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Analytics Consulting Project

2 Credits

BU.520.690.X5

Wednesdays 8:15 AM – 11:15 AM B230

Required Sponsor Meetings 258

1. March 26 (Thur), 1–2 p.m.

2. April 15 (Wed), 1–2 p.m.

3. May 13 (Wed), 1–2 p.m.

Spring II 2026

Hopkins Bloomberg Center

Instructors

Communication Faculty: Christina Black, PhD | Assistant Professor of Practice, Business Communication

Consulting Faculty: Richard (Rick) Smith, PhD | Executive Advisor to the Dean, Professor of Practice, Management & Organization

Analytics Faculty: Nazli Turken, PhD | Associate Professor of Practice, Business Analytics and Operations Management

Contact Information

[email protected] 

[email protected]

[email protected]

Office Hours

TBA

Teaching Assistant

TBD

Recommended Texts & Learning Materials

Ashkenas, Rin (2017). How to Handle Underperformers on a Team You Inherit. Harvard Business Review.

Harvard Business Review Press (2019). HBR Guide to Project Management. Boston, Massachusetts: Harvard Business Review Press.

Duarte, N. (2012). HBR guide to persuasive presentations. Boston, MA: Harvard Business Review Press.

Munter, M., & Hamilton, L. (2013). Guide to managerial communication (10th ed.). Upper Saddle River, NJ: Pearson.

Nussbaumer Knaflic, C. (2015). Storytelling with data (C. N. Knaflic, Ed.). John Wiley & Sons. 

Technology Requirements 

Software: The course may involve various programming languages or software depending on the sponsor’s needs. The course does not have a goal to teach a particular package, but rather to enable analytics in a business project.

The following programming languages and software may be used in the course:

(a) Python

(b) Tableau

Course Description

In this course, students will assume the role of analytics consultants, engaging with a real-world business problem presented by an industry sponsor. Throughout the course, they will acquire the skills to scope complex business problems, select and apply pertinent analytics methodologies, prepare and analyze data, and generate actionable insights. The students will be trained to effectively communicate their findings to a variety of audiences through writing, data visualizations, and presentations. The course will equip students with the soft skills necessary to complete analytics projects. Topics covered include the basics of consulting, project management strategies, collaborative teamwork dynamics, and an examination of ethical considerations in the field of analytics.

Prerequisite(s)

Practical Machine Learning (BU.520.710), and Business Communication (BU.120.601)

Learning Objectives

By the end of this course, students will be able to:

1. Identify and characterize the analytics problem from a general description of the problem provided by the sponsor.

2. Apply project management and team dynamics principles to effectively in a real-world sponsor scenario.

3. Apply analytics methods to develop insights using data and information from several sources.

4. Create reports, visualizations, and presentations with business outcomes for technical or non-technical audiences.

5. Understand professional and ethical responsibilities in an analytics context.

6. Give and receive professional-level feedback.

Attendance
Bear in mind that your performance is being continually evaluated by faculty. Your faculty will come to class fully prepared each day; we expect you to do the same. This entails reading the assigned articles, attempting to answer questions, and being ready and willing to participate in class discussions.

Students are expected to attend all class sessions in person. Additionally, the students must comply with the school’s overall policies regarding on-site and remote-live classes. For your reference, the school's detailed attendance policies are copied below:

· Students in onsite courses are expected to attend classes in person.

· Students may miss up to one class session of a course without loss of attendance and participation points (if applicable) for the following reasons:

o If they are displaying symptoms of any illness or are within five days of a positive COVID test.

o If they inform the instructor of their intent to miss class for any reason at least 48 hours before class.

· Beyond the one allowed absence, faculty have full discretion over attendance and participation policies, subject to any disability accommodations that have been requested through Student Disability Services (SDS).

· NOTE: The exception immediately above does not apply to classes containing an in-class exam, quiz, or major deliverable. Students are expected to attend those classes in-person, unless a disability related accommodation has been requested through SDS.

· Students who anticipate or have difficulty complying with these rules should discuss any concerns with their advisor and may apply for a Leave of Absence.

