Charles W. Lamden School of Accountancy
ACCTG 790 “Case Studies in Accounting Practice” Spring 2016
Instructor Contact Information
Nancy Jones, SSE2420, (619)594-5331 (email is the preferred means of communication),
njones@mail.sdsu.edu
Office Hours: Mondays and Wednesdays 1:00 to 3:00
Prerequisites
Master of Science in Accountancy (MSA) student
Advanced to candidacy by SDSU Graduate and Research Affairs
Course Description
The era of “big data” is upon on us and unlike prior decades, data is so easy to acquire that the
sheer volume of data availability is sometimes daunting. Accounting professionals have access to
the data that can help them maintain or develop a strategic advantage or to remain competitive in
today’s fast-paced business environment. Those who fail to do so may put their organization at a
disadvantage. Data analytics has become a must-have skill for all business managers and
particularly accountants who often know both internal and external data, better than their
counterparts in other areas of the business.
“Data analytics is imperative for companies that wish to employ successful financial
accounting practices. It’s the key to being able to maximize profits from the supply chain,
manage production flows, score credit loans, predict customer churn and optimize
scheduling.” [Matthew France, Chief Financial Officer at GCE, EPM Channel, June 2013].
The goal of this course is to synthesize theory and application to prepare students for the
dynamics of real-world professional accounting practice: diagnosing problems and issues (often
in the face of significant uncertainty), analyzing relevant information, making responsible and
ethical decisions, and reporting decision results and recommendations. The course focuses on
analytical techniques and provides hands-on experience to develop skills with select business
analysis technologies.
MSA Degree Learning Outcomes (DLO’s)
MSA students will graduate being able to:
DLO 1.1 Students will compare, contrast, interpret, or criticize accounting and business
decisions and information using professional business communication.
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DLO 2.1 Students will actively participate in team decision making displaying interpersonal
skills, motivation, appropriate attitude, and meaningful contributions.
DLO 3.1 Students will apply ethical judgment and professional standards in analyzing situations
and formulating accounting and business decisions.
DLO 4.1 Students will use relevant research tools and academic/professional literature to analyze
or take a position in accounting and business situations.
DLO 5.1 Students will address unstructured problems in the areas of accounting information
systems, financial reporting, or taxation.
DLO 6.1 Students will identify and discuss the significance of diversity and cultural differences
in the global business environment.
This course contributes to these goals through its course learning outcomes noted below.
Course Learning Outcomes
LO1. Apply critical analytical thinking to identify and frame business problems for analysis.
LO2. Solve accounting and business related problems using appropriate analytics tools.
LO3. Create visualizations of data to provide clear insights into accounting and other business
data, to effectively communicate those insights, and to support recommendations.
LO4. Recommend appropriate actions to address real-world problems in accounting practice.
LO5. Identify and evaluate the veracity of sources of unstructured and structured data for use in
analysis.
LO6. Discuss ethical issues as they pertain to the performance and use of data analysis.
LO7. Write effectively to communicate analysis results in the framework of the business
problem.
Required Reading
 “Practical Analytics”, N. Kale and N. Jones, Epistemy Press, 2015, ISBN: 978-09856008-9-1, available as an e-book at
http://store.epistemypress.com/books/analytics.html. Use the discount code NINA2016 to
receive 50% off the list price.
 Articles and links posted on BlackBoard.
Recommended Reference Text
“The Case Study Handbook: How to Read, Discuss, and Write Persuasively About Cases”,
William Ellet, Harvard Business School Press, 2007, ISBN 978-1-4221-0158-2.
Use of Technology
Note: this is not a computer-skills course. However, it does require extensive use of the computer
as a tool. To accomplish the objectives of this course, you will spend a significant portion of
your time both in and out of the class learning and using computerized information systems with
their associated idiosyncrasies. All of the class assignments will involve the use of the computer
in one way or another.
Since much of our in-class work will utilize a computer, you will need to (want to) bring your
laptop to each class session unless I tell you otherwise. A PC-based computer is preferable to
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those with Apple/Mac operating systems as some of the software that we will be using either
works better on a PC or will not work on an Apple/Mac machine at all.
