Filter Results:
(1,557)
Show Results For
- All HBS Web
(1,557)
- News (204)
- Research (1,134)
- Events (16)
- Multimedia (1)
- Faculty Publications (662)
Show Results For
- All HBS Web
(1,557)
- News (204)
- Research (1,134)
- Events (16)
- Multimedia (1)
- Faculty Publications (662)
- 2021
- Working Paper
Invisible Primes: Fintech Lending with Alternative Data
By: Marco Di Maggio, Dimuthu Ratnadiwakara and Don Carmichael
We exploit anonymized administrative data provided by a major fintech platform to investigate whether using alternative data to assess borrowers’ creditworthiness results in broader credit access. Comparing actual outcomes of the fintech platform’s model to... View Details
Keywords: Fintech Lending; Alternative Data; Machine Learning; Algorithm Bias; Finance; Information Technology; Financing and Loans; Analytics and Data Science; Credit
Di Maggio, Marco, Dimuthu Ratnadiwakara, and Don Carmichael. "Invisible Primes: Fintech Lending with Alternative Data." Harvard Business School Working Paper, No. 22-024, October 2021.
- 2020
- Working Paper
An Empirical Guide to Investor-Level Private Equity Data from Preqin
By: Juliane Begenau, Claudia Robles-Garcia, Emil Siriwardane and Lulu Wang
This note provides guidance on the use of investor-level private equity data from Preqin for empirical research. Preqin primarily sources its cash flow data through Freedom of Information Act (FOIA) requests with U.S. public pensions. Our focus is on the components of... View Details
Keywords: Private Equity Returns; Prequin Data; Private Equity; Analytics and Data Science; Investment Return
Begenau, Juliane, Claudia Robles-Garcia, Emil Siriwardane, and Lulu Wang. "An Empirical Guide to Investor-Level Private Equity Data from Preqin." Working Paper, December 2020.
- February 2021
- Tutorial
T-tests: Theory and Practice
This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with... View Details
- Research Summary
Overview
Associate Professor Yael Grushka-Cockayne's research and teaching activities focus on data science, forecasting, project management, and behavioral decision-making. View Details
- February 2019 (Revised August 2019)
- Case
Maccabitech: The Promise of Israel's Healthcare Data
By: Scott Duke Kominers and Carin-Isabel Knoop
Dr. Varda Shalev bridges technology and medicine through Maccabitech, a "research and innovation wing" of Israel's Maccabi Healthcare Services (MHS) that partners with research institutions, pharmaceutical companies, and startups. Shalev hopes to scale Maccabitech's... View Details
Keywords: Big Data; Healthcare; Analytics and Data Science; Digital Platforms; Health Care and Treatment; Innovation and Invention; Research; Entrepreneurship; Risk Management; Israel
Kominers, Scott Duke, and Carin-Isabel Knoop. "Maccabitech: The Promise of Israel's Healthcare Data." Harvard Business School Case 819-032, February 2019. (Revised August 2019.)
- Article
One Obstacle to Curing Cancer: Patient Data Isn't Shared
By: Richard G. Hamermesh and Kathy Giusti
Precision Medicine requires large datasets to identify the mutations that lead to various cancers. Currently, genomic information is hoarded in fragmented silos within numerous academic medical centers, pharmaceutical companies, and some disease-based foundations. For... View Details
Keywords: Healthcare; Technological And Scientific Innovation; Cancer Care In The U.S.; Cancer Treatment; Precision Medicine; Personalized Medicine; Data Sharing; Technological Innovation; Analytics and Data Science; Health Disorders; Medical Specialties; Research and Development; Customization and Personalization; Health Industry; United States
Hamermesh, Richard G., and Kathy Giusti. "One Obstacle to Curing Cancer: Patient Data Isn't Shared." Harvard Business Review (website) (November 28, 2016).
- 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
Keywords: Data Science; Analytics and Data Science; Analysis; Customers; Household; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (B)." Harvard Business School Supplement 119-026, August 2018. (Revised September 2018.)
- March 2022 (Revised January 2025)
- Technical Note
Statistical Inference
This note provides an overview of statistical inference for an introductory data science course. First, the note discusses samples and populations. Next the note describes how to calculate confidence intervals for means and proportions. Then it walks through the logic... View Details
Keywords: Data Science; Statistics; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Statistical Inference." Harvard Business School Technical Note 622-099, March 2022. (Revised January 2025.)
- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
This note describes sampling and t-tests, two fundamental statistical concepts. View Details
Keywords: Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Analytics and Data Science; Analysis; Surveys; Mathematical Methods
Bojinov, Iavor I., Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih, and Michael W. Toffel. "Comparing Two Groups: Sampling and t-Testing." Harvard Business School Technical Note 621-044, August 2020.
- November 2019 (Revised January 2020)
- Case
Bayer Crop Science
By: David E. Bell, Damien McLoughlin, Natalie Kindred and James Barnett
In mid-2019, a year after German conglomerate Bayer Group closed its acquisition of U.S.-based seeds giant Monsanto, the leadership of Bayer’s Crop Science division (which absorbed Monsanto) is reflecting on the opportunities ahead. Some observers have questioned... View Details
Keywords: Agribusiness; Research and Development; Innovation and Invention; Innovation Strategy; Mergers and Acquisitions; Consolidation; Customer Value and Value Chain; Change Management; Agriculture and Agribusiness Industry; Technology Industry; United States; Germany
Bell, David E., Damien McLoughlin, Natalie Kindred, and James Barnett. "Bayer Crop Science." Harvard Business School Case 520-055, November 2019. (Revised January 2020.)
