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February 2013
Case

Recorded Future: Analyzing Internet Ideas About What Comes Next

Recorded Future is a "big data" startup company that uses Internet data to make predictions about events, people, and entities. The company primarily serves government intelligence agencies, but has some private sector clients and is considering taking on more. The... View Details

Keywords: Big Data; Analytics; Internet; Analytics and Data Science; Internet and the Web; Entrepreneurship; Forecasting and Prediction; Business Startups; Information Technology Industry

January 2021 (Revised March 2021)
Case

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Jill Avery, Ayelet Israeli and Emma von Maur

THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details

Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States

February 2017 (Revised June 2017)
Supplement

ExxonMobil: Business as Usual? (B)

By: George Serafeim, Shiva Rajgopal and David Freiberg

The case presents ExxonMobil's response to growing pressure to disclose how climate change will impact their business. This includes multiple asset impairments and losing a proxy vote to shareholders to increase climate change related reporting. Supplements the (B)... View Details

Keywords: Oil ＆ Gas; Oil Prices; Oil Companies; Asset Impairment; Predictive Analytics; Sustainability; Environmental Impact; Innovation; Disclosure; Accounting; Valuation; Energy Sources; Ethics; Corporate Disclosure; Governance Compliance; Climate Change; Financial Reporting; Energy Industry; United States

Teaching Interest

Overview

Paul is primarily interested in teaching data science to management students through the case method. This includes technical topics (programming and statistics) as well as higher-level management issues (digital transformation, data governance, etc.) As a research... View Details

Keywords: A/B Testing; AI; AI Algorithms; AI Creativity; Algorithm; Algorithm Bias; Algorithmic Bias; Algorithmic Fairness; Algorithms; Analytics; Application Program Interface; Artificial Intelligence; Causality; Causal Inference; Computing; Computers; Data Analysis; Data Analytics; Data Architecture; Data As A Service; Data Centers; Data Governance; Data Labeling; Data Management; Data Manipulation; Data Mining; Data Ownership; Data Privacy; Data Protection; Data Science; Data Science And Analytics Management; Data Scientists; Data Security; Data Sharing; Data Strategy; Data Visualization; Database; Data-driven Decision-making; Data-driven Management; Data-driven Operations; Datathon; Economics Of AI; Economics Of Innovation; Economics Of Information System; Economics Of Science; Forecast; Forecast Accuracy; Forecasting; Forecasting And Prediction; Information Technology; Machine Learning; Machine Learning Models; Prediction; Prediction Error; Predictive Analytics; Predictive Models; Analysis; AI and Machine Learning; Analytics and Data Science; Applications and Software; Digital Transformation; Information Management; Digital Strategy; Technology Adoption

August 2018 (Revised September 2018)
Supplement

LendingClub (C): Gradient Boosting & Payoff Matrix

By: Srikant M. Datar and Caitlin N. Bowler

This case builds directly on the LendingClub (A) and (B) cases. In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default... View Details

Keywords: Data Analytics; Data Science; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction

May 2021 (Revised February 2024)
Teaching Note

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Ayelet Israeli and Jill Avery

THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details

Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States

August 2015 (Revised January 2017)
Technical Note

From Correlation to Causation

By: Feng Zhu and Karim R. Lakhani

To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes... View Details

Keywords: Statistics; Regression; Data Analytics; Decisions; Forecasting and Prediction; Judgments

August 2018 (Revised September 2018)
Supplement

LendingClub (B): Decision Trees & Random Forests

By: Srikant M. Datar and Caitlin N. Bowler

This case builds directly on the LendingClub (A) case. In this case students follow Emily Figel as she builds two tree-based models using historical LendingClub data to predict, with some probability, whether borrower will repay or default on his loan.
... View Details

Keywords: Data Science; Data Analytics; Decision Trees; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction

Research Summary

Overview

By: Kris Johnson Ferreira

Professor Ferreira's research primarily focuses on how retailers can use algorithms to make better revenue management decisions, including pricing, product display, and assortment planning. In the retail industry, anticipating consumer demand is arguably one of the... View Details

Keywords: E-commerce; Analytics; Revenue Management; Pricing; Assortment Planning; Field Experiments; Operations; Supply Chain; Supply Chain Management; Retail Industry

October 2022 (Revised December 2022)
Case

SMART: AI and Machine Learning for Wildlife Conservation

By: Brian Trelstad and Bonnie Yining Cao

Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife... View Details

Keywords: Business and Government Relations; Emerging Markets; Technology Adoption; Strategy; Management; Ethics; Social Enterprise; AI and Machine Learning; Analytics and Data Science; Natural Environment; Technology Industry; Cambodia; United States; Africa

14 Mar 2023
Cold Call Podcast

Can AI and Machine Learning Help Park Rangers Prevent Poaching?