During the semester, you will be asked to download and install software on your computer or to
access systems online. Everyone’s computer is set up a bit differently and you may experience
technical difficulties. Therefore do not assume that everything will run smoothly every time. Be
sure to start assignments early to allow enough time to work through any glitches. The worst that
can happen is that you get your assignment done and turned in before the deadline. Problem
solving is a highly desirable skill in the business world, so I expect you to do your own problem
solving and work your way through any technical issues so that you can successfully complete
your assignments. Some class time may be spent using the software, but do not expect to spend
class time working through software download issues.
Software Tools Used in this Class:
The following is a list of software we may use during the semester. With the exception of Excel,
this software is currently available to you at no charge via the academic alliances with these
organizations.




Microsoft Excel 2010 or newer with Solver and Power Pivot add-ins for stochastic
modeling, data staging, and other advanced applications
Audimation IDEA for audit analytics
SAP Business Explorer (BEx) Query Designer for querying data sources
SAP Business Intelligence suite of tools for data mining, descriptive and predictive
modeling, and visualizations
You will be provided with instructions on how to load the software to your laptop or access it
online on the class BlackBoard site.
Add/Drop Policy
Any student who does not attend class during the first week of classes may be dropped from the
course. February 2 is the last day that you can drop the course via the Webportal. You are
responsible for your own adds and drops.
Exam and Quizzes
The final exam will be a case study in which you will use the analytical tools and skills you have
acquired during the semester to analyze an issue, answer questions, and/or solve a problem.
Quizzes may be announced or unannounced at the instructor’s discretion. Typically they will ask
questions about the reading materials but they may cover other topics as well. Quizzes may be
online or paper-based.
Assignments
Assignments are designed to reinforce the concepts of the lectures, discussions, and reading and
to exercise your critical thinking skills. Some assignments may be done as part of a team and
others will be done individually. Team assignments will be designated as such. Some
assignments will be started and completed during class. Others will be more comprehensive and
therefore require more time to complete. These larger assignments will be discussed or started in
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class in a collaborative environment to reduce the technology learning curve and insure
understanding of assignment instructions. Even so, you should plan to spend time and energy
outside of class to complete these assignments. Expect them to challenge you.
Grading parameters will be provided for assignments. In general, be sure to support your answers
with references, diagrams and figures, tables, and other supporting documentation. If you are
unfamiliar with how to analyze a case or unstructured problem, you may wish to refer to “The
Case Study Handbook” by William Ellet listed above as the Recommended Reference Text.
Many of the assignments, especially the “out-of-class” assignments will have more than one
correct answer. In fact, I would expect that each student’s submission will vary since it
represents the individual or his/her team’s unique perspective. Therefore, although I will provide
you with feedback in as timely a manner as possible, please allow additional time for me to
evaluate each submission for “correctness” and fulfillment of assignment requirements.
Complete all assignments in a professional manner, so that the physical appearance is neat and
orderly, the assignment is complete, and your thoughts are organized in a logical sequence.
Unless otherwise indicated, handwritten documents are unacceptable.
Follow assignment instructions carefully to maximize your grade.
To receive credit for an assignment you must complete the assignment in the proper format and
submit the assignment electronically before the deadline. Failure to do so will result in a zero
on the assignment.
Missed Exam/Late Assignment Policy
The exam and quizzes are to taken in class during the regularly scheduled time. If you believe
you are going to miss the exam or a quiz, you must notify me before it is given. Only in the rare
instance that it isn’t possible to notify me (for example, you are in a serious auto accident on the
way to take the exam and end up in the hospital), will there be consideration for not following
this rule. Proof must be brought to the instructor to validate the absence. Otherwise, this will be
an unexcused absence and the grade on the exam or quiz will be zero. To allow for unexpected
circumstances resulting in a missed quiz, the lowest quiz grade during the semester will be
dropped. Thus you could miss one quiz without deleterious effects to your grade.
Assignments must be submitted according to the instructions, but generally via BlackBoard, by
the due date. Assignments turned in after the due date will receive no (zero) credit. In other
words, no late assignments will be accepted for grading. You are responsible for knowing due
dates. If you believe that you will have a conflict with an assignment due date, you are strongly
encouraged to submit assignments early. If you are unable to attend class on the day that we are
completing an in-class assignment, you may request a substitute assignment at least a week in
advance. When possible, I will attempt to provide you with the opportunity to complete an
alternative activity. This will not always be possible, so do not count on this option. If you are
unable to complete an in-class assignment, your score on the assignment will be zero.
