Impact Analytics

Analytics → Action → Impact

By design, Analytics at Wharton is a trailblazer. The first of its kind, Analytics at Wharton unites the School’s innovative teaching, research, and industry engagement initiatives that use data to improve decision-making and generate actionable business insights across a variety of industries.

We are united in our core value of using analytics to create lasting societal and environmental impact. We generate cutting-edge research, uncover dynamic insights, inform business practices and public policy, inspire the next generation of business leaders, and create pathways for organizations and historically excluded populations to gain access to analytics education and resources.

Together, we can strengthen business and create a more inclusive, equitable, and sustainable global economy.

By the Numbers

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Research Projects Funded
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Scholarship Funding Raised
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Students Engaged

Focus Areas

With its bench strength of faculty expertise and student talent, Analytics at Wharton is able and willing to address systemic problems with robust and focused attention, exploring areas like educational disparities, gender and racial inequity, and climate change.

Non-Profit, Government, and Policy

Penn Students Make Impact with Historic Philadelphia Non-Profit

As part of the spring 2022 Analytics Accelerator, a team of Wharton and Penn Engineering students spent six weeks helping the newly merged Philadelphia Orchestra and Kimmel Center, Inc. to identify opportunities to strengthen audience growth and attendance frequency by exploring their combined data. This project sees two world-famous and historic Philadelphia institutions (Wharton was founded in 1881, The Philadelphia Orchestra in 1900), joining forces.

Impact Analytics

Wharton Researchers Build Algorithm to Help Fight Sex Trafficking

January 30, 2023
Impact Analytics

Research Spotlight: Penn Media Accountability Project

November 20, 2022
Impact Analytics

Penn Students Make Impact with Historic Philadelphia Non-Profit

August 30, 2022

Diversity, Equity, and Inclusion

Fourth Annual Women in Data Science @ Penn Conference

The Wharton School and Penn Engineering are proud to host the fourth annual Women in Data Science (WiDS) @ Penn Conference on February 3, 2023. For the first time since the pandemic, attendees will join us on campus for in-person talks showcasing the latest advances in data science, speaker Q&A sessions, and networking opportunities.

A celebrated interdisciplinary event, WiDS @ Penn welcomes academic, industry, and student speakers from across the data science landscape to celebrate its diversity, both in subject matter and personnel.

Impact Analytics

Wharton Researchers Build Algorithm to Help Fight Sex Trafficking

January 30, 2023
Impact Analytics

Opening Doors and Closing Gaps: How Wharton is Creating Access and Equality for Women in Data Science and Analytics

March 7, 2022
Impact Analytics

Wharton Women in Data Science and Analytics

March 6, 2022

Environmental, Social and Governance

Data Analytics for Economic Efficiency in Energy Policy

Analytics at Wharton provides funding to a wide variety of research initiatives. In this research spotlight, we profile Susanna Berkouwer, Assistant Professor of Business Economics and Public Policy, and their research in Data Analytics for Economic Efficiency in Energy Policy.

Impact Analytics

Artificial Intelligence Risk & Governance

November 20, 2022
Impact Analytics

How Can Managers Design Socially Inclusive Strategies?

March 18, 2022
Impact Analytics

Wharton Great Question: Prof. Witold Henisz

November 24, 2021

Skilling and Educational Access

MindCORE Summer Fellowship Program Aims for a More Equitable Neuroscience Future

Penn is making sure that the next generation of neuroscientists will be different. The University has launched a multidisciplinary fellowship to attract more women and people of color to the field, which has lagged behind other sciences in diverse representation. The MindCORE Summer Fellowship is a paid, 10-week program open to Penn and non-Penn undergrads who partner with mentors to embark on a unique research project based on their own interests.

Impact Analytics

Wharton Researchers Build Algorithm to Help Fight Sex Trafficking

January 30, 2023
Impact Analytics

Renée Creppy Combines Passion for Neuroscience and Soccer During MindCORE Summer Fellowship Program

September 21, 2022
Impact Analytics

MindCORE Summer Fellowship Program Aims for a More Equitable Neuroscience Future

September 20, 2022

Funded Projects

The Data Science and Business Analytics Fund supports new opportunities to expand the impact of big data analytics. Drawing on Wharton faculty’s diverse research excellence, these projects transform opportunities using unprecedented volumes of digital, numerical, and text-based data.

Artificial Moral Agents

Amy Sepinwall, Associate Professor of Legal Studies and Business Ethics

This project seeks to gain clarity on whether AI can satisfy the requirements of moral agency and how this impacts corporations.

Building a Nudge Map: A Use Case of Research Cartography to Evolve Social Science

Duncan Watts, Stevens University Professor of Computer and Information Science, Communication, and Operations, Information and Decisions
Linnea Gandhi, Doctoral Candidate, OID

This project seeks to build a map of “nudge” or “choice architecture” interventions, enabling practitioners and academics alike to navigate the theoretical space easily and effectively. The map will be seeded with historical studies and enriched with data from new lab and field experiments to help validate what we, as a field, do and don’t yet “know” about the efficacy of these interventions across contexts.

