- Advanced Data Management
- Hypothesis Testing[AF1]
- Economics, Marketing and Finance
- Prescriptive Models
- Correlation vs. Causation
- Difference in Differences
- Discrete Choice Models
- Reports
- Game Theory
- Market Entry
- Growth Strategy
- Product Experimentation
- Pricing Models
- Machine Learning
- Text Analytics
- IP Optimization
- Clustering
- Supply Chain Design
- Inventory Management
- Scheduling
- Personalization
- Production Planning
Capstone: Applied Analytics Project
A Unique and Attractive Proposition
The UCLA Anderson Applied Analytics Project (AAP) is a real solution to your pressing analytics issues via a consulting project by the No. 1 business analytics master’s program,* and is a partnership that advances our students' futures.
The AAP is a 10-week project serving as the students' comprehensive exam, and it should represent their best efforts.
-
NDA: A standard nondisclosure agreement protects the client and all data, and it provides full ownership to the client in the end.
-
Time: Clients agree to meet with their team six to eight times during the project.
-
Data: Clients provide UCLA data access for the sole purpose of solving the related strategic problem. Access is necessary for project completion, when all data is returned to client.
A Comprehensive Process and Analysis
AAP clients and UCLA Anderson faculty work together to develop an actionable project scope.
Teams, balanced in their skills, work with faculty and the client from the experimental design phase to deep analysis to model building, and then communicate their results and recommendations.
Time commitment: Four to six video conference calls over 10 weeks
Data commitment: Medium-to-large data set to be analyzed and reported on
Analytics Tools and Techniques Employed:
Sample Projects
We have a variety of approaches, depending on project need, industry vertical and project scope enclosed in the following deck:
Let’s Connect
Email cheryl asahi if you have any questions or are interested in the AAP.
The Applied Analytics Project (AAP) serves as a capstone to the Master of Science in Business Analytics (MSBA) curriculum and represents an opportunity to merge theory and principles with up-to-the-minute business practice.
The hands-on AAP helps prepare our students for a career in quantitative analysis and data science by testing their ability to solve complex analytical business problems in real-world settings.
MSBA candidates also hone their communication skills and delve deeply into an area of interest beyond the classroom. The UCLA Anderson MSBA program takes pride in this important partnership with the analytics community and invites you to take a closer look at the benefits available to both corporate clients and students.
Program Structure
UCLA Anderson MSBA AAPs are designed to provide companies and organizations of all sizes access to scarce business analytics talent. AAPs are completed in groups of up to four students and serve as the master's thesis and graduation requirement for all MSBA candidates. Students will be challenged to use their newly acquired data management, quantitative analysis and business communications skills to unlock the hidden insights in your data.
The Process
Our students will begin by gathering all of the information necessary to understand the organization and the analytics question at hand. In the same period, the client organization will be gathering and organizing any data that the team will analyze.
They will work with you and their faculty advisor to determine which business analytics approach is best suited to your problem, and they will then apply that method to analyze your data.
Finally, the team will report on their findings and any newly developed analytical practices.
The outputs of this exercise may include
- New statistical insights previously unavailable to the company
- New metrics and key performance indicators (KPIs)
- Process optimization recommendations and models
- Predictive and prescriptive analytics approaches
- Data management recommendations
- People and process recommendations to support your data science practice
Requirements
- Quantitative data of reasonable quality and in sufficient quantity to serve as a project
- Two client contacts who will serve as primary and secondary project contacts for the team
- Regular progress calls with the team during the active phase of the project (October–December)
- All parties sign standard UCLA Anderson nondisclosure agreement
How to Apply
Please submit your application online at our program website. We will review your applications and schedule a short application review call to clarify any questions and to confirm your interest.
Student teams will then review the lead list and a bid-and-match process will be used to match teams with projects.
This project description will set the scope of the project and align all parties’ expectations. It will include:
- The topic
- A short background and review of related research
- The scope of the project
- The data required and planned data sources
Students will complete secondary research over the summer and will present a refined scope to the company and their advisor at the beginning of the following quarter. The goal is to have all required data assembled during the summer and made available to students at the start of fall quarter. Throughout the fall quarter, students and client will hold conference calls at least once every two weeks.
In early November, students will submit a midpoint report on the project, and the final report will be completed in early December.