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Class Attendance and Participation
Typically, each class session will be part lecture and part hands-on activities. Some lecture and
discussion content will not be contained in the text and of course, group work in class cannot be
recreated. Therefore, regular attendance is all that more important for realization of the
knowledge which will help you succeed in this course (and hopefully in your career as well). If
you do have to miss a class, you are responsible for finding out what occurred during the missed
class meeting. I recommend that you ask another student to share notes or otherwise get you up
to speed.
Because this is an interactive course and we may need more or less than the originally scheduled
time to discuss a topic, the course schedule may (probably will) change. Any changes will be
announced in BlackBoard and/or in class.
Grading Policies
Case write ups will be graded based on the case study methodologies of “The Case Study
Handbook” by William Ellet. Grading parameters specific to the assignment will be provided in
the assignment instructions. All work should be professionally completed and presented. Work
that was obviously thrown together at the last minute will receive limited feedback.
Because activities may be added, changed, or omitted during the semester, the following point
assignments are approximate.
Table 1: Possible Grade Points by Activity
Activity
In-Class Assignments
Other Assignments
Quizzes
Final Exam/Case Study
Total
Points
100
265
50
125
540
Course grades will be determined by your percentage of the total points earned based on a
standard grading scale in accordance with San Diego State University policy (see Graduate
Bulletin, pp. 60-61). Graduate grades shall be: A (outstanding achievement, available for the
highest accomplishment), B (average, awarded for satisfactory performance), C (minimally
passing), D (unacceptable for graduate credit, course must be repeated), F (failing).
Other Student Responsibilities
Your first responsibility is to read and understand this syllabus and the class schedule. If you
have questions, ask them now.
It is your responsibility to come to class prepared. Read assigned material before attending class.
This will increase your comprehension of the material and will allow you to contribute to the
class in a meaningful way. You may also wish to do your own research so that you can
contribute to the class discussion.
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You are also responsible for checking BlackBoard on a regular basis. Announcements, due dates,
changes to the syllabus or schedule, additional activities, and other communications will be
posted on the site and failure to access it could mean that you miss out on important information
and any associated remuneration. Report any grade discrepancies you find in the BlackBoard
grade book within two weeks of posting. You should also retain any returned assignments for the
duration of the semester to compare against the grade book.
You are expected to behave professionally at all times during class sessions:
 Regularly attend class,
 Arrive in class on time,
 Do not leave class until the class period is complete,
 Come prepared for class – this means that you have completed the required readings and
assignments prior to class,
 Pay attention during class - this means that you will not talk to other students during class
unless the conversation is about a class topic and then is not disruptive to the other
students,
 Do not do other work or other tasks not related to the class during the class:
 Respect your classmates by being a productive, non-disruptive, member of the class.
Unprofessional behavior may result in your dismissal from class and could adversely affect your
grade.
Academic Integrity
The University adheres to a strict policy regarding cheating and plagiarism. These activities will
not be tolerated in this class. Become familiar with the policy.
If you have questions on what is plagiarism, please consult the policy and this helpful guide from
the Library
Students are expected to behave ethically in all aspects of this course. When in doubt, ask your
instructor. Cheating of any kind is an unacceptable behavior and will not be tolerated. Some of
the more common types of academic dishonesty relate to the following:
 Plagiarism - Do not use published and/or unpublished material without acknowledging
the source.
Examples of Plagiarism include but are not limited to:
 Using sources verbatim or paraphrasing without giving proper attribution (this can
include phrases, sentences, paragraphs and/or pages of work)
 Copying and pasting work from an online or offline source directly and calling it
your own
 Using information you find from an online or offline source without giving the
author credit
 Replacing words or phrases from another source and inserting your own words or
phrases
 Submitting a piece of work you did for one class to another class
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


Cheating on assignments or projects – Do not collaborate with other students unless it is
specifically stated by the instructor that working with others is allowed (e.g., a team
project).
Cheating on exams and quizzes – Do not acquire from, or give information to, other
students about exams. Do not use materials or resources during exams that are not
expressly permitted by the instructor.
For additional information on plagiarism and cheating, refer to
http://www.sa.sdsu.edu/srr/cheating-plagiarism.html.
With the exception of specifically designated group work, the assignments, and of course, the
exam and quizzes each need to represent your own independent, individual effort. Cite all
sources of information. In those cases where collaboration is allowed, list specifically those
individuals with whom you have collaborated.
