Publications
Publications
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- All HBS Web
(1,355)
- Faculty Publications (289)
- 2020
- Working Paper
Machine Learning for Pattern Discovery in Management Research
Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details
- Article
Financial Analysis of Pediatric Resident Physician Primary Care Longitudinal Outpatient Experience
By: Robert S. Kaplan, Carole H. Stipelman, Brad Poss, Laura Anne Stetson, Luca Boi, Michael Rogers, Caleb Puzey, Sri Koduri, Vivian S. Lee and Edward B. Clark
Objective
To determine whether residency training represents a net positive or negative cost to academic medical centers, we analyzed the cost of a residency program and clinical productivity of residents and faculty in an outpatient primary care practice with or... View Details
To determine whether residency training represents a net positive or negative cost to academic medical centers, we analyzed the cost of a residency program and clinical productivity of residents and faculty in an outpatient primary care practice with or... View Details
- August 2018 (Revised September 2018)
- Case
Predicting Purchasing Behavior at PriceMart (A)
By: Srikant M. Datar and Caitlin N. Bowler
This case follows VP of Marketing, Jill Wehunt, and analyst Mark Morse as they tackle a predictive analytics project to increase sales in the Mom & Baby unit of a nationally recognized retailer, PriceMart. Wehunt observed that in the midst of the chaos that surrounded... View Details
- August 2018 (Revised September 2018)
- Supplement
Predicting Purchasing Behavior at PriceMart (B)
By: Srikant M. Datar and Caitlin N. Bowler
Supplements the (A) case. In this case, Wehunt and Morse are concerned about the logistic regression model overfitting to the training data, so they explore two methods for reducing the sensitivity of the model to the data by regularizing the coefficients of the... View Details
- August 2018 (Revised April 2019)
- Case
Chateau Winery (A): Unsupervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case follows Bill Booth, marketing manager of a regional wine distributor, as he applies unsupervised learning on data about his customers’ purchases to better understand their preferences. Specifically, he uses the K-means clustering technique to identify groups... View Details
- August 2018 (Revised April 2019)
- Supplement
Chateau Winery (B): Supervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details
- August 2018 (Revised September 2018)
- Case
LendingClub (A): Data Analytic Thinking (Abridged)
By: Srikant M. Datar and Caitlin N. Bowler
LendingClub was founded in 2006 as an alternative, peer-to-peer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns... View Details
- 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.
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- 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
- July 2018 (Revised June 2020)
- Case
The Boston Cranberry Company
By: Alan MacCormack
This case describes the operations of a fictitious company that processes Cranberries. The case contains data that allows students to calculate the bottleneck stage in production, and to evaluate alternative investment options for increasing cranberry processing... View Details
- 2018
- Simulation
Financial Analysis Simulation: Data Detective
By: Suraj Srinivasan and V.G. Narayanan
In this simulation, students learn to identify typical industry characteristics revealed in financial data. Equipped with an interactive and flexible set of tools, students analyze disguised financials and—using their knowledge of operational practices and reasoning... View Details
- May 2018 (Revised June 2018)
- Case
Cowen Inc.: Leveraging Data
By: Boris Groysberg, Sarah Abbott and Annelena Lobb
Cowen Inc.’s broker-dealer, Cowen and Company, LLC, boasted a number of analysts who had made prescient stock calls on the basis of creative data analysis. Now Cowen Inc. had opened a new subsidiary, Kyber, which would attempt to monetize new data science products.... View Details
- May 2018
- Exercise
Data Visualization & Communication Exercise
By: Srikant M. Datar and Caitlin N. Bowler
This exercise uses the 1986 Challenger shuttle disaster to explore the relationship between data visualization, effective communication, and decision-making. Students review and analyze excerpts from the 13 charts engineers presented to NASA executives the night before... View Details
- March 2018
- Case
TrustSphere: Building a Market for Relationship Analytics
By: Boris Groysberg and Katherine Connolly Baden
Manish Goel was the CEO of TrustSphere, a seven-year-old company in the data analytics industry that focused squarely on relationship analytics, a space in which TrustSphere was pioneering a unique technology and solutions in the areas of sales, risk, and people... View Details
- February 2018 (Revised December 2020)
- Case
People Analytics at Teach For America (A)
By: Jeffrey T. Polzer and Julia Kelley
As of mid-2016, national nonprofit Teach For America (TFA) had struggled with three consecutive years of declining application totals, and senior management was re-examining the organization's strategy, including recruitment and selection. A few months earlier, former... View Details
- February 2018
- Supplement
People Analytics at Teach For America (B)
By: Jeffrey T. Polzer and Julia Kelley
This is a supplement to the People Analytics at Teach For America (A) case. In this supplement, Managing Director Michael Metzger must decide how to extend his team’s predictive analytics work using Natural Language Processing (NLP) techniques. View Details
- February 2018 (Revised June 2021)
- Case
New Constructs: Disrupting Fundamental Analysis with Robo-Analysts
By: Charles C.Y. Wang and Kyle Thomas
This case highlights the business challenges associated with a financial technology firm, New Constructs, that created a technology that can quickly parse complicated public firm financials to paint a clearer economic picture of firms, remove accounting distortions,... View Details
- 2019
- Working Paper
Machine Learning Approaches to Facial and Text Analysis: Discovering CEO Oral Communication Styles
By: Prithwiraj Choudhury, Dan Wang, Natalie A. Carlson and Tarun Khanna
We demonstrate how a novel synthesis of three methods—(1) unsupervised topic modeling of text data to generate new measures of textual variance, (2) sentiment analysis of text data, and (3) supervised ML coding of facial images with a cutting-edge convolutional neural... View Details
- Article
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
By: Seth Neel and Aaron Leon Roth
Data that is gathered adaptively—via bandit algorithms, for example—exhibits bias. This is true both when gathering simple numeric valued data—the empirical means kept track of by stochastic bandit algorithms are biased downwards—and when gathering more complicated... View Details
- November 28, 2017
- Editorial
Active Investing v.2.0
By: Gabriel Karageorgiou and George Serafeim