2024 Super Analytics Challenge Overview

The Super Analytics Challenge 2024 emerged amidst a landscape of dynamic shifts to the modern workforce in the United States. In an era defined by rapid technological advancements, geopolitical complexities, and the lingering effects of the global pandemic, organizations are compelled to navigate unprecedented challenges while ensuring the alignment of their workforce with evolving market needs. McKinsey’s (2023) research underscores this urgency, revealing that 40% of American employers are grappling with skill shortages, underscoring the critical need for innovative approaches to workforce development. Against this backdrop, this year’s challenge addressed the barriers hindering individuals’ access to opportunities within the advanced manufacturing sector, a cornerstone of economic prosperity. Recognizing the imperative for agility and adaptability, the challenge seeks to foster innovative solutions that empower individuals with the skills and capabilities needed to thrive in an ever-evolving job market. View the PDF version of the final case that was shared with students.

Executive support and guidance were provided by executive leaders from:

Impact Highlights

Graduate Student Participants

Student Teams

Represented Universities

Solutions Provided

Media Mentions

WPXI News, Our Region’s Business – Super Analytics Challenge

View the segment >>

Pittsburgh Technology Council, TEQ Hub: 2024 Super Analytics Challenge Explores Workforce Issues

Read the article >>

Pittsburgh Technology Council: 2024 Super Analytics Challenge: Data-Driven Solutions to Local Issues

Read the article >>

Super Analytics Challenge Finale Video

Watch here >>

Student Team Information

Winning Team: Team 10

Anirudh Narayanan, University of Pittsburgh

James Cole, Duquesne University

Shiv Waleacha, Penn State University

Jinqiu Liang, Carnegie Mellon University

Yasha Kaushal, University of Pittsburgh

Executive Coach

Kee Won Song, IBM

Solution Summary

Team 10’s proposed solution for addressing workforce development issues in western Pennsylvania involves the implementation of Mobile Training Units. These units are designed to target high school graduates at the greatest risk by providing them with critical skills training, a stipend, and guaranteed job placement. To identify the target population, they utilized an ARIMA Model, considering demographic features, per-student ROI prediction, and geographic unemployment concentration. By partnering with advanced manufacturers and high schools, the solution aims to bridge the gap between education and industry needs, thereby cultivating a skilled and educated workforce to meet the demands of the region’s advanced manufacturing sector.

Team 1

Siva Komaragiri, Carnegie Mellon University

Erumusele Onotole, Duquesne University

Anisha Anisha, Penn State University

Tanushri Sunil Gavali, University of Pittsburgh

Zhu Yuchen, Carnegie Mellon University

Executive Coach

Rachel Rangel, Prosphire

Solution Summary

Team 1 proposed to aid workforce development agencies in Pennsylvania and West Virginia by connecting underrepresented youth to existing programs in the advanced manufacturing industry. They plan to address identified concerns, gathered through interviews and data analysis, by implementing specific policies such as targeted marketing, training programs, internships, and career explorations. By leveraging partnerships with organizations offering technical upskilling and engaging with public schools for data insights, their solution aims to create a more adaptive ecosystem for skill development among high school students in the region.

Team 2

Anni Kang, Carnegie Mellon University

Carlos Salazar, Duquesne University

Jane Yun, Penn State University

Yongha Jang, University of Pittsburgh

Zhaoyang Feng, University of Pittsburgh

Executive Coach

Deepa Pai, Accenture

Solution Summary

Team 2 proposed the creation of a centralized website that assists job seekers in the manufacturing industry by suggesting in-demand skills and providing links to local skill-building resources. Their solution aims to address the workforce development challenges in western Pennsylvania by emphasizing certification and licensing, thus bridging the skills gap and fostering industry growth aligned with future labor market demands. Through data-driven insights, including correlation analysis between wages and certifications, and utilizing techniques like Random Forest Regression, they aim to enhance the attraction and retention of young talent in the manufacturing sector.

Team 3

Abhishek Kulshrestha, University of Pittsburgh

Ying Zhou, Carnegie Mellon University

Keval Lethiya, Duquesne University

Ganeshraman, Penn State University

Shirley Zhang, University of Pittsburgh

Executive Coach

Manoj Krishna, Accenture

Solution Summary

Team 3 proposed an integrative assessment approach to unite students with regional manufacturers in the energy and transportation sectors, aiming to minimize the skills gap and bolster sector resilience. Their solution utilizes data modeling, market research, and performance metrics to tailor results to individual circumstances, fostering effective connections between key stakeholders. Additionally, they plan to extend their solution into an integrative app, providing a platform for seamless collaboration and communication among students and manufacturers in western Pennsylvania.

Team 4

Anmol Kumar, Carnegie Mellon University

Darnell Grate, Duquesne University

Sukanya Mandal, Penn State University

Ghassan Salah, University of Pittsburgh

Mengyan Zhang, University of Pittsburgh

Executive Coach

Curren Katz, Johnson & Johnson

Solution Summary

Team 4 proposed a three-pronged strategy to address workforce development challenges in western Pennsylvania by employing data analytics to design and implement incentive programs tailored for underrepresented communities in advanced manufacturing careers. Their solution includes incentivizing and improving workforce conditions through specialized mentorship for women in the field and enhancing employable skill development and entrepreneurship opportunities. Utilizing data cleaning, visualization, and predictive modeling techniques, they aim to boost participation from underrepresented communities and foster a more inclusive and diverse workforce in the region’s advanced manufacturing sector.

