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Show Results For
- All HBS Web
(1,184)
- People (1)
- News (421)
- Research (661)
- Events (6)
- Multimedia (7)
- Faculty Publications (211)
- 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
Elsner, Daniel, Pouya Aleatrati Khosroshahi, Alan MacCormack, and Robert Lagerström. "Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications." Proceedings of the Hawaii International Conference on System Sciences 52nd (2019): 5827–5836.
- October 2015 (Revised October 2016)
- Case
Building Watson: Not So Elementary, My Dear! (Abridged)
By: Willy C. Shih
This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the... View Details
Keywords: Analytics; Big Data; Business Analytics; Product Development Strategy; Machine Learning; Machine Intelligence; Artificial Intelligence; Product Development; AI and Machine Learning; Information Technology; Analytics and Data Science; Information Technology Industry; United States
Shih, Willy C. "Building Watson: Not So Elementary, My Dear! (Abridged)." Harvard Business School Case 616-025, October 2015. (Revised October 2016.)
- 07 Mar 2023
- HBS Case
ChatGPT: Did Big Tech Set Up the World for an AI Bias Disaster?
company, Google CEO Sundar Pichai issued an apology. Learning from Google’s mistakes The takeaways from Gebru’s story are hardly singular to Google as Big Tech scrambles to build ever-larger AI data sets... View Details
- 2021
- Working Paper
The Value of Descriptive Analytics: Evidence from Online Retailers
By: Ron Berman and Ayelet Israeli
Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we find an... View Details
Keywords: Descriptive Analytics; Big Data; Synthetic Control; E-commerce; Online Retail; Difference-in-differences; Martech; Internet and the Web; Analytics and Data Science; Performance; Retail Industry
Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Harvard Business School Working Paper, No. 21-067, November 2020. (Revised December 2021. Accepted at Marketing Science.)
- 2012
- Book
Judgment Calls: Twelve Stories of Big Decisions and the Teams That Got Them Right
By: Thomas H. Davenport and Brook Manville
This book includes twelve detailed stories of organizations that have successfully tapped their data assets, diverse perspectives, and deep knowledge to build an organizational decision-making capability. The book introduces a model that utilizes the collective... View Details
Keywords: Organizational Judgment; Decision-making; Decisions; Organizational Structure; Business Processes
Davenport, Thomas H., and Brook Manville. Judgment Calls: Twelve Stories of Big Decisions and the Teams That Got Them Right. Harvard Business Review Press, 2012. (Publisher's Weekly Top 10 Business Book of 2012.)
- 10 May 2022
- Research & Ideas
Being Your Own Boss Can Pay Off, but Not Always with Big Pay
self-employment incomes in both high and low capital industries are falling sharply compared with the wages that organizations pay workers, according to the researchers. Their data came from a number of sources, including US Census and... View Details
Keywords: by Jay Fitzgerald
- Article
Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error
By: Celia Cintas, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan and Edward McFowland III
Reliably detecting attacks in a given set of inputs is of high practical relevance because of the vulnerability of neural networks to adversarial examples. These altered inputs create a security risk in applications with real-world consequences, such as self-driving... View Details
Keywords: Autoencoder Networks; Pattern Detection; Subset Scanning; Computer Vision; Statistical Methods And Machine Learning; Machine Learning; Deep Learning; Data Mining; Big Data; Large-scale Systems; Mathematical Methods; Analytics and Data Science
Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks via Subset Scanning of Autoencoder Activations and Reconstruction Error." Proceedings of the International Joint Conference on Artificial Intelligence 29th (2020).
- January 2019 (Revised October 2019)
- Case
Glossier: Co-Creating a Cult Brand with a Digital Community
By: Jill Avery
Glossier’s proclaimed strategy was “born from content; fueled by community.” The digital-first, direct-to-consumer beauty brand had experienced rapid growth, with sales up 600% in 2017 and a customer portfolio that grew by threefold. But, its founder, Emily Weiss, was... View Details
Keywords: Brands; Brand Management; Brand Communication; Retailing; DTC; Influencer; Startup; Internet Marketing; Big Data; Crowdsourcing; Growth and Development Strategy; Social Media; E-commerce; Internet and the Web; Digital Marketing; Consumer Products Industry; Beauty and Cosmetics Industry; Retail Industry; United States; North America
Avery, Jill. "Glossier: Co-Creating a Cult Brand with a Digital Community." Harvard Business School Case 519-022, January 2019. (Revised October 2019.)
- August 2015 (Revised February 2017)
- Case
Bridj and the Business of Urban Mobility (A): Developing a New Model
By: Rosabeth Moss Kanter and Daniel Fox
Bridj, a Boston startup that provides Big Data-powered, "pop-up" bus routes that respond to transportation demand, has been in operation for a little over a year and has recently launched service in Washington, D.C., its second market. Despite media acclaim and... View Details
Keywords: Startup; Startup Management; Big Data; Smart Transit; Stakeholder Engagement; Stakeholder Management; Urban Vehicle; Mobility; Mass Transit; Uber; Government Relations; Technological Innovation; Analytics and Data Science; Entrepreneurship; Business and Stakeholder Relations; Transportation; Business Startups; Management; Business and Government Relations; Transportation Industry; Boston; District of Columbia
Kanter, Rosabeth Moss, and Daniel Fox. "Bridj and the Business of Urban Mobility (A): Developing a New Model." Harvard Business School Case 316-025, August 2015. (Revised February 2017.)
