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- All HBS Web
(1,519)
- News (192)
- Research (1,049)
- Events (20)
- Multimedia (8)
- Faculty Publications (656)
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- February 2021 (Revised February 2021)
- Background Note
eGrocery and the Role of Data for CPG Firms
By: Ayelet Israeli, Fedor (Ted) Lisitsyn and Mark A. Irwin
This notes provides information about the eGrocery industry and how traditional CPG companies handle this channel and potential data. It is recommended to use together with a series of exercises entitled: "E-Commerce Analytics for CPG Firms (A), (B), and (C)." View Details
Keywords: Data; Data Analysis; Data Analytics; Data Sharing; CPG; Consumer Packaged Goods (CPG); Delivery Planning; Customer Lifetime Value; Online Channel; Retail; Retail Analytics; Retailing Industry; Ecommerce; Grocery; Optimization; Analytics and Data Science; Analysis; Customer Value and Value Chain; Marketing Channels; E-commerce; Retail Industry; Consumer Products Industry; United States
Israeli, Ayelet, Fedor (Ted) Lisitsyn, and Mark A. Irwin. "eGrocery and the Role of Data for CPG Firms." Harvard Business School Background Note 521-077, February 2021. (Revised February 2021.)
- April 29, 2014
- Column
Corporate Reporting in the Big Data Era
By: George Serafeim
Advancements in information technology can improve corporate communication with shareholders, but not through incessant data dumps. Instead, companies will more likely be poised for continued success if they use digital platforms for long-term oriented engagement and... View Details
Keywords: Integrated Reporting; Big Data; Corporate Reporting; Sustainability; Corporate Social Responsibility; Corporate Governance; Accounting; Reporting; Organizational Change and Adaptation; Corporate Accountability; Analytics and Data Science; Information Technology; Communication; Financial Reporting; Business and Shareholder Relations
Serafeim, George. "Corporate Reporting in the Big Data Era." IIRC Blog (April 29, 2014).
- Article
Core Earnings: New Data and Evidence
By: Ethan Rouen, Eric C. So and Charles C.Y. Wang
Using a novel dataset, we show that components of firms' GAAP earnings stemming from ancillary business activities or transitory shocks are significant in frequency and magnitude. These components have grown over time and are dispersed across various sections of the... View Details
Keywords: Core Earnings; Transitory Earnings; Non-operating Earnings; Quantitative Disclosures; Equity Valuation; Big Data; Business Earnings; Financial Reporting; Valuation; Analytics and Data Science
Rouen, Ethan, Eric C. So, and Charles C.Y. Wang. "Core Earnings: New Data and Evidence." Journal of Financial Economics 142, no. 3 (December 2021): 1068–1091.
- 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
... View Details
Keywords: Data Science; Data Analytics; Decision Trees; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (B): Decision Trees & Random Forests." Harvard Business School Supplement 119-021, August 2018. (Revised September 2018.)
- October 2020
- Article
The Elasticity of Science
By: Kyle Myers
This paper identifies the degree to which scientists are willing to change the direction of their work in exchange for resources. Data from the National Institutes of Health are used to estimate how scientists respond to targeted funding opportunities. Inducing a... View Details
Myers, Kyle. "The Elasticity of Science." American Economic Journal: Applied Economics 12, no. 4 (October 2020): 103–134.
- August 1997
- Case
Orbital Sciences Corporation: ORBCOMM
By: Das Narayandas and John A. Quelch
In late 1993, Orbital Communications Corp. (OCC), a subsidiary of Orbital Sciences Corp., is developing a global two-way wireless data communications system, called "ORBCOMM," based on a 26-satellite constellation in low earth orbit. Service is scheduled to begin in... View Details
Keywords: Business Subsidiaries; Business Model; Business Startups; Price; Global Strategy; Marketing Strategy; Demand and Consumers; Partners and Partnerships; Salesforce Management; Telecommunications Industry
Narayandas, Das, and John A. Quelch. "Orbital Sciences Corporation: ORBCOMM." Harvard Business School Case 598-027, August 1997.