Classroom Protocol

This class follows the school and university’s overall policies regarding student conduct. Additionally, it is anticipated that you uphold the highest standards of personal and professional integrity in all course-related activities. As a student of the Analytics Consulting course, you are not only representing yourself as a professional in the analytics field but also the Business Analytics and Risk Management program at the Johns Hopkins Carey Business School. 

Assignments

	Assignment	Team or Individual	Learning Objectives	Weight
Sponsor Engagement (15%)	Sponsor Engagement Plan x 2	Team	1	6%
	Sponsor Meeting Participation	Team		9%
Team Management (3%)	Team Contract	Team	2	3%
Problem Solving Skills (33%)	Status Report 1	Individual	3, 4, 5	8%
	Status Report 2	Individual	3, 4, 5	10%
	Final Status Report	Team	3, 4, 5	15%
Story-telling Skills (25%)	Midpoint Presentation	Team	3, 4, 5	10%
	Mock Final Presentation	Team	3, 4, 5	15%
	Extra Credit Final Presentation to Sponsors (Top 3 Teams)	Team	3, 4, 5	5%
	Extra Credit for Teams Ranked 4 and 5	Team		2%
Classroom Deliverables (16%)	Team Check-In x 4	Team	1, 2, 3, 4, 5	8%
	Quizzes x 2	Individual	1, 2, 3, 4, 5	8%
Feedback Deliverables (8%)	Peer Evaluation	Individual	2, 6	4%
	Peer Presentation Feedback	Team	2, 6	4%
	Total			105% (max)

Sponsor Engagement

Sponsor Engagement Plans (6%, team)

In the sponsor engagement plans, students should formulate comprehensive questions to guide their meetings with the sponsor. Sample topics to consider include

1. Understanding the sponsor's business situation and complication/challenge.

2. Understanding any data-related restrictions, such as privacy concerns or usage limitations.

3. Determining the key question that your team might address for the sponsor.

4. Understanding how the sponsor plans to utilize the recommendations of the analysis.

5. Exploring any potential constraints or limitations that might affect the analysis.

A template will be provided. 

Sponsor Meeting Participation (9%, team)

A team will receive full points if at least two members participate for the full duration, take detailed notes, and ask any questions not yet addressed by the sponsor. At the final sponsor meeting—when teams deliver their presentations—all five members of each of the top-five teams must attend. Additionally, at least two members from every other team should be present, ready to share their final recommendations if requested.

Team Management

Team Contract (3%, team) 1

The team contract is a formal agreement among team members that outlines the roles, responsibilities, and expectations for each team member, ensuring effective collaboration and accountability throughout the project. This allows team members to discuss their strengths and weaknesses early on, helping to assign roles more effectively for a successful collaboration on the project.

Problem Solving Skills: Status Reports (33%)

Each team will submit three Status Reports over the term—two drafts and one final—that blend the SCQR (Situation-Complication-Question-Recommendation) framework from class with an analysis of current findings and proposed next steps. The draft submissions provide opportunities for feedback and refinement before the final version. The sponsor will review the final recommendation worksheet and use them to select the Top 5 teams. Additionally, teams are encouraged to accompany their submissions to the analytics faculty or sponsor with any inquiries or concerns regarding the content or methodological issues.

Status Report 1 (8%, individual)

Each team must submit Status Report 1 to the faculty for feedback by 11:59 PM ET, three days after the Week 2 class session. This report should include (1) a short summary of the variables explored along with their sources and meaning, (2) at least one exploratory finding with explanation of its importance and meaning from each team member, whether based on analytics or qualitative research. It should outline the data cleaning process along with the analysis in detail. It should also be accompanied with any code. The Status Report must incorporate all requirements of the projects along with any other comments from the first sponsor meeting. Each team member should write their own portion of the findings and indicate it with their name.

Status Report 2 (10%, individual) 1, 2, 

Each team must submit Status Report 2 to the faculty for feedback by 11:59 PM ET, three days after the Week 3 class session. This report should include, from each analytics team member, at least one model application or additional exploratory data‐analysis result, and from each qualitative research team member, at least one summarized finding. It should also be accompanied with any code. All analytics errors identified in the previous status report submission must have been fixed. Teams should document their notes from the project description, sponsor meetings, and feedback from prior presentations, along with the corresponding action plans. All action plans are to be completed by the time of the final presentations; if not, a valid explanation must be provided. Each team member should write their own portion of the findings and indicate it with their name.