Data Analytics for Economic Efficiency in Energy Policy

Susanna Berkouwer, Assistant Professor of Business, Economics and Public Policy
Arthur van Benthem, Associate Professor of Business, Economics and Public Policy

This project builds a research portfolio that gathers large data sets from the U.S. and across the world and uses sophisticated econometric tools to analyze this data with the goal of quantifying the inefficiency and unintended consequences from inefficient regulations, and to propose improved energy policy.

The Drivers of Immigrant Hiring

Saerom (Ronnie) Lee, Assistant Professor of Management
Exequiel (Zeke) Hernandez, Associate Professor of Management

Using multiple large-scale datasets on the U.S. labor market, this project will examine the firm-level drivers of hiring immigrant workers.

The Effect of Workplace and Economic Stress on Health Outcomes

Marius Guenzel, Assistant Professor of Finance

The goal of this project is to empirically study the effect of workplace and economic stress on health outcomes including aging and mortality.

Wharton Undergraduate Capstone Course: Federal and State Management of the Pandemic

Robert P. Inman, Richard King Mellon Professor Emeritus of Finance; Professor Emeritus of Business Economics & Public Policy

This project uses data collection for a student-led evaluation of the health and economic consequences of the Covid-19 pandemic and the effectiveness of national and state-wide policy responses to contain the coronavirus and to mitigate its health and economic consequences. The format for this evaluation will be a Capstone Course (BEPP 401) entitled, Federal and State Management of the Pandemic: Money, Messages, Vaccinations, and State Policies.

Measuring the Narratives of the COVID-19 Pandemic

Duncan Watts, Stevens University Professor of Computer and Information Science, Communication, and Operations, Information and Decisions
Baird Howland, PhD Student, Annenberg School of Communication, Computational Social Science Lab at Penn,
Valery Yakubovich, Executive Director, Computational Social Science Lab at Penn

The goal of this project is to study our understanding of the COVID-19 pandemic – the remarkably varied conceptions of what is happening, why it is happening, and what should be done in response, with a rare combination of quantitative rigor and qualitative depth.

Unmasking Sex Trafficking Supply Chains with Machine Learning

Hamsa Bastani, Assistant Professor of Operations, Information, and Decisions
Pia Ramchandani, Doctoral Candidate of Operations, Information, and Decisions

In collaboration with the Tellfinder Alliance for Global Counter-Human Trafficking, this project will leverage unstructured, massive deep web data from leading adult-services websites using a novel machine learning framework to construct the first global network view of sex trafficking supply chains.

Wharton Forensic Analytics Lab Data Case Series

Dan Taylor, Associate Professor of Accounting

This five-part case series will highlight recent accounting frauds (e.g., Wirecard, Luckin Coffee, etc.) and how each of the frauds could have been detected using business analytics.

Applied Neuroscience and Business Analytics Summer Undergraduate Internships for Underrepresented Students

Michael Platt, James S. Riepe University Professor of Marketing, Neuroscience, and Psychology; Faculty Director, Wharton Neuroscience Initiative
Elizabeth Johnson, Executive Director, Wharton Neuroscience Initiative

Wharton Neuroscience Initiative will support two underrepresented undergraduate summer students focused specifically on Applied Neuroscience and Business Analytics for a 10-week summer internship program. These students will be part of a new, larger applied brain and cognitive science summer undergraduate internship program which aims to combat systemic inequalities and a lack of diversity that plague neuroscience, brain and behavioral science, analytics, and data science careers.

Transparency in Police Misconduct Investigations

Dean Knox, Assistant Professor of Operations, Information, and Decisions
Rachel Mariman, Senior Research Project Manager, Analytics at Wharton

Using unique access to archives of administrative records on civilian complaints against police, this experimental study seeks to assess how city residents in Philadelphia, New York, and Chicago understand and perceive the current civilian complaint process, and systematically evaluates the impact of transparency initiatives on civic engagement and public trust in police.

Wharton Undergraduate Capstone Course: Managing the Pandemic Money and Messages

Robert P. Inman, Richard King Mellon Professor Emeritus of Finance; Professor Emeritus of Business Economics & Public Policy

This project uses data collection for a student-led evaluation of the health and economic consequences of the Covid-19 pandemic and the effectiveness of national and state-wide policy responses to contain the coronavirus and to mitigate its health and economic consequences. The format for this evaluation will be a Capstone Course (BEPP 401) entitled, Managing the Pandemic: Messages and Money.

