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Show Results For
- All HBS Web
(3,299)
- News (517)
- Research (2,505)
- Events (43)
- Multimedia (18)
- Faculty Publications (1,611)
- June 2010 (Revised July 2011)
- Case
Classic Knitwear and Guardian: A Perfect Fit?
By: John A. Quelch and Patricia Girardi
Classic Knitwear manufactures and distributes casual apparel, either unbranded or under a private-label brand name. Partly because Classic has no brand recognition with consumers, gross margins are low. To improve margins, the company considers partnering via a... View Details
Keywords: Market Research; Forecasting; Consumer Marketing; New Product Marketing; Product Lines; Merchandising; Branding; Demand and Consumers; Partners and Partnerships; Marketing Strategy; Forecasting and Prediction; Product Marketing; Brands and Branding; Product Development; Apparel and Accessories Industry; Apparel and Accessories Industry
Quelch, John A., and Patricia Girardi. "Classic Knitwear and Guardian: A Perfect Fit?" Harvard Business School Brief Case 104-217, June 2010. (Revised July 2011.)
- 2018
- Working Paper
Bayesian Ensembles of Binary-Event Forecasts: When Is It Appropriate to Extremize or Anti-Extremize?
By: Kenneth C. Lichtendahl Jr., Yael Grushka-Cockayne, Victor Richmond R. Jose and Robert L. Winkler
Many organizations face critical decisions that rely on forecasts of binary events. In these situations, organizations often gather forecasts from multiple experts or models and average those forecasts to produce a single aggregate forecast. Because the average... View Details
Keywords: Forecast Aggregation; Linear Opinion Pool; Generalized Additive Model; Generalized Linear Model; Stacking.; Forecasting and Prediction
Lichtendahl, Kenneth C., Jr., Yael Grushka-Cockayne, Victor Richmond R. Jose, and Robert L. Winkler. "Bayesian Ensembles of Binary-Event Forecasts: When Is It Appropriate to Extremize or Anti-Extremize?" Harvard Business School Working Paper, No. 19-041, October 2018.
- October 2014
- Case
Honeywell and the Great Recession (A)
By: Sandra J. Sucher and Susan J. Winterberg
CEO Dave Cote spent six years turning around an ailing Honeywell and in 2008 Cote and his team face a new challenge: how to respond to the Great Recession. Cote does not want to give up the gains he made in transforming and unifying Honeywell. With a fall-off in... View Details
Keywords: Layoffs; Furloughs; Downsizing; Work Sharing; Short Time Work; Recessions; Earnings Forecast; Job Cuts and Outsourcing; Cost Management; Executive Compensation; Crisis Management; Financial Crisis; Manufacturing Industry
Sucher, Sandra J., and Susan J. Winterberg. "Honeywell and the Great Recession (A)." Harvard Business School Case 315-022, October 2014.
- December 2003 (Revised February 2008)
- Background Note
Law and Legal Reasoning: An Introduction
By: Henry B. Reiling
Gives prominence to Mr. Justice Holmes' Prediction Theory of the law as a practical--and by analogy to forecasting in finance and other functional areas of business--comfortable, and familiar way for businesspeople to think about the law. Law is defined as a forecast... View Details
Reiling, Henry B. "Law and Legal Reasoning: An Introduction." Harvard Business School Background Note 204-080, December 2003. (Revised February 2008.)
- 2021
- Article
An Empirical Examination of Sell-Side Brokerage Analysts' Published Research, Concierge Services, and High-Touch Services
By: David A. Maber, Boris Groysberg and Paul M. Healy
This paper uses a proprietary panel dataset to categorize and quantify the activities that sell-side brokerage analysts use to build and sustain their network of buy-side client relations. We then examine the marginal impact of these activities on key analyst outcome... View Details
Maber, David A., Boris Groysberg, and Paul M. Healy. "An Empirical Examination of Sell-Side Brokerage Analysts' Published Research, Concierge Services, and High-Touch Services." European Accounting Review 30, no. 4 (2021): 827–853.
- 2021
- Working Paper
When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making
By: Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage and Himabindu Lakkaraju
McGrath, Sean, Parth Mehta, Alexandra Zytek, Isaac Lage, and Himabindu Lakkaraju. "When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making." Working Paper, January 2021.
- 01 Jun 2023
- News
3-Minute Briefing: Jeremy Grantham (MBA 1966)
change, geopolitics, declining fertility rates, bad agricultural practices, high levels of debt, shortages of labor and raw materials, and more. You can’t predict the stress... View Details
- 16 Oct 2019
- Working Paper Summaries
Core Earnings? New Data and Evidence
- February 2018 (Revised December 2020)
- Supplement
People Analytics at Teach For America (Data Set)
This data set is a supplement to the People Analytics at Teach For America (A) case. View Details
- June 18, 2014
- Blog Post
How to Kill Quarterly Earnings Guidance
By: Gabriel Karageorgiou, Daniela Saltzman and George Serafeim
Karageorgiou, Gabriel, Daniela Saltzman, and George Serafeim. "How to Kill Quarterly Earnings Guidance." HBR Blog Network (June 18, 2014). http://blogs.hbr.org/2014/06/how-to-kill-quarterly-earnings-guidance/.