- February 2016 (Revised February 2017)
- Case
The Climate Corporation
By: David E. Bell, Forest Reinhardt and Mary Shelman
Climate Corporation is a San Francisco–based data analytics company focused on agricultural applications. It was acquired by Monsanto in 2013. In 2015, Climate's decision support platform was used on 75 million acres of farmland in the U.S.; however, most of those... View Details
Keywords: Agribusiness Industry; Farming; Big Data; Data Analytics; Agriculture; Agribusiness; Decision Making; Analytics and Data Science; Agriculture and Agribusiness Industry
Bell, David E., Forest Reinhardt, and Mary Shelman. "The Climate Corporation." Harvard Business School Case 516-060, February 2016. (Revised February 2017.)
- 2024
- Working Paper
Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python
By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details
Keywords: Empirical Methods; Empirical Operations; Statistical Methods And Machine Learning; Statistical Interferences; Research Analysts; Analytics and Data Science; Mathematical Methods
Ouellet, Melissa, and Michael W. Toffel. "Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python." Harvard Business School Working Paper, No. 25-010, August 2024.
- January 2025 (Revised March 2025)
- Case
Thomas Müller: Mr. Bayern Munich
By: Boris Groysberg, Sascha L. Schmidt, Alexander Liebhart and Sarah Abbott
In 2024, FC Bayern Munich superstar Thomas Müller announced his retirement from German national football. His contract with Bayern Munich runs through the end of the 2024-25 season. In 2025, Müller reflects on his long career in football, on the skills that have driven... View Details
Keywords: Soccer; Football; Data Science And Analytics Management; Bundesliga; Sports Data; ＂Sports Organizations,; Career Changes And Transitions; Career Management; Retirement Transition; Skills Development; Analysis; Competency and Skills; Decision Making; Performance; Personal Development and Career; Retirement; Transition; Sports Industry; Germany
Groysberg, Boris, Sascha L. Schmidt, Alexander Liebhart, and Sarah Abbott. "Thomas Müller: Mr. Bayern Munich." Harvard Business School Case 425-031, January 2025. (Revised March 2025.)
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation; AI and Machine Learning
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)
- Fall 2012
- Article
How 'Big Data' Is Different
Many people today in the information technology world and in corporate boardrooms are talking about "big data." Many believe that, for companies that get it right, big data will be able to unleash new organizational capabilities and value. But what does the term "big... View Details
Keywords: Big Data; Analytics; Mathematical Methods; Information Management; Information Technology Industry
Davenport, Thomas H., Paul Barth, and Randy Bean. "How 'Big Data' Is Different." MIT Sloan Management Review 54, no. 1 (Fall 2012).
- March 2020
- Article
Diagnosing Missing Always at Random in Multivariate Data
By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin
Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first... View Details
Keywords: Missing Data; Diagnostic Tools; Sensitivity Analysis; Hypothesis Testing; Missing At Random; Row Exchangeability; Analytics and Data Science; Mathematical Methods
Bojinov, Iavor I., Natesh S. Pillai, and Donald B. Rubin. "Diagnosing Missing Always at Random in Multivariate Data." Biometrika 107, no. 1 (March 2020): 246–253.
- August 2015 (Revised May 2017)
- Case
TSG Hoffenheim: Football in the Age of Analytics
By: Feng Zhu, Karim R. Lakhani, Sascha L. Schmidt and Kerry Herman
In 2015, Dietmar Hopp, owner of Germany's Bundesliga football team TSG Hoffenheim and co-founder of the global enterprise software company SAP, was considering how to ensure long-term sustainability and competitiveness for TSG Hoffenheim. While historically a small... View Details
Zhu, Feng, Karim R. Lakhani, Sascha L. Schmidt, and Kerry Herman. "TSG Hoffenheim: Football in the Age of Analytics." Harvard Business School Case 616-010, August 2015. (Revised May 2017.)
- 12 Jul 2010
- Research & Ideas
Rocket Science Retailing: A Practical Guide
The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance (Harvard Business Press). As a practical guide, The New View Details
- April 2020
- Case
Ment.io: Knowledge Analytics for Team Decision Making
By: Yael Grushka-Cockayne, Jeffrey T. Polzer, Susie L. Ma and Shlomi Pasternak
Ment.io was a software platform that used proprietary data analytics technology to help organizations make informed and transparent decisions based on team input. Ment was born out of founder Joab Rosenberg’s frustration that, while organizations collected ever... View Details
Keywords: Decision Making; Information Technology; Knowledge; Knowledge Acquisition; Knowledge Management; Operations; Information Management; Product; Product Development; Entrepreneurship; Business Startups; Communications Industry; Information Industry; Information Technology Industry; Web Services Industry; Middle East; Israel
Grushka-Cockayne, Yael, Jeffrey T. Polzer, Susie L. Ma, and Shlomi Pasternak. "Ment.io: Knowledge Analytics for Team Decision Making." Harvard Business School Case 420-078, April 2020.