Final Status Report (15%, team) 2

Teams must submit their Final Status Report to faculty and the sponsor by 11:59 PM ET, on Saturday after the Week 6 class session. This document should include detailed analyses addressing each question in the team’s SCQR issue tree, plus an outline of any remaining work. The sponsor will use these submissions to select the Top 5 teams. There should be demonstration of additional completed work since the last status report submission. All analytics errors identified in the previous status report submissions must have been fixed. Teams should document their notes from the project description, sponsor meetings, and feedback from prior presentations, along with the corresponding action plans. All action plans are to be completed by the time of the final presentations; if not, a valid explanation must be provided. 

Storytelling Skills: Presentations (25%)

There will be two presentations throughout the term: Midpoint and Mock Final.

Midpoint Presentation (10%, individual comments, team grade, team presentation)1, 2, 3

Each team will present the core ideas of their project during in-class presentations. Students will be given individual feedback and team grades. The midpoint presentation must eliminate all analytics errors noted in the status report submissions and address every project requirement and sponsor request from the two meetings—either by presenting completed analyses or by outlining planned future work.

Mock Final Presentation (15%, individual comments, team grade, team presentation)1, 2, 3

Each team will present their “sponsor ready” presentations for feedback. Students will be given team grades. All comments from the Midpoint Presentation must be addressed.

Extra Credit Final Presentation (5%, team)

Selected teams will present their findings to the sponsor in Week 8. Although a template and guidance will be provided, teams are encouraged to customize their presentation format to address any sponsor-specified requirements. If a team is unable to present during Week 8, it will be reassigned to 4th- or 5th-place status and awarded a 2% extra-credit bonus instead of 5%.

Extra Credit for Teams Ranked 4 and 5 (2%, team)

All members of the teams ranked 4th and 5th must attend the final sponsor presentations and be prepared to step in if a Top-3 team cannot present. If called upon, the backup team will earn 5% extra credit.

Classroom Deliverables (16%)

Team Check-Ins (8%, team) 2,3

Throughout the term, there will be 4 team check-ins: 3 for analytics check-ins in Weeks 2, 3, and 6 during class with analytics faculty, and 1 for communication in Week 6 with communication faculty. If any team can't meet during class for the analytics check-ins, they'll need to schedule a separate time with the faculty. All team members must be present during the team check-ins.

Quizzes (8%, individual) 2, 1

Students will complete two quizzes in Week 0 and Week 1. The quizzes test students’ knowledge and readiness to engage in a professional and ethical manner with the sponsor and their proprietary data.

Feedback Deliverables (8%)

Peer Evaluation (4%, individual) 2

A portion of students’ final grade is based on peer evaluations. This means you will review and grade each other's effort, teamwork, and work products. A template will be provided.

Peer Presentation Feedback (4%, team) 3

Each team will provide feedback to other teams for the Mock Final Presentations. For the Mock Presentations, teams will identify what they think is different in their own and in others’ presentations. These identified differences will form the basis for their final presentations to the sponsor.

Grading

The grade of A is reserved for those who demonstrate extraordinary performance as determined by the instructor. The grade of A- is awarded only for excellent performance. The grades of B+ and B are awarded for good performance. The grades of B-, C+, C, and C- are awarded for adequate but substandard performance. The grades of D+, D, and D- are not awarded at the graduate level. The grade of F indicates the student’s failure to satisfactorily complete the course work. For Core/Foundation courses, the grade point average of the class should not exceed 3.35. For Elective courses, the grade point average should not exceed 3.45.

Policy on Generative AI

The utilization of Generative AI tools is strictly prohibited for all components of the project, except when explicitly permitted by the sponsor. Given that numerous companies prohibit the use of open-source AI due to privacy issues, it is crucial for students to adhere to the sponsor's specific guidelines and requirements.

Academic integrity is a cornerstone of the Carey Business School. Generative artificial intelligence (AI) tools such as ChatGPT are widely available; however, no data may be uploaded to non-JHU GenAI platforms. You are working with proprietary data protected under an NDA which you have signed, and sharing it would violate that agreement. You may, however, use GenAI tools for general coding assistance, provided that no proprietary information is disclosed.