- 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).
- 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.)
- Spring 2016
- Article
The Billion Prices Project: Using Online Prices for Inflation Measurement and Research
By: Alberto Cavallo and Roberto Rigobon
New data-gathering techniques, often referred to as “Big Data” have the potential to improve statistics and empirical research in economics. In this paper we describe our work with online data at the Billion Prices Project at MIT and discuss key lessons for both... View Details
Keywords: Billion Prices Project; Online Scraped Data; Online Price Index; Economics; Research; Price; Analytics and Data Science
Cavallo, Alberto, and Roberto Rigobon. "The Billion Prices Project: Using Online Prices for Inflation Measurement and Research." Journal of Economic Perspectives 30, no. 2 (Spring 2016): 151–178.
- Teaching Interest
Overview
By: John A. Deighton
I teach about the ecosystem of big data, the role of data in advertising and creative industries, and customer management and personal privacy in an era of individual addressability. View Details
- September 2020 (Revised July 2022)
- Technical Note
Algorithmic Bias in Marketing
By: Ayelet Israeli and Eva Ascarza
This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and product—characterizing the marketing... View Details
Keywords: Algorithmic Data; Race And Ethnicity; Promotion; ＂Marketing Analytics＂; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeting; Targeted Advertising; Pricing Algorithms; Ethical Decision Making; Customer Heterogeneity; Marketing; Race; Ethnicity; Gender; Diversity; Prejudice and Bias; Marketing Communications; Analytics and Data Science; Analysis; Decision Making; Ethics; Customer Relationship Management; E-commerce; Retail Industry; Apparel and Accessories Industry; United States
Israeli, Ayelet, and Eva Ascarza. "Algorithmic Bias in Marketing." Harvard Business School Technical Note 521-020, September 2020. (Revised July 2022.)
- August 2018 (Revised October 2020)
- Case
Tailor Brands: Artificial Intelligence-Driven Branding
By: Jill Avery
Using proprietary artificial intelligence technology, startup Tailor Brands set out to democratize branding by allowing small businesses to create their brand identities by automatically generating logos in just minutes at minimal cost with no branding or design skills... View Details
Keywords: Startup; Services; Artificial Intelligence; Machine Learning; Digital Marketing; Brand Management; Big Data; Internet Marketing; Analytics; Marketing; Marketing Strategy; Brands and Branding; Information Technology; Entrepreneurship; Venture Capital; Business Model; Consumer Behavior; AI and Machine Learning; Analytics and Data Science; Advertising Industry; Service Industry; Technology Industry; United States; North America; Israel
Avery, Jill. "Tailor Brands: Artificial Intelligence-Driven Branding." Harvard Business School Case 519-017, August 2018. (Revised October 2020.)
- 2011
- Working Paper
Big BRICs, Weak Foundations: The Beginning of Public Elementary Education in Brazil, Russia, India, and China
By: Latika Chaudhary, Aldo Musacchio, Steven Nafziger and Se Yan
Our paper provides a comparative perspective on the development of public primary education in four of the largest developing economies circa 1910: Brazil, Russia, India and China (BRIC). These four countries encompassed more than 50 percent of the world's population... View Details
Keywords: Developing Countries and Economies; Economic Growth; Early Childhood Education; Government and Politics; Wealth and Poverty; China; India; Russia; Brazil
Chaudhary, Latika, Aldo Musacchio, Steven Nafziger, and Se Yan. "Big BRICs, Weak Foundations: The Beginning of Public Elementary Education in Brazil, Russia, India, and China." Harvard Business School Working Paper, No. 11-083, February 2011. (Revised July 2011.)
- November 28, 2017
- Editorial
Active Investing v.2.0
By: Gabriel Karageorgiou and George Serafeim
Keywords: Investment; Investing; Technology; Big Data; Quantitative Analysis; ESG; ESG (Environmental, Social, Governance) Performance; Sustainability; Analytics and Data Science
Karageorgiou, Gabriel, and George Serafeim. "Active Investing v.2.0." Pensions & Investments (online) (November 28, 2017).
- January 2021 (Revised March 2021)
- Case
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Jill Avery, Ayelet Israeli and Emma von Maur
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
Avery, Jill, Ayelet Israeli, and Emma von Maur. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Case 521-070, January 2021. (Revised March 2021.)
- 2012
- Working Paper
Big BRICs, Weak Foundations: The Beginning of Public Elementary Education in Brazil, Russia, India, and China
By: Latika Chaudhary, Aldo Musacchio, Steven Nafziger and Se Yan
Our paper provides a comparative perspective on the development of public primary education in four of the largest developing economies circa 1910: Brazil, Russia, India and China (BRIC). These four countries encompassed more than 50% of the world's population in 1910,... View Details
Keywords: History; Middle School Education; Data and Data Sets; Residency; Integration; Perspective; Surveys; Geographic Location; Welfare or Wellbeing; Government and Politics; Developing Countries and Economies; Growth and Development; China; India; Brazil; Russia
Chaudhary, Latika, Aldo Musacchio, Steven Nafziger, and Se Yan. "Big BRICs, Weak Foundations: The Beginning of Public Elementary Education in Brazil, Russia, India, and China." NBER Working Paper Series, No. 17852, February 2012.