The purpose of the case study assignment is to provide an opportunity
to demonstrate their ability to apply concepts learning via assigned
readings and course lectures to solve business problems. Students are
required to read the assigned case study and case studies are accessible
via the Harvard Business Publishing coursepack which can be accessed
via the link provided at the top of the syllabus. Case analyses
assignments should be submitted via Canvas in the appropriately labeled
assignment folder.
A case analysis requires you to apply the knowledge you have gained
through your assigned readings and class lectures to: (1) investigate a
business problem, (2) examine the alternative solutions, (3) and propose
the most effective solution using supportive evidence. Please review
the “Case Study Primer” document uploaded to the “Readings” folder prior
to completing your first case assignment.
Grading Criteria:
- Case analysis should be 1-2 pages in length (Strictly no more than 500 words)
length using Times New Roman, 12-point font, double-spaced, .doc or
.docx format. Failure to follow the formatting guidelines will result in
a reduction of points for professional writing. Each case will be
graded utilizing a rubric and it is encouraged that you review the
grading rubric prior to completing the assignment. Case study
assignments are worth 50 points each and are approximately 25% of your
overall course grade. - The format of the case analysis should be one comprehensive document
(rather than bullet points addressing each of the sections) and should
contain the four sections listed below.
I. Introduction: This section should identify the key problems and issues in the case study.
II. Background: This section should provide background information, relevant facts, and the most important issues.
III. Address Questions: Each case
assignment will include questions that need to be addressed. This
section should provide responses to the questions presented applying the
knowledge you gained through your assigned readings and class lectures.
IV. Solutions and Recommendations: This
section should contain proposed solutions and recommendations and
strategies for accomplishing the proposed solutions. Apply concepts from
your assigned readings and class lectures to support your suggestions
with solid evidence.
All case studies are due at 8:00AM EST on Mondays. Late submissions will not be accepted and zero points will be awarded.
Case #3:
Jennie Maze Limited: Enhancing Call Center Performance Using Predictive Analytics
Case Questions:
- What is the business problem and what would be your predictive analytic approach to solving it?
- What data inconsistencies did you find and how would you resolve
them? Explain the structure of the data and how you would clean the
data.
Solutions and Recommendations:
What are the next steps that should be completed to have a fully
functional and automated approach for forecasting incoming call volume
at each of the six call centers across the US?