Amenity Value of Green Space

Susan Wachter, Albert Sussman Professor of Real Estate, Professor of Finance
Shane Jensen, Professor of Statistics, Department of Statistics

This project seeks to identify the neighborhood amenity value of transforming blighted and vacant lots into maintained green open space by deploying spatial techniques and integrating multiple data sources to improve our understanding of the dynamics of urban change and identify how residents value “greener” neighborhoods.

Big Data and Analytics in Housing

Benjamin Keys, Rowan Family Foundation Professor; Professor of Real Estate; Professor of Finance
Maisy Wong, James T. Riady Associate Professor of Real Estate; Assistant Director, Grayken Program in International Real Estate at the Zell/Lurie Real Estate Center

This project procures access to the The Corelogic Multiple Listing Services (MLS) database and includes 10 million observations of property listing data, and more than 600 variables that describe listing details. Professor Ben Keys will use the dataset for his research agenda: How is Climate Change Reshaping Housing and Mortgage Markets? Professor Maisy Wong will use the dataset to study the returns to scale of MLS platforms.

Incentivized Resume Rating

Corinne Low, Assistant Professor of Business Economics and Public Policy
Judd B. Kessler, Associate Professor of Business Economics and Public Policy

This project expands upon the recently published paper in American Economic Review, Incentivized Resume Rating: Eliciting Employer Preferences without Deception, by building two platforms to disseminate the research tools and insights from the IRR method targeted at researchers/policymakers and firms.

Wharton Energy Analytics Lab

Edgar Dobriban, Assistant Professor of Statistics
Eric J. Tchetgen Tchetgen, Luddy Family President’s Distinguished Professor, Professor of Statistics
Steven O. Kimbrough, Professor of Operations, Information and Decisions

Wharton Energy Analytics Lab brings to bear cutting-edge applications of machine learning techniques to position Wharton as an undisputed leader in connecting data analytics and energy markets to face societal challenges. The lab will develop research, teaching expertise, knowledge dissemination and outreach efforts to diverse audiences.

Environmental, Social, and Governance Analytics Lab

Witold Henisz, Deloitte & Touche Professor of Management in Honor of Russell E. Palmer, former Managing Partner and Director, Wharton Political Risk Lab

This project focuses on analyzing the materiality of businesses’ environmental, social and governance risks and opportunities and promotes faculty research, teaching, and student learning in this area.

Wharton Forensic Analytics Lab

Daniel Taylor, Associate Professor of Accounting

This project will develop research and teaching expertise on the application of Big Data and predictive analytics to issues related to insider trading, financial irregularities, and fraud. The Lab will aim to create new tools and technologies, academic research, and teaching and educational materials.

Women in Analytics and Data Science Conference

Mary Purk, Executive Director of Wharton Customer Analytics
Linda Zhao, Professor of Statistics

This conference, for Penn students, aims to inspire and educate data scientists, regardless of gender, and support women in analytics and data science-related careers. Planned for February 14, 2020, on Penn’s campus, this event is part of the larger Women in Data Science (WiDS) initiative originated at Stanford in November 2015 and includes a global conference, 150+ regional events, a datathon, and numerous podcasts.

Affiliated Faculty

Affiliated Faculty work on projects funded by Analytics at Wharton to further our mission of delivering analytics education to students, advancing innovative data science and business analytics research, and connecting academia to industry.

Hamsa Bastani
Assistant Professor of Operations, Information and Decisions

Susanna Berkouwer
Assistant Professor of Business Economics and Public Policy

Edgar Dobriban
Assistant Professor of Statistics

Witold Henisz
Deloitte & Touche Professor of Management; Vice Dean and Faculty Director of the ESG Initiative at the Wharton School

Exequiel (Zeke) Hernandez
Associate Professor of Management

Robert P. Inman
Richard King Mellon Professor Emeritus of Finance; Professor Emeritus of Business Economics & Public Policy

Shane Jensen
Professor of Statistics

Benjamin Keys
Rowan Family Foundation Professor, Professor of Real Estate, Professor of Finance

Dean Knox
Assistant Professor of Operations, Information, and Decisions

Saerom (Ronnie) Lee
Assistant Professor of Management

Michael Platt
James S. Riepe University Professor of Marketing, Neuroscience, and Psychology; Faculty Director, Wharton Neuroscience Initiative

Amy Sepinwall
Associate Professor of Legal Studies and Business Ethics

Daniel Taylor
Associate Professor of Accounting

Arthur van Benthem
Associate Professor of Business Economics and Public Policy

Susan Wachter
Albert Sussman Professor of Real Estate; Professor of Finance

Duncan Watts
Stevens University Professor & twenty-third Penn Integrates Knowledge Professor

Maisy Wong
James T. Riady Associate Professor of Real Estate; Assistant Director, Grayken Program in International Real Estate at the Zell/Lurie Real Estate Center

Linda Zhao
Professor of Statistics and Data Science