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Show Results For
- All HBS Web
(1,263)
- People (1)
- News (419)
- Research (647)
- Events (6)
- Multimedia (7)
- Faculty Publications (207)
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- 2020
- Working Paper
Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective
We provide a comprehensive examination of whether, to what extent, and which accounting variables are useful for improving the predictive accuracy of GDP growth forecasts. We leverage statistical models that accommodate a broad set of (341) variables—outnumbering the... View Details
Keywords: Big Data; Elastic Net; GDP Growth; Machine Learning; Macro Forecasting; Short Fat Data; Accounting; Economic Growth; Forecasting and Prediction; Analytics and Data Science
Datar, Srikant, Apurv Jain, Charles C.Y. Wang, and Siyu Zhang. "Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective." Harvard Business School Working Paper, No. 21-113, December 2020.
- 02 Apr 2015
- Research & Ideas
Digital Initiative Summit: Freeing Patient Data to Enable Innovation
listed difficulties translating data into practice, something he has experienced and is trying to address in his transition from practitioner to health care entrepreneur. "About 85 percent of practice today is driven by anecdotal... View Details
- 25 Apr 2012
- What Do You Think?
How Will the “Age of Big Data” Affect Management?
Summing Up: Will Access To Big Data Further Enable Fact-based Decision Making Or Analysis Paralysis? "To T. S. Eliot's prescient words 'Where is the wisdom we have lost in knowledge? Where is the knowledge... View Details
Keywords: Re: James L. Heskett
- 22 Mar 2021
- Research & Ideas
How to Learn from the Big Mistake You Almost Make
first survey, the data showed that the closer the situation got to causing patient harm, the more important psychological safety became in determining whether the employees would report the near-miss event. “With near misses that we... View Details
- 22 Feb 2024
- Research & Ideas
How to Make AI 'Forget' All the Private Data It Shouldn't Have
wasn't as big of a deal, because you could just retrain the model from scratch. Just throw out that data and do it again. That's really not plausible when training a model takes months and costs many... View Details
- May 2021
- Article
The Firm Next Door: Using Satellite Images to Study Local Information Advantage
By: Jung Koo Kang, Lorien Stice-Lawrence and Forester Wong
We use novel satellite data that track the number of cars in the parking lots of 92,668 stores for 71 publicly listed U.S. retailers to study the local information advantage of institutional investors. We establish car counts as a timely measure of store-level... View Details
Keywords: Satellite Images; Store-level Performance; Institutional Investors; Local Advantage; Overweighting; Processing Costs; Alternative Data; Big Data; Emerging Technologies; Information; Quality; Institutional Investing; Decision Making; Behavioral Finance; Analytics and Data Science
Kang, Jung Koo, Lorien Stice-Lawrence, and Forester Wong. "The Firm Next Door: Using Satellite Images to Study Local Information Advantage." Journal of Accounting Research 59, no. 2 (May 2021): 713–750.
- 02 Apr 2015
- Research & Ideas
Digital Initiative Summit: Big Messages, Small Screens, Many Choices
Again, hardly anyone raised a hand. "And that's the problem," Balis said. Other Articles In This Series Big Messages, Small Screens, Many Choices Companies Must Forget—and Borrow The Business of Crowdsourcing Freeing Patient View Details
- November–December 2022
- Article
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; Marketing; Retail Industry
Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Marketing Science 41, no. 6 (November–December 2022): 1074–1096.
- 04 Jan 2022
- Research & Ideas
Scrap the Big New Year's Resolutions. Make 6 Simple Changes Instead.
ability to collect and analyze more data more quickly, decision-making and problem-solving have become increasingly complex. Many people look to technology to solve modern problems, but the more technology advances, the more human... View Details
Keywords: by Kristen Senz
- 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.)
- 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.
- 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.)
- 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.)
- 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
- 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.)
- 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).
- 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.)
- 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.)