2021 Wharton Annual Analytics Conference Recap
In partnership with Analytics at Wharton, AIAB hosted the Annual Analytics Conference virtually on May 3-7, 2021. Industry leaders – including keynote speaker Jamie Moldafsky, WG’89, Chief Marketing and Communications Officer of Nielsen – spoke about the latest trends in business analytics, data science, and AI.
More than 540 business professionals, academics, and members of the Penn community registered for this week-long virtual event. Many tuned in for live talks and technical workshops that emphasized, with the right tools and strategic vision, data-focused professionals can move from siloed analytics to impactful action.
Data and Analytics as a Source of Truth and a Force for Good
Advertising, like any other form of content, has the ability to change people. That is its primary purpose; to impact hearts and minds. Its messages are meant to reach consumer segments that inspire audiences to take action.
Keynote speaker, Jamie Moldafsky, Chief Marketing and Communications Officer at Nielsen, discusses the moral imperative to use data and analytics as a force for good, and ultimately, systemic change.
Analytics Is a Team Sport
Why Did It Take so Long to Adopt the 3-point Shot?
What It’s Like Working with MBA Coaches on an Analytics Strategy
Daryl Morey serves as the President of Basketball Operations for the Philadelphia 76ers, joining the organization in the summer of 2020 after 14 seasons with the Houston Rockets. In his prolific career leading NBA teams, Daryl has utilized analytics to recruit talent and maximize player and team performance. In a live Q&A session moderated by Adi Wyner, Faculty Lead, Wharton Sports Analytics and Business Initiative, Daryl answered questions from the audience about how he uses analytics to create impact on and off the court.
Lessons Learned from AI in Enterprise
Over the next decade, every company will be transformed by AI. In this presentation, Rajen will explore some of the most prominent use cases and challenges with implementing AI in enterprise. Also, he will go over the key lessons learned in implementing AI and provide examples.
Fairness in AI – Lessons from Practice
Pymetrics helps companies build the workforce of the future, using behavioral science and audited AI technology. Dr. Vaughan will discuss their efforts to deploy machine learning at scale, with a particular focus on their efforts towards diversity, fairness, accountability, and transparency. Lastly, he will discuss the road ahead for fairness in the AI space, with learnings derived from the many challenges (and benefits) of their efforts deploying AI in a regulated environment.
Q&A with Elizabeth (Zab) Johnson
Following their talks, Elizabeth (Zab) Johnson, Executive Director and Senior Fellow at Wharton Neuroscience Initiative, moderated a live Q&A session with Rajen Sheth, VP of Google Cloud AI and Industry Solutions, and Alex Vaughan, Chief Scientific Officer at Pymetrics, about lessons learned from implementing AI in enterprise and using AI to facilitate fair hiring practices.
Marketing at Scale: How Microsoft Uses the Cloud and Analytics to Discover Powerful Insights
In this session, you will learn about Azure and how the Microsoft marketing team turns ideas into solutions by leveraging the Azure products and services. You’ll learn the basics of Azure storage, Azure Synapse, and Azure Purview for data governance as well as how to use those services to power your immediate BI and machine learning needs.
The Art & Science of A/B Testing for Business Decisions
Can you make business decisions with the certainty of a scientist? That is the promise of A/B testing, which is a well-established but increasingly popular business practice based on using randomized controlled experiments for managerial decisions. But where exactly does this supposed science fit into the art of running a business? In this workshop, we will use a mix of lecture, discussion, and interactive simulations to introduce both core concepts and modern developments in the practice of A/B testing.
What Do We Know and Do We Actually Know It: Using Federal Economic Data for Policy Analysis
This workshop will review several key federal data sources from an applied perspective, discussing how (and whether) policymakers and the public can use the data to guide decisions, especially in a crisis. It will cover the data underlying forecasts of revenue and the effects of tax changes, headline indicators for the economy like GDP and unemployment, real-time measurement of behavior and economic activity during the COVID-19 pandemic, and other topics.
Integrating Data in Teradata Vantage – A Case Study on Delivering Business Insights During COVID-19
In this 90-minute workshop, you will explore first-hand Teradata’s Resiliency Dashboard, a business-centric, execution-focused tool designed to help companies navigate during the pandemic and beyond. Teradata explains how integrated diverse data sets from this dashboard can jump start modeling efforts to inform business decisions. Participants will walk away with several real-time case study implementations and novel ideas for utilizing data to gain insights into their own organizations.
The Importance of Cultural and Social Intersections to Data Analytics
Following the endnote address with Sue Taylor, CIO of the Bill and Melinda Gates Foundation, Wharton professors Eric Bradlow, Stephanie Creary, and Katherine Klein discussed the crucial role data analytics plays in integrating diversity, equity, and inclusion into our organizations and society at large.
