MSBA APPLIED PROJECT SHOWCASE
2023-24
May 31 ,2024
9:00am – 4:30pm
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Location: UW Tacoma Campus, Joy 215 (Presentation)
TLC-SNO Building (Poster Session)
Morning sessions will be livestreamed on this page.
SCHEDULE
9:00 am – 9:15 am
Opening Remarks (MLG 110 & Livestream)
- Michael Turek – Assistant Teaching Professor, MSBA Director and CBA Associate Director
- Sergio Davalos, Ph.D. – Associate Professor; CBA Director
9:15 am – 12:15 pm
MSBA Student Project Presentations (JOY 215 & Livestream)
12:15 pm – 12:30 pm
Information Session (JOY 215 & Livestream)
- Michael Turek
12:30 pm – 2:00 pm
Lunch & Networking (JOY 215 )
2:00 pm – 3:00 pm
MSBA Poster Session (TLC)
3:00 pm – 4:30 pm
Calling for Applied Project Proposals for AY 2023-24!
Does your business have a challenging problem to solve? Are you seeking data-driven insights about your organization? If so, submit your project proposal before the application deadline, June 1O, 2024. We look forward to co-creating value with you!
WATCH THE LIVE STREAM RECORDING!
If you couldn’t join us in-person in UWT campus, you can still watch the event recordings at this virtual event webpage. Here, you can find the livestream of morning sessions and learn more about the projects and our student consultants.
Please scroll down and go to the last section to learn more about this year’s projects and our student consultants.
Hear from Our Students
The MSBA program was transformative, offering excellent courses, respected professors, and extensive resources. The classes and hands-on projects enhanced my skills in data analysis, decision-making, and teamwork. I am very thankful for the amazing support from the CBA staff, the MSBA faculty and staff, and my entire cohort. Balancing studies with a full-time job and three kids was challenging but rewarding, providing me with valuable skills, a strong network, and lifelong friends. Special thanks to my husband, Irfan, and our children, Ezgi, Deniz, and Ozan, my mom and friends for their encouragement and support!
The Masters in Business Analytics program at UW Tacoma has exceeded my expectations in every way. The comprehensive curriculum, practical focus, and support from faculty have been instrumental in my growth as a data analytics professional. I am immensely grateful for the opportunity to be a part of this program and would highly recommend it to anyone looking to pursue a career in the dynamic field of business analytics.
During the MSBA program, I got an opportunity to gain hands on experience in working with BI tools and techniques. The applied project gave a holistic experience of working on agile methodologies. This one-year MSBA program helped me to enhance my critical thinking, data analysis and deriving solutions skills. I would like to thank my husband Hemanth Vasana and my daughter Aradhya who supported me throughout the program by motivating and cooperating. The MSBA program has prepared me very well to work with any data-driven organization.
Virginia Mason Franciscan Health-1
Healthcare and Financial Analytics
Healthcare
Underutilization of different locations within their network, VMHF aims to transfer patients without compromising their health, maximize the use of other facilities, and obtain financial benefits by utilizing underutilized facilities. This evaluation encompasses ensuring effective delivery of value to patients, maximizing facility usage without compromising patient health, and addressing lag periods between surgeries. Additionally, transferring patients to underutilized facilities serves as a strategic solution to optimize resource utilization while maintaining patient care standards
#Financial Analytics, Healthcare Analytics, Markerting Position.
Aayu Bajaj
Harshita Manganahalli
Sajan Karki
Zafar Iqbal
Mohamed Abdi
Virginia Mason Franciscan Health-2
Healthcare and Financial Analytics
Healthcare
Our project aims to reduce surgical supply costs for VMFH using advanced data analytics and machine learning. We analyzed surgeon preference cards to identify key variables influencing costs and developed a predictive model using Azure ML and R Studio. This model forecasts costs and suggests savings through alternative products. We deployed it as a web service and integrated it into Power Apps for real-time predictions. Additionally, we created a Power BI dashboard to visualize cost predictions and potential savings. This comprehensive approach empowers stakeholders with data-driven insights for cost optimization, demonstrating significant potential for reducing expenses and improving surgical supply management. Our methodology ensures a strategic framework for ongoing efficiency and cost reduction.
