Exam 40%

Students must write all examinations in order to obtain credit for the course.

Students may conduct research as part of their coursework in this class. Instructors for the course are responsible for ensuring that student research projects comply with College policies on ethical conduct for research involving humans, which can require obtaining Informed Consent from participants and getting the approval of the Douglas College Research Ethics Board prior to conducting the research.

Learning outcomes

Upon successful completion of the course, the student will be able to:

Apply appropriate techniques to prepare both static and flexible budgets
Explain the concepts, techniques, and merits of various management control systems used in both domestic and international operations
Apply various cost allocation concepts and techniques to a variety of cost settings
Analyze financial statements using data analytics
Use information from automated data capture to form and analyze financial statements
Access, examine, and integrate different data files
Analyze data patterns, identify discrepancies, and extract unusual items
Examine financial data for existence of misrepresentations in areas such as matched or unmatched records, duplication, and limit violation
Create, interpret, and analyze dashboards
Apply the data analytics process to communicate insights and track outcomes

Textbook materials

Textbooks and Materials to be Purchased by Students

Horngren, Charles T., Sundem, Garry L., Statton, William O., Teall, Howard, D.

Management Accounting, latest Canadian ed. Toronto: Prentice Hall Canada.

Requisites

Prerequisites

ACCT 1235 or equivalent

Corequisites

None

Equivalencies

None

Course Guidelines

Course Guidelines for previous years are viewable by selecting the version desired. If you took this course and do not see a listing for the starting semester / year of the course, consider the previous version as the applicable version.

January 2025 (Current)