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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

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

Article

Four Things No One Will Tell You About ESG Data

By: Sakis Kotsantonis and George Serafeim

As the ESG finance field and the use of ESG data in investment decision-making continue to grow, the authors seek to shed light on several important aspects of ESG measurement and data. This article is intended to provide a useful guide for the rapidly rising number of... View Details

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Research Summary

Reforming Social Science

By: Max H. Bazerman

Social science research affects all of us. When researchers learned organ donation rates are higher in countries where human organs are automatically available for donation unless you specifically “opt-out” of the system, as opposed to countries like the U.S., where... View Details

March 2022 (Revised January 2025)
Technical Note

Prediction & Machine Learning

By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton

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

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

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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

March 2022 (Revised January 2025)
Technical Note

Statistical Inference

By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton

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

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

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

Keywords: by Martha Lagace; Retail; Auto

August 2020
Technical Note

Comparing Two Groups: Sampling and t-Testing

By: Iavor I Bojinov, Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih and Michael W. Toffel

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

September 2016 (Revised May 2018)
Case

Zurich Insurance: Global Job Structure and Data Analysis

By: Boris Groysberg and Katherine Connolly

Zurich Insurance was undergoing organizational change after implementing five new people practices focused on manager development, diversity and inclusion, job model and data analytics, recruitment, and talent pipeline. The case “Zurich Insurance: Fostering Key People... View Details

Keywords: Managing Change; Organizational Behavior; Organizational Architecture; Organizational Change and Adaptation; Leadership; Human Capital; Change Management; Organizational Structure; Insurance; Organizational Culture; Globalization; Human Resources; Insurance Industry

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

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

May 1983 (Revised December 1987)
Case

Technical Data Corp.

By: William A. Sahlman

Describes a decision confronting the president of a small company about selling some or all of the shares in his company to another firm. Technical Data Corp. provides analytical services to professional bond market traders over a system of computer terminals operated... View Details

Keywords: Stocks; Entrepreneurship; Business Startups; Internet and the Web; Information Infrastructure; Mobile and Wireless Technology; Valuation; Negotiation Tactics; Mergers and Acquisitions; Corporate Strategy; Horizontal Integration; Information Industry; Service Industry

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

Keywords: Analytics and Data Science; Forecasting and Prediction; Recruitment; Analysis

Article

Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications

By: Daniel Elsner, Pouya Aleatrati Khosroshahi, Alan MacCormack and Robert Lagerström

Existing application performance management (APM) solutions lack robust anomaly detection capabilities and root cause analysis techniques that do not require manual efforts and domain knowledge. In this paper, we develop a density-based unsupervised machine learning... View Details

Keywords: Big Data; Data Science And Analytics Management; Governance And Compliance; Organizational Systems And Technology; Anomaly Detection; Application Performance Management; Machine Learning; Enterprise Architecture; Analytics and Data Science

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

Keywords: Information Technology; Measurement and Metrics; Sports; Sports Industry

2023
Chapter

Marketing Through the Machine’s Eyes: Image Analytics and Interpretability

By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan

he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details

Keywords: Transparency; Marketing Research; Algorithmic Bias; AI and Machine Learning; Marketing

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

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