- 1997
- Chapter
On the Dynamics of Forecasting in Technologically Complex Environments: The Unexpectedly Long Old Age of Optical Lithography
Keywords: History; Information Technology; Situation or Environment; Complexity; Forecasting and Prediction; Technology Industry
Henderson, Rebecca M. "On the Dynamics of Forecasting in Technologically Complex Environments: The Unexpectedly Long Old Age of Optical Lithography." In Technological Innovation: Oversights and Foresights, edited by Raghu Garud, Praveen Rattan Nayyar, and Zur Baruch Shapira. New York: Cambridge University Press, 1997.
- 05 Feb 2019
- Working Paper Summaries
Stereotypes and Belief Updating
- June 2010 (Revised July 2011)
- Teaching Note
Classic Knitwear and Guardian: A Perfect Fit? (Brief Case)
By: John A. Quelch and Patricia Girardi
Teaching Note for 4217. View Details
- 2016
- Book
Innovation Equity: Assessing and Managing the Monetary Value of New Products and Services
By: Elie Ofek, Eitan Muller and Barak Libai
This book bridges the gap between what academics know, and what innovation stakeholders—from managers, to investors, to analysts, to consumers—need to know about how new products and services are expected to perform in the marketplace. The book develops a compelling... View Details
Keywords: Innovation; Technology Diffusion; New Products; Customer Lifetime Value; Monetization Strategy; Social Influence; Innovation Adoption; Forecasting Demand; Commercialization; Marketing Strategy; Practice; Customer Value and Value Chain; Research; Innovation and Management; Technology Adoption; Forecasting and Prediction; Product Development
Ofek, Elie, Eitan Muller, and Barak Libai. Innovation Equity: Assessing and Managing the Monetary Value of New Products and Services. University of Chicago Press, 2016.
- 2019
- Working Paper
Managing Churn to Maximize Profits
By: Aurelie Lemmens and Sunil Gupta
Customer defection threatens many industries, prompting companies to deploy targeted, proactive customer retention programs and offers. A conventional approach has been to target customers either based on their predicted churn probability, or their responsiveness to a... View Details
Keywords: Churn Management; Defection Prediction; Loss Function; Stochastic Gradient Boosting; Customer Relationship Management; Consumer Behavior; Profit
Lemmens, Aurelie, and Sunil Gupta. "Managing Churn to Maximize Profits." Harvard Business School Working Paper, No. 14-020, September 2013. (Revised December 2019. Forthcoming at Marketing Science.)
- 11 Jul 2018
- Working Paper Summaries
Channeled Attention and Stable Errors
- February 2019
- Case
Miroglio Fashion (A)
By: Sunil Gupta and David Lane
Francesco Cavarero, chief information officer of Miroglio Fashion, Italy’s third-largest retailer of women’s apparel, was trying to bring analytical rigor to the company’s forecasting and inventory management decisions. But fashion is inherently hard to predict. Can... View Details
Keywords: Inventory Management; Demand Forecasting; Artificial Intelligence; Machine Learning; Forecasting and Prediction; Operations; Management; Decision Making; AI and Machine Learning; Apparel and Accessories Industry; Apparel and Accessories Industry
Gupta, Sunil, and David Lane. "Miroglio Fashion (A)." Harvard Business School Case 519-053, February 2019.
- May 2018
- Article
Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change
By: Edward L. Glaeser, Hyunjin Kim and Michael Luca
Data from digital platforms have the potential to improve our understanding of gentrification and enable new measures of how neighborhoods change in close to real time. Combining data on businesses from Yelp with data on gentrification from the Census, Federal Housing... View Details
Keywords: Forecasting Models; Simulation Methods; Regional Economic Activity: Growth, Development, Environmental Issues, And Changes; Geographic Location; Local Range; Transition; Analytics and Data Science; Measurement and Metrics; Economic Growth; Forecasting and Prediction
Glaeser, Edward L., Hyunjin Kim, and Michael Luca. "Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change." AEA Papers and Proceedings 108 (May 2018): 77–82.
- July 2019
- Article
I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice
By: Kate Barasz, Tami Kim and Ioannis Evangelidis
People often speculate about why others make the choices they do. This paper investigates how such inferences are formed as a function of what is chosen. Specifically, when observers encounter someone else's choice (e.g., of political candidate), they use the chosen... View Details
Keywords: Self-other Difference; Social Perception; Inference-making; Preferences; Consumer Behavior; Prediction; Prediction Error; Decision Choices and Conditions; Perception; Behavior; Forecasting and Prediction
Barasz, Kate, Tami Kim, and Ioannis Evangelidis. "I Know Why You Voted for Trump: (Over)inferring Motives Based on Choice." Special Issue on The Cognitive Science of Political Thought. Cognition 188 (July 2019): 85–97.
- Article
Beacon and Warning: Sherman Kent, Scientific Hubris, and the CIA's Office of National Estimates
By: J. Peter Scoblic
Would-be forecasters have increasingly extolled the predictive potential of Big Data and artificial intelligence. This essay reviews the career of Sherman Kent, the Yale historian who directed the CIA’s Office of National Estimates from 1952 to 1967, with an eye toward... View Details
Keywords: National Security; Analytics and Data Science; Analysis; Forecasting and Prediction; History
Scoblic, J. Peter. "Beacon and Warning: Sherman Kent, Scientific Hubris, and the CIA's Office of National Estimates." Texas National Security Review 1, no. 4 (August 2018).