Tentative Course Calendar

Instructors reserve the right to alter course content and/or adjust the pace to accommodate class progress. Students are responsible for keeping up with all adjustments to the course calendar.

Date	Week	Topic	Meetings (Outside of Class)	Recordings/Readings	Due by 11:59 pm ET on Saturday (unless stated otherwise)
	0			Nondisclosure Agreements	Ethics Quiz due by the first class session
	1	· Prep for the First Sponsor Meeting · After the First Sponsor Meeting · Project Plan and Sponsor Engagement Plan 1	First Meeting with Sponsor		Sponsor Meeting Skills Quiz   Sponsor Engagement Plan 1 due by 6pm on class day.   Team Contract
	2	· Exploratory Data Analysis · Accurate Data Aggregation · Analytics Team Check-In 1 with analytics faculty	Analytics Team Check-In 1 with BAAI faculty continued	Analytics Methods Review	Status Report 1
	3	· Analytics Team Check-In 2 with analytics faculty · Consulting Team Check-In with faculty		Analytics Methods Review	Status Report 2 Sponsor Engagement Plan 2 due by 6 pm on class day.
	4	· Storytelling with Data for Decks & Presentations · Executive Summaries · Uses and Limits of AI	Second Meeting with Sponsor
	5	Midpoint Presentations			Slides due by midnight before presentations
	6	· Analytics Team Check-In 3 with BAAI faculty · Communication Team Check-In with faculty	Analytics Team Check-In 3 with BAAI faculty continued		Final Status Report
	7	Mock Final Presentations			Slides due by midnight before presentations Peer Presentation Feedback
	8	Special class session with sponsor	Final Presentations to Sponsor		Peer Evaluation

The class sessions that will be led or attended by communication faculty are in italics.

The class sessions that will be led or attended by consulting faculty are in bold.

Analytics faculty will attend all class sessions and workshops except for Module 3.

Please note that the communication and analytics faculty will attend the beginning of the first class session for introductions.

Class Session Plans

Module 0

Students must submit their non-disclosure agreements before the first class in order to access the sponsor’s dataset. They will also complete an ethics quiz to ensure they understand the consequences of any NDA violation.

Module 1

This session will include working in teams, engaging with a sponsor, managing expectations, organizing work efforts, and addressing interdependencies. In addition, students must complete a quiz to verify that they understand the skills necessary to meet with a consulting sponsor. At the end of the day of the class session, each team will submit Sponsor Engagement Plan 1. At the end of Week 1, each individual will complete the quiz on sponsor meeting skills and each team will submit the Team Contract.

First Sponsor Meeting

Each project will be assigned to two sections. The students’ first interaction with the sponsor will take place during lunchtime—a 1 hour session between 11:30 am – 2:15 pm—during the first week. At least 2 members from each student team are required to attend. Each team will ask a unique question to the sponsor, selected in advance by the faculty from the students' previously submitted engagement plans. The meetings may be recorded with the sponsor’s permission.

Module 2

In class, the analytics faculty will focus on teaching data preparation and preliminary data analysis tailored to the project. The remaining class time will be allocated for analytics team check-ins, where students will share insights from their first sponsor meeting and outline their strategy for addressing the sponsor's business question through analytics methodologies. The teams will work on their analysis and Status Report 1 until the end of the class session allowing for interaction among teams. Each team will submit their Status Report 1 by 11:59 pm on Saturday.

Module 3

The class time will be devoted to Analytics and Consulting Team Check-ins, focusing primarily on how newly acquired information impacts the team's strategic approach. Asynchronously, the analytics faculty will review the analytics methods relevant to the project. Each team will submit their Status Report 2 by 11:59 pm on Saturday.

Module 4

In class, the communication faculty will coach students on how to approach their two major deliverables: the status update and presentation to the sponsor. At the end of the day of the class session, each team will submit Sponsor Engagement Plan 2.

Second Sponsor Meeting

A second sponsor meeting will take place during lunchtime of Week 4. The format will be similar to the first sponsor meeting.

