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Show Results For
- All HBS Web
(6,908)
- News (1,262)
- Research (4,449)
- Events (116)
- Multimedia (73)
- Faculty Publications (3,085)
- September 2020 (Revised July 2022)
- Exercise
Artea (D): Discrimination through Algorithmic Bias in Targeting
By: Eva Ascarza and Ayelet Israeli
This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
Keywords: Targeted Advertising; Discrimination; Algorithmic Data; Bias; Advertising; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Artea (D): Discrimination through Algorithmic Bias in Targeting." Harvard Business School Exercise 521-043, September 2020. (Revised July 2022.)
- July 16, 2015
- Article
How Small Businesses Can Fend Off Hackers
By: Lou Shipley
If you wanted to hack a business, which one would you pick: A Fortune 500 company with a large digital-security budget and a team dedicated to protecting its cyberassets? Or a small enterprise that doesn’t employ a single IT security specialist? Security breaches at... View Details
Keywords: Hack; Data Security; Small Business; Analytics and Data Science; Safety; Information Technology; Cybersecurity
Shipley, Lou. "How Small Businesses Can Fend Off Hackers." Wall Street Journal (July 16, 2015).
- March 2019
- Case
HOPI: Turkey's Shopping Companion
By: Sunil Gupta, Donald Ngwe and Gamze Yucaoglu
The case opens in 2017 as Onur Erbay, CEO of HOPI, a multi-vendor loyalty platform, is contemplating a critical decision. The case chronicles the origins of Boyner Group, the parent company of HOPI and a major retailer in Turkey, and development of retail and customer... View Details
Keywords: Loyalty Programs; Multi-vendor Platform; Retail; Big Data; Customer Relationship Management; Mobile and Wireless Technology; Business Model; Analytics and Data Science; Competitive Strategy; Decision Making; Applications and Software; Digital Platforms; Technology Industry; Retail Industry; Turkey
Gupta, Sunil, Donald Ngwe, and Gamze Yucaoglu. "HOPI: Turkey's Shopping Companion." Harvard Business School Case 519-057, March 2019.
- 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
- April 2013
- Case
Managing with Analytics at Procter & Gamble
By: Thomas H. Davenport, Marco Iansiti and Alain Serels
Senior management at P&G has put a strong emphasis on using data to make "better, smarter, real-time business decisions." The Global Business Services (GBS) organization has developed tools, systems and processes to provide managers throughout P&G with direct access to... View Details
Keywords: Analytics; Data Management; Forecasting; Shared Services; Procter ＆ Gamble; Laundry Detergent; Information Management; Forecasting and Prediction; Information Technology; Mathematical Methods; Consumer Products Industry; North America
Davenport, Thomas H., Marco Iansiti, and Alain Serels. "Managing with Analytics at Procter & Gamble." Harvard Business School Case 613-045, April 2013.
- Article
Uninformed Consent
By: Leslie K. John
Companies want access to more and more of your personal data—from where you are to what’s in your DNA. Can they unlock its value while respecting consumers’ privacy? View Details
Keywords: Personal Data; Privacy; Customers; Analytics and Data Science; Ethics; Governing Rules, Regulations, and Reforms
John, Leslie K. "Uninformed Consent." Special Issue on The Big Idea: Tracked. Harvard Business Review (website) (September–October 2018).
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
- March 2022 (Revised January 2025)
- Technical Note
Linear Regression
By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
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.)
- September 2020 (Revised June 2023)
- Exercise
Artea: Designing Targeting Strategies
By: Eva Ascarza and Ayelet Israeli
This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details
Keywords: Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; ＂Marketing Analytics＂; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analytics; Data Analysis; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Targeting; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Algorithmic Bias; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Artea: Designing Targeting Strategies." Harvard Business School Exercise 521-021, September 2020. (Revised June 2023.)
- 2022
- Book
The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI
By: Paul Leonardi and Tsedal Neeley
The pressure to "be digital" has never been greater, but you can meet the challenge.
The digital revolution is here, changing how work gets done, how industries are structured, and how people from all walks of life work, behave, and relate to each other. To thrive... View Details
Keywords: Digital; Artificial Intelligence; Big Data; Digital Transformation; Technological Innovation; Transformation; Learning; Competency and Skills
Leonardi, Paul, and Tsedal Neeley. The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI. Boston, MA: Harvard Business Review Press, 2022.