Keywords: Re: Brian L. Trelstad; Computer; Information Technology; Technology

October 2017 (Revised April 2018)
Case

Improving Worker Safety in the Era of Machine Learning (A)

By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson

Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details

Keywords: Machine Learning; Policy Implementation; Empirical Research; Inspection; Occupational Safety; Occupational Health; Regulation; Analysis; Forecasting and Prediction; Policy; Operations; Supply Chain Management; Safety; Manufacturing Industry; Construction Industry; United States

October 2016 (Revised April 2018)
Case

DataXu: Selling Ad Tech

By: Frank V. Cespedes, John Deighton, Lisa Cox and Olivia Hull

DataXu served marketers by buying digital advertising for brands using its demand-side platform. It sought a way to build a more predictable revenue stream in the very transactional media marketplace, and hoped that two new marketing analytics products would give it a... View Details

Keywords: Sales Management; Pricing; Programmatic Ad Buying; ＂Marketing Analytics＂; Advertising Technology; Sales; Digital Marketing; Marketing Strategy; Advertising Campaigns; Product Launch; Product Positioning; Media; Technology Industry; Advertising Industry; Boston; Massachusetts

22 Oct 2019
Research & Ideas

Use Artificial Intelligence to Set Sales Targets That Motivate

advanced analytics that incorporate artificial intelligence (AI). “Chung has seen companies dramatically improve productivity after adopting advanced analytics to guide compensation.” In an ideal world, a... View Details

Keywords: by Michael Blanding

October 2010
Article

Culture Clash: The Costs and Benefits of Homogeneity

By: Eric Van den Steen

This paper develops an economic theory of the costs and benefits of corporate culture-in the sense of shared beliefs and values in order to study the effects of "culture clash" in mergers and acquisitions. I first use a simple analytical framework to show that shared... View Details

Keywords: Cost vs Benefits; Organizational Culture; Economics; Information Management; Forecasting and Prediction; Values and Beliefs; Mergers and Acquisitions; Framework; Satisfaction; Motivation and Incentives; Power and Influence; Communication

Find at Harvard

2009
Working Paper

Culture Clash: The Costs and Benefits of Homogeneity

By: Eric J. Van den Steen

This paper develops an economic theory of the costs and benefits of corporate culture—in the sense of shared beliefs and values—in order to study the effects of "culture clash" in mergers and acquisitions. I first use a simple analytical framework to show that shared... View Details

Keywords: Mergers and Acquisitions; Cost vs Benefits; Values and Beliefs; Organizational Change and Adaptation; Organizational Culture; Motivation and Incentives; Theory

21 Jul 2008
Research & Ideas

Solving the Marketing Resources Allocation Puzzle

managers are being held to higher standards when it comes to justifying customer investments. We foresee the need for marketing professionals to develop even greater analytical skill as the field continues to evolve. This should be a very... View Details

Keywords: by Sean Silverthorne

October 2013
Article

How Much to Make and How Much to Buy? An Analysis of Optimal Plural Sourcing Strategies

By: Phanish Puranam, Ranjay Gulati and Sourav Bhattacharya

While many theories of the firm seek to explain when firms make rather than buy, in practice, firms often make and buy the same input—they engage in plural sourcing. We argue that explaining the mix of external procurement and internal sourcing for the same input... View Details

Keywords: Supply Chain; Forecasting and Prediction; Framework; Prejudice and Bias; Mathematical Methods

Find at Harvard

September 2020 (Revised September 2021)
Case

Student Success at Georgia State University (A)

By: Michael W. Toffel, Robin Mendelson and Julia Kelley

Georgia State University had developed a reputation for driving student success by nearly doubling its graduation rate for students of all racial, ethnic, and socioeconomic backgrounds. It did so while growing its student body and the proportion of Black/African... View Details

March 2021 (Revised January 2022)
Case

Philips: Redefining Telehealth

By: Regina E. Herzlinger, Alec Petersen, Natalie Kindred and Sara M. McKinley

As one of the world’s largest healthcare companies, Philips sought to reach beyond the walls of the hospital and expand its hospital-to-home program to gain future competitive advantage through technology solutions combining predictive analytics with care delivery. By... View Details

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