Any observed or reported instance of academic dishonesty will be prosecuted to the extent
possible. During any stage of the semester, if you deviate from the standards of academic
integrity you will at minimum receive a zero on the assignment and may receive a grade of F for
the course. In addition, the instructor may report the event to the Department and the University.
The University may decide to apply additional penalties.
Please refer to San Diego State University Academic Integrity Policy for Student Discipline Rights and Responsibilities at http://www.sa.sdsu.edu/srr/conduct1.html.
Students with Disabilities
Upon identifying themselves to the instructor and the university, students with verified
disabilities will receive reasonable accommodation for learning and evaluation. If you are a
student with a disability and believe you will need accommodations for this class, it is your
responsibility to contact Student Disability Services at (619) 594-6473. To avoid any delay in the
receipt of your accommodations, you should contact Student Disability Services as soon as
possible. Please note that accommodations are not retroactive, and that I cannot provide
accommodations based upon disability until I have received an accommodation letter from
Student Disability Services. For more information, go to the Disabilities Services website at
http://go.sdsu.edu/student_affairs/sds/Default.aspx or call (619)594-6473.
Proposed Course Schedule
The course schedule that follows, gives you a week-by-week description of the course activities.
It includes the planned topics, readings, assignments, and due dates. The pace of this course is
fast and you are strongly advised to keep up with the reading and assignments.
Note: it is impossible to predict the precise flow of the course and the activities and dates may
have to be adjusted from time to time.
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Table 2: Proposed Schedule for Accounting 790 Case Studies in Accounting
Week
1
2
Class
Date
20-Jan
27-Jan
Required Reading
Articles In
BlackBoard:
1. Analyzing Big
Data
2. The Evolution of
Auditors
3. Big Data and
Analytics in Audit
Chapter 1 and 2
3
3-Feb
Chapter 5 and 6
4
5
10-Feb
17-Feb
Chapter 7
6
24-Feb
Chapter 9
7
2-Mar
Chapter 3, skip LSA
8
9-Mar
Chapter 4, focus
on transformation
9
16-Mar
Chapter 10 and 11
Other
Recommended
Reading
The Case Study
Handbook: How to
Read, Discuss, and
Write Persuasively
About Cases
Appendix A
Chapter 8
ACTG790 Case Studies in Accounting Practice - Spring 2016
Discussion Topics
Course Overview,
What is Data Analytics &
how is it important to
Accountants?
LO
Activities
Assignment Due
Dates
1
Data sources, databases
Financial Reporting &
Analysis: slicing & dicing,
queries, reports
Data Visualization: charts,
dashboards & advanced
visualization techniques
work day - no class
Data Visualization: charts,
dashboards & advanced
visualization techniques
5
possible quiz, inclass activity
1
possible quiz, inclass activity
3
intro to Retail
Fraud #3
Retail Fraud #1 Risk Assessment
Data warehouses
Extracting, transforming &
loading data for analysis,
GIGO
Data Mining, Descriptive
Models for Decision
Making
2,5
in-class activity,
intro to IDEA
possible quiz, inclass activity
Retail Fraud #3
2,5
possible quiz, inclass activity
3
1,2,4
,5
in-class activity
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Week
Class
Date
10
23-Mar
30-Mar
11
12
6-Apr
13-Apr
13
20-Apr
14
27-Apr
15
Finals
Week
4-May
Required Reading
Other
Recommended
Reading
Discussion Topics
Descriptive Models for
Decision Making
Spring Break
Chapter 12
Chapter 13
Chapter 14
11-May
ACTG790 Case Studies in Accounting Practice - Spring 2016
Predictive Data Models
Predictive Data Models
Predictive Models with
non-discrete variables and
outcomes for Budgeting &
Product Costing
Big Data issues
Interpretation &
Evaluation of results for
Internal & External
Reporting and Audit,
Ethical Considerations
LO
1,2,4
Activities
intro to
Bankruptcy
assignment,
possible quiz
1,2,4
1,2,4
possible quiz, inclass activity
in-class activity
1,2,4
1
6
intro to stochastic
modeling
assignment
discussion
acitivity
discussion
acitivity
FINAL EXAM
(comprehensive)
page 9 of 9
Assignment Due
Dates
Retail Fraud #4
Bankruptcy
Predictions
Stochastic
Modeling
Assignment