#Operations/Optimization, Financial Analytics, Predictive Analytics
Sachi Sangrakhyana
Withney Okonye
Aaron Thai
Bikramjit Singh
MultiCare Health System
Healthcare
MultiCare Off-Campus Emergency Departments (OCEDs) are part of a large hospital and have been growing steadily each year, with patient numbers varying by season. Predicting daily patient volume is challenging due to growth and seasonal changes, affecting staffing and resource planning. The goal of this project is to analyze and predict patient volume trends at MultiCare OCEDs, focusing on growth and seasonal variations.
#Healthcare Analytics
Anwesha Mohanty
Kunsulyu Janabayeva
Vani Anilkumar
Navneet Singh
Safiye Filiz Kula
Radius Recycling
Steel Manufacturing and Scrap Metal Recycling Company
#Customer Service Analytics, Agent Allocation Optimization.
Ayub Mirreh
Nasir Sheikh
Sravani Ravula
Siddesh Hassan Lingaraj
Sound Credit Union
Banking and Fintech
The project aims to deal with the problem of rising customer delinquency at Sound Credit Union. The objective is to build a predictive model to assess and mitigate delinquency, considering trends and patterns from previous data. This will transform the reactive approach Sound is now using into a proactive one. Using customer data from Q4 of 2021 to Q3 of 2022, we built a ML model using a two-class boosted decision tree algorithm. The model currently has an accuracy of 75.4%, which indicates a strong capability of identifying high-risk customers. This predictive model will enable early identification of delinquent customers, which will allow Sound Credit Union to act before delinquencies occur, enhancing financial stability for members and reducing potential losses for the credit union.
#Predictive Analytics
Moosa Naushab
Bowie Stanescki
Akshay Palle
Akanksha Garg
Le Hai Trieu Tran
Toysmith
Toys Retail and Wholesale
Faire.com, a leading online wholesale portal, caters Toysmith’s products to over 10K independent retailers. Traditionally being a B-2-B Toy manufacturing and distribution company, Toysmith is a trusted partner and supplier to various big chains across different industries. To monetize and grow online e-commerce platforms, the project is scoped to tackle optimized demand forecasting for over 560 prominent products contributing to over $10 million in revenue. The project intends to forecast demand considering the patterns and trends in demand in the past. The goal is to predict demand accurately to aid the procurement team in maintaining inventory efficiently. This is intended to result in a reduction of out-of-stock and lost sales. The team has developed carefully curated a machine learning model to forecast demand and achieve set goals.
#Inventory, Marketing, Scheduling
Revathi Chintapalli
Liyihui Peng
Yan Liu
Simran Kaur Hora
UW Tacoma
Higher Education
Our project focuses on developing an analytical model to predict and flag students at risk of dropping out from the university. Utilizing data modeling of past student information, we analyze various factors influencing student retention, such as academic performance, attendance records, demographic information, and engagement metrics. By identifying at-risk students early, our dashboard aims to enable targeted interventions, improving overall retention rates and supporting student success. This proactive approach leverages machine learning algorithms to provide accurate, actionable insights, helping the university to potentially implement effective strategies to enhance student support and reduce dropout rates.
#Student Retention Analytics, Predictive Analytics, Educational Data Mining
Dana Abdirakhym
Dounia Benjdya
Justin-Alec Cabanos
Sukhdeep Kaur
Diane Hoang
Swire Shipping North America
Shipping
The Swire Shipping North America project aimed to enhance customer insights and streamline the detention collection process. We developed a neural network regression model using Azure Machine Learning Studio to predict days in charge, created a Power Apps prototype for tracking detention proposals and disputes, and analyzed customer behavior with Power BI dashboards. Swire Shipping can utilize these tools by integrating the predictive model into their data pipeline, expand the Power Apps for better internal access to detention data, and conduct quarterly analyses using the Power BI dashboards to continuously improve operations.
#Operations
Chun Wang
Lourdes Sinsaya Ccorimanya
Isaiah Hatch
Currie & Brown
Construction Consulting
#Construction Material Cost Analytics
Sheba Baichan
Jonathan Dudley
Paul Shemchuk
Nhung Le
Grace Tembreull
Communities in Schools of Tacoma
Non Profit Organization
#Predictive Analytics, Optimization Analytics, and Financial Analytics.
Brandon Bourgette
Sean Wang
Camille Martinez