Team 5

Yiwen Zhao, Carnegie Mellon University

Shenrui Guan, Penn State University

Astrid Rolon Rosa, University of Pittsburgh

Navodita Mathur, University of Pittsburgh

Tiffany Salamone, West Virginia University

Executive Coach

Justin Mallgrave, Xylem

Solution Summary

Team 5 proposed the development of a mobile app called “FemInnovate” aimed at assisting women in overcoming barriers in the advanced manufacturing sector. The app focuses on addressing recruitment, promotion opportunities, and leadership development, thereby leveraging technology to support women in STEM fields and enhance their success in manufacturing careers. By analyzing worker skills, profiles, and industry demands, they aim to tailor the app’s features to bridge the skill gap and promote inclusivity in the western Pennsylvania workforce.

Team 6

Anahita Subramanya, Carnegie Mellon University

Bala Sai Nadh Kesana, Penn State University

Nikitha Tirumala, University of Pittsburgh

Yu Feng, University of Pittsburgh

Megan Smagala, West Virginia University

Executive Coach

Scott Dietz, Catalyst Connection

Solution Summary

Team 6 proposed a solution that utilizes data analysis of wages by county and training funded with career grant award allocations to ensure alignment between regional companies and entry-level applicants in the advanced manufacturing sector. Their approach involves analyzing county data within the industry and mapping out opportunities to connect career-seeking individuals with appropriate training programs, partnering with companies to recommend effective approaches based on successful strategies observed across various counties in Pennsylvania. By leveraging data insights, they aim to facilitate a more efficient and targeted workforce development process, addressing the workforce challenges affecting western Pennsylvania.

Team 7

Shambhavi Bhushan, Carnegie Mellon University

Regulavalasa, Penn State University

Joshua Misiura, University of Pittsburgh

Glenn Whited, West Virginia University

Executive Coach

Eric Fiedler, Ajinga

Solution Summary

Team 7’s proposed solution focuses on addressing barriers to entry for women in Advanced Manufacturing (AM) and manufacturing while ensuring workplace equity through a two-pronged training approach. They utilized data from the Bureau of Labor Statistics, Census Bureau, and American Community Survey (ACS) to model the impact of various factors on average wages in the industry. Their solution involves providing training opportunities for women in low-skill, underpaid jobs to transition into AM roles and offering advancement pathways for women in AM associate positions to progress to engineering positions, thereby promoting gender diversity and equity in the workforce of western Pennsylvania.

Team 9

Muskan Aggarwal, Carnegie Mellon University

Samuel P. Baycer, Duquesne University

Derek Jiang, Penn State University

James Arnott, University of Pittsburgh

Thomas Leech, University of Pittsburgh

Executive Coach

Trey Randal, BNY Mellon

Solution Summary

Team 9 proposed to expand and promote existing training programs aimed at skill development for incarcerated individuals in western Pennsylvania by targeting counties in need based on correctional data and utilizing a Python-based job and skill forecast model. Their solution emphasizes a systematic and integrated approach that capitalizes on already-existing frameworks, aiming to facilitate the rehabilitation and reintegration of individuals into the workforce and advanced manufacturing sectors. By providing dedicated and hardworking workers, they seek to benefit both employers in the manufacturing sector and the broader community, contributing to a more inclusive and productive workforce.

Advisory Committee

Industry Partners

Albrecht Powell, Managing Director, Data & Applied Intelligence & Pittsburgh Office Managing Director, Accenture

Onyinyechi Daniel, Vice President, Data & Analytics Strategy, Highmark Health

Bob Schukai, Executive Vice President, Technology, Mastercard

Andy Hannah, President, Othot, & Executive Director, 1486 Labs

Manpreet Saini, VP Professional Services, Analytics and Insights, SAP

Andy Sudar, Director, U.S. Commercial Services Sales Consulting & Business Development, SAS

Community Partners

Dillon Moore, Sr. Director, Policy & Data, Partner 4 Work

Jonathan Kersting, Vice President of Communications and Media, Pittsburgh Technology Council

Linda Topoleski, Workforce Development Consultant

Dave Rea, Managing Director, Human Capital Team at Catalyst Connection

Zachary Markovits, VP, Local Practice Lead, Results for America

Academia

Tad Brinkerhoff, Assistant Dean, Tepper Masters Programs, Carnegie Mellon University (Tepper)

Karen Donovan, Senior Associate Dean for Academic Programs and Executive Education and an Associate Professor of Marketing, Duquesne University (Palumbo)

Chris Solo, Associate Clinical Professor of Supply Chain and Analytics, Penn State University (Smeal)

Thomas Bias, Associate Professor, Health Policy, Management, and Leadership, West Virginia University

Rebecca Badawy, Associate Dean, University of Pittsburgh (Katz)

Christopher Barlow, Director, Corporate Engagement & Career Services, University of Pittsburgh (Katz)

Nausheen Fatima, Student Case Writing Team Lead & MS student, University of Pittsburgh (Katz)

This was my first experience in a case challenge, and initially it was challenging, but we learned a lot throughout the competition. We worked well together as a team and are now more knowledgeable on the topic.

Anmol Kumar, MIS '24

Carnegie Mellon University

Muskaan Aggarwal, MIS '24

Carnegie Mellon University