Module 5

In class, each team will present the core ideas that they have been developing in their draft decks to the faculty, without their classmates in the room. While the presentations are in teams, students will receive individual feedback and team grades.

Module 6

During class, the analytics faculty will address frequently encountered methodology issues noted in Status Report 2, Midpoint Presentations or commonly raised by teams. The remainder of the time will be spent with Analytics and Communication Team Check-Ins.

Module 7

In class, each team will present draft presentations to the faculty team for feedback. Students will receive team grades. After class, each team will offer feedback to other teams as well. Communication, analytics, and consulting faculty, along with input from the sponsors, will select the top three teams from the two sections to present to the sponsors in Module 8.

Module 8

There will be a combined “Special Class Session” for the final presentations with the sponsor, and at least two members from each non-presenting team are required to attend to ensure meaningful engagement with the sponsor. Each team member will submit their peer evaluations by 11:59 pm on the day of the final presentations.  

Final Presentations to the Sponsor

The selected teams are scheduled to present their findings to the sponsor, following a meeting arrangement similar to that in Module 1. Each team presentation will be a maximum of 10 minutes with 10 minutes for questions, allowing for 60-minute sessions. Other teams will also get a chance to share their findings or recommendations with the sponsor during this meeting or in written form.

Carey Business School Policies and General Information

Please note that failure to become acquainted with Carey policies will not excuse any student from adhering to these policies.

Canvas Site

A Canvas course site is set up for this course. Each student is expected to check the site throughout the semester as Canvas will be the primary venue for outside classroom communications between the instructor and students. Students can access the course site at https://canvas.jhu.edu/.

Technical Support

24/7 technical support for questions regarding Canvas, Zoom, and other technical issues is available. Please refer to Carey’s Academic Resources webpage for contact information and other details.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions, and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services. Please request accommodations for this course as early as possible to provide time for effective communication and arrangements. For further information or to start the process of requesting accommodations, please contact Student Disability Services at the Carey Business School.

Academic Ethics Policy

Carey expects graduates to be exemplary global citizens in addition to innovative business leaders. The Carey community believes that honesty, integrity, and community responsibility are qualities inherent in an exemplary citizen. The objective of the Academic Ethics Policy (AEP) is to create an environment of trust and respect among all members of the Carey academic community and hold Carey students accountable to the highest standards of academic integrity and excellence.

It is the responsibility of every Carey student, faculty member, and staff member to familiarize themselves with the AEP and its procedures. Failure to become acquainted with this information will not excuse any student, faculty, or staff member from the responsibility to abide by the AEP. Please contact the Office of Student Affairs if you have any questions. For the full policy, please visit the Academic Ethics Policy webpage.

Student Conduct Code

The fundamental purpose of the Johns Hopkins University’s regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. Please contact the Office of Student Affairs if you have any questions regarding this policy. For the full policy, please visit the Student Conduct Code webpage.

Commitment to Respect

Respectful behavior creates an environment within the Carey Business School where all are valued and can be productive. Carey defines respectful behavior as conduct that, at a minimum, demonstrates consistent courtesy for others, including an effort to understand differences. As such, all in the community agree to the Carey Commitment to Respect, which states that we all strive to show that we value each other’s human dignity and our differences, and to choose behavior and language that demonstrates mutual respect. Please visit the Commitment to Respect webpage to learn more about the expectations and resources available.

Classroom Policies for All On-Site and Remote-Live Classes

Carey is committed to maintaining the highest standards of excellence in all forms of instruction. To that end, we have developed policies and procedures for all classes offered in on-site and remote-live formats. These policies will govern all courses occurring in these formats, and all students are expected to familiarize themselves with and adhere to these policies.

Student Success Center

The Student Success Center offers assistance in core writing and quantitative courses. For more information, visit the Student Success Center webpage.

Other Important Policies and Services

Students are encouraged to consult the Student Handbook and Academic Catalog and Student Services and Resources for information regarding other policies and services. For your convenience, there is a singular website students can visit to learn about all JHU and Carey policies.

Copyright Statement

Unless explicitly allowed by the instructor, course materials, class discussions, and examinations are created for and expected to be used by class participants only. The recording and rebroadcasting of such material, by any means, is forbidden. Violations are subject to sanctions under the Academic Ethics Policy