- Article
Ensembles of Overfit and Overconfident Forecasts
By: Y. Grushka-Cockayne, V.R.R. Jose and K. C. Lichtendahl
Firms today average forecasts collected from multiple experts and models. Because of cognitive biases, strategic incentives, or the structure of machine-learning algorithms, these forecasts are often overfit to sample data and are overconfident. Little is known about... View Details
Grushka-Cockayne, Y., V.R.R. Jose, and K. C. Lichtendahl. "Ensembles of Overfit and Overconfident Forecasts." Management Science 63, no. 4 (April 2017): 1110–1130.
- August 2021
- Case
Precision Paint Co.
Describes a marketing director about to launch a new process for demand forecasting. Provides data that allow students to do a multivariable regression analysis. A rewritten version of an earlier case. View Details
Bojinov, Iavor I., Chiara Farronato, Janice H. Hammond, Michael Parzen, and Paul Hamilton. "Precision Paint Co." Harvard Business School Case 622-055, August 2021.
- December 2017
- Teaching Note
Yemeksepeti: Growing and Expanding the Business Model through Data
By: William R. Kerr and Alexis Brownell
Teaching Note for HBS No. 817-095. 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
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (B): Supervised Learning." Harvard Business School Supplement 119-024, August 2018. (Revised April 2019.)
- March 2022 (Revised January 2025)
- Technical Note
Linear Regression
This note provides an overview of linear regression for an introductory data science course. It begins with a discussion of correlation, and explains why correlation does not necessarily imply causation. The note then describes the method of least squares, and how to... View Details
Keywords: Data Science; Linear Regression; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Linear Regression." Harvard Business School Technical Note 622-100, March 2022. (Revised January 2025.)
- 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).
- June 2022 (Revised January 2025)
- Technical Note
Causal Inference
This note provides an overview of causal inference for an introductory data science course. First, the note discusses observational studies and confounding variables. Next the note describes how randomized experiments can be used to account for the effect of... View Details
Keywords: Causal Inference; Causality; Experiment; Experimental Design; Data Science; Analytics and Data Science
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Causal Inference." Harvard Business School Technical Note 622-111, June 2022. (Revised January 2025.)
- August 2018 (Revised February 2023)
- Case
Hubble Contact Lenses: Data Driven Direct-to-Consumer Marketing
By: Jill Avery and Ayelet Israeli
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 valuation of $200 million and debating... 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; Consumer Behavior; Acquisition; Growth and Development Strategy; Customer Focus and Relationships; Social Media; E-commerce; Analytics and Data Science; Health Industry; Consumer Products Industry; United States; North America; Europe
Avery, Jill, and Ayelet Israeli. "Hubble Contact Lenses: Data Driven Direct-to-Consumer Marketing." Harvard Business School Case 519-011, August 2018. (Revised February 2023.)
- October 2022
- Supplement
Single Earth: Science White Paper Supplement
By: Rembrand Koning and Emer Moloney
Science White Paper prepared by Single.Earth to give an overview of the models and solutions it has developed. View Details
Keywords: Business Startups; Entrepreneurship; Climate Change; Environmental Sustainability; Green Technology; Natural Resources; Pollution; Analytics and Data Science; Marketing; Product Marketing; Product Launch; Product Positioning; Markets; Market Timing; Strategy; Green Technology Industry; Estonia
- July 2022
- Teaching Note
eGrocery and the Role of Data and E-Commerce Analytics for CPG Firms
By: Ayelet Israeli
Teaching Note for HBS Case No. 521-077. View Details
Keywords: Data; Data Analysis; Data Analytics; Data Sharing; CPG; Consumer Packaged Goods (CPG); Delivery Planning; Customer Lifetime Value; Online Channel; Retail; Retail Analytics; Retailing Industry; Ecommerce; Grocery; Optimization; Analytics and Data Science; Analysis; Customer Value and Value Chain; Marketing Channels; E-commerce; Retail Industry; Consumer Products Industry; United States
- 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.
- 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 Science of Retailing helps retailers mine their... View Details
- Spring 2016
- Article
Has Social Science Taken Over Electoral Campaigns and Should We Regret It?
By: Vincent Pons
Pons, Vincent. "Has Social Science Taken Over Electoral Campaigns and Should We Regret It?" French Politics, Culture and Society 34, no. 1 (Spring 2016): 34–47.
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)