One week of live programming was not enough time to showcase the breadth and depth of Analytics at Wharton. So, we curated research, thought leadership, and projects from our programs and labs that demonstrate the real-world impact of analytics on an organization’s strategic decision-making.
Women in Data Science @ Penn
The University of Pennsylvania was proud to host the second annual (first virtual) Women in Data Science (WiDS) @ Penn Conference on February 8-12, 2021. Over the course of the week, nearly 500 registrants had access to academic and industry talks, live speaker Q&A sessions, and networking opportunities in our virtual Gather.Town conference space.
This year’s theme – This is What a Data Scientist Looks Like – emphasized the depth, breadth, and diversity of data science, both in subject matter and personnel. A celebrated interdisciplinary event, WiDS @ Penn welcomed academic and industry speakers from across the data science landscape.
Incentivized Resume Rating
A new tool to study what employers value in hiring, and work to eliminate bias.
Environmental, Social, and Governance Analytics Lab
The ESG Analytics Lab focuses on developing high-quality, replicable academic research and pedagogy resulting in insights that can help current and future investors, asset managers and other ESG integrators make informed decisions.
Every fall and spring semester, AI and Analytics for Business hosts the Analytics Accelerator, an experiential learning program that pairs students with a company to solve a real-world business problem using the company’s actual datasets and the latest techniques including machine learning and AI.
Computational Social Science
Learning from Contaminated Data: Insights from Racial Bias in Police-Civilian Contact
Analyzing datasets of convenience can lead to severely mistaken conclusions when analysts fail to account for selection in how they have obtained the data. Drawing on recent controversies in the study of racial bias in policing, we examine solutions ranging from proxy variables to debiasing corrections.
Real News, Fake News, and No News at All: A Data-Driven View of the Information Ecosystem
“Fake news,” broadly defined as false or misleading information masquerading as legitimate news, is frequently asserted to be pervasive online with serious consequences for democracy. Using a unique multimode dataset that comprises a nationally representative sample of mobile, desktop, and television consumption, we refute this conventional wisdom.
Wharton Financial Analytics
Project North Star
North Star is an AI program that benchmarks companies against publicly traded firms and provides guidance on achieving growth and profitability objectives. Using financial data spanning the last century, North Star provides projected KPI paths against which firms can compare themselves to quantify progress.
Wharton Neuroscience Initiative
Decomposing Loss Aversion from Gaze Allocation and Pupil Dilation
The direction in which people look and how dilated their pupils get can reveal the decision they’re about to make. Feng Sheng discusses how his recently proposed computational model with eye-tracking and pupillometry provides a framework for this decision process.
Wharton People Analytics
Back to Basics: 5 Techniques to Make the Most of Your People Data
In this tour de force presentation, Andrea Jones-Rooy, Director of the NYU Center for Data Science, explains why your data and the fancy techniques you use on it are not as good as you think they are…and why the humble histogram might be worth more than 1000 lines of code.
Can Algorithms Be Fair?
With algorithms all but certain to take on a larger role in our organizations, we asked technology journalist extraordinaire Kara Swisher to lead MIT research scientist Andy McAfee and Stanford A.I. ethics expert Elizabeth Adams in a debate about what fair algorithms could and should look like over the coming decade.
Wharton Research Data Services
WRDS Text Analysis
Wharton Research Data Services (WRDS) provides the leading business intelligence, data analytics, and research platform to academic, government, and commercial institutions — enabling comprehensive thought leadership, historical analysis, and insight into the latest innovations in research.
Wharton Sports Analytics and Business Initiative
Check the Tape-He’s Wide oPenn: Target-Agnostic Evaluation of CBs & WRs
A student research project focused on creating a relative skill rating system based upon success in coverage matchups to measure defender skill. Guidance provided by WSABI faculty co-leads Cade Massey and Adi Wyner.
Wharton Forensic Analytics Lab
WFA has a three‐part mission, focused broadly on the application of academic research to practice and education: (1) create and disseminate new tools and technologies to academics and private sector partners; (2) create and disseminate academic research to media, practitioners, and regulators; and (3) create and disseminate teaching and educational materials to academics and current and prospective students.
Markets in Motion
The pandemic-induced recession is the tipping point that is forcing businesses to accelerate the digital transformation of their commercial models. New research from The Wharton School, in collaboration with Forbes, confirms business leaders are shifting their budgets and management focus in digital channels to gain access to buyers, support virtual selling, and replace traffic and eyeballs from face-to-face trade shows, events, and storefronts.
As a continuation of their recently published white paper, “The Markets in Motion Study: What Every CMO Needs to Know to Make Marketing Decisions During The Covid-19 Recession,” Wharton professors David Reibstein and Raghu Iyengar have conducted over 20 interviews with business leaders in a series that examines how companies are pivoting their business strategies and innovating in a time of disruption due to the COVID-19 pandemic.