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Show Results For
- All HBS Web
(1,557)
- News (205)
- Research (1,122)
- Events (16)
- Multimedia (1)
- Faculty Publications (655)
- 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.
- 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.)
- January 2019 (Revised February 2024)
- Teaching Note
Hubble Contact Lenses: Data Driven Direct-to-Consumer Marketing
By: Ayelet Israeli
Teaching Note for HBS No. 519-011. As its Series A extension round approaches, the founders of Hubble, a subscription-based, social-media fueled, direct-to-consumer (DTC) brand of contact lenses, are reflecting on the marketing strategies that have taken them to a... View Details
Keywords: DTC; Direct To Consumer Marketing; Health Care; Mobile; Attribution; Experimentation; Experiments; Churn/retention; Customer Lifetime Value; Internet Marketing; Big Data; Analytics; A/B Testing; CRM; Advertising; Marketing; Marketing Channels; Marketing Strategy; Media; Brands and Branding; Marketing Communications; Digital Marketing; Acquisition; Growth and Development Strategy; Customer Focus and Relationships; Consumer Behavior; Social Media; E-commerce
- 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.
- 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.
- 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).
- 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
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (A): Unsupervised Learning." Harvard Business School Case 119-023, August 2018. (Revised April 2019.)
- 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.
- 2021
- Chapter
Building Small Business Utopia: How Artificial Intelligence and Big Data Can Increase Small Business Success
By: Karen G. Mills and Annie Dang
Small business lending has remained unchanged for decades, laden with frictions and barriers that prevent many small businesses from accessing the capital they need to succeed. Financial technology, or “fintech,” promises to change this trajectory. In 2010, new fintech... View Details
Keywords: Big Data; Fintech; Artificial Intelligence; Small Business; Financing and Loans; Capital; Success; AI and Machine Learning; Analytics and Data Science
Mills, Karen G., and Annie Dang. "Building Small Business Utopia: How Artificial Intelligence and Big Data Can Increase Small Business Success." In Big Data in Small Business, edited by Carsten Lund Pedersen, Adam Lindgreen, Thomas Ritter, and Torsten Ringberg. Edward Elgar Publishing, 2021.
- 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.)
- 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.)
- 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
- 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.
- 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.)
- 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.)
- 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).
- 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
- July 2023
- Case
HealthVerity: Real World Data and Evidence
By: Satish Tadikonda
Andrew Kress (CEO and founder) and his team had built a promising marketplace business at HealthVerity serving its core market in healthcare, with a focus on pharmaceutical R&D and services. Thus far, HealthVerity’s products had been unique to the pharma and pharma... View Details
Tadikonda, Satish. "HealthVerity: Real World Data and Evidence." Harvard Business School Case 824-019, July 2023.
- 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.)