- June 2018 (Revised June 2018)
- Case
Facebook Confronts a Crisis of Trust
By: William W. George and Amram Migdal
The case, “Facebook Confronts a Crisis of Trust,” starts with the crisis Facebook founder and CEO Mark Zuckerberg is facing in March 2018 over Cambridge Analytica’s accessing data from 87 million Facebook accounts in order to influence the 2016 U.S. Presidential... View Details
Keywords: Facebook; Data Privacy; Data Manipulation; Data Science; Political Campaigns; Political Influence; Voter Mobilization; Voters' Interests; Election Outcomes; Elections; Cambridge Analytica; Mark Zuckerberg; Sheryl Sandberg; Voting; Decision Making; Demographics; Ethics; Geopolitical Units; Government and Politics; Government Legislation; National Security; Political Elections; Information Management; Leadership; Leadership Style; Crisis Management; Social Psychology; Personal Characteristics; Power and Influence; Society; Public Opinion; Technology Industry; United States; United Kingdom
George, William W., and Amram Migdal. "Facebook Confronts a Crisis of Trust." Harvard Business School Case 318-145, June 2018. (Revised June 2018.)
- December 2020
- Supplement
VIA Science (B)
By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (B)." Harvard Business School Supplement 721-368, December 2020.
- August 2022
- Supplement
Zalora: Data-Driven Pricing Recommendations
By: Ayelet Israeli
This exercise can be used in conjunction with the main case "Zalora: Data-Driven Pricing" to facilitate class discussion without requiring data analysis from the students. Instead, the exercise presents reports that were created by the data science team to answer the... View Details
Keywords: Pricing; Pricing Algorithms; Dynamic Pricing; Ecommerce; Pricing Strategy; Pricing And Revenue Management; Apparel; Singapore; Startup; Demand Estimation; Data Analysis; Data Analytics; Exercise; Price; Internet and the Web; Apparel and Accessories Industry; Retail Industry; Fashion Industry; Singapore
Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
- January 2023
- Supplement
Apple: Privacy vs. Safety (B)
By: Henry McGee, Nien-hê Hsieh and Christian Godwin
In 2020, as the COVID-19 pandemic swept across the globe, Apple and Google partnered to develop a contact tracing application that would collect information about users infected with the disease and notify those who they had been in contact with. While Apple/Google’s... View Details
Keywords: Iphone; Encryption; Data Privacy; Customers; Customer Focus and Relationships; Decision Making; Ethics; Values and Beliefs; Globalized Firms and Management; Government and Politics; Health; Health Pandemics; Leadership; Markets; Safety; Social Issues; Information Technology; Telecommunications Industry; Technology Industry; Consumer Products Industry; Electronics Industry; Health Industry; United States; Europe
McGee, Henry, Nien-hê Hsieh, and Christian Godwin. "Apple: Privacy vs. Safety (B)." Harvard Business School Supplement 323-066, January 2023.
- June 2022 (Revised January 2025)
- Technical Note
Causal Inference
By: Iavor I Bojinov, Michael Parzen and Paul Hamilton
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.)
- January 2020
- Case
Banorte Móvil: Data-Driven Mobile Growth
By: Ayelet Israeli, Carla Larangeira and Mariana Cal
In mid-2019, Carlos Hank was deliberating over the results for Banorte Móvil—the mobile application for Banorte, Mexico’s most profitable and second-largest financial institution. Hank, who had been appointed as Banorte´s Chairman of the Board in January 2015, had... View Details
Keywords: Data Analytics; Customer Lifetime Value; Financial Institutions; Mobile and Wireless Technology; Growth and Development Strategy; Customers; Technology Adoption; Communication Strategy; Banking Industry; Mexico; Latin America
Israeli, Ayelet, Carla Larangeira, and Mariana Cal. "Banorte Móvil: Data-Driven Mobile Growth." Harvard Business School Case 520-068, January 2020.
- 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.)
- August 2020
- Article
The Tradeoffs Between Safety and Alert Fatigue: Data from a National Evaluation of Hospital Medication-related Clinical Decision Support
By: Zoe Co, A Jay Holmgren, David C Classen, Lisa P Newmark, Diane Seger, Melissa Danforth and David W Bates
Co, Zoe, A Jay Holmgren, David C Classen, Lisa P Newmark, Diane Seger, Melissa Danforth, and David W Bates. "The Tradeoffs Between Safety and Alert Fatigue: Data from a National Evaluation of Hospital Medication-related Clinical Decision Support." Journal of the American Medical Informatics Association 27, no. 8 (August 2020): 1252–1258.