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- All HBS Web
(6,913)
- News (1,265)
- Research (4,450)
- Events (116)
- Multimedia (73)
- Faculty Publications (3,088)
Show Results For
- All HBS Web
(6,913)
- News (1,265)
- Research (4,450)
- Events (116)
- Multimedia (73)
- Faculty Publications (3,088)
- 2003
- Working Paper
The Flattening Firm: Evidence from Panel Data on the Changing Nature of Corporate Hierarchies
By: Raghuram G. Rajan and Julie Wulf
Using a detailed database of managerial job descriptions, reporting relationships, and compensation structures in over 300 large U.S. firms, we find that firm hierarchies are becoming flatter. The number of positions reporting directly to the CEO has gone up... View Details
Rajan, Raghuram G., and Julie Wulf. "The Flattening Firm: Evidence from Panel Data on the Changing Nature of Corporate Hierarchies." NBER Working Paper Series, No. 9633, April 2003. (Published in Review of Economics & Statistics 2006.)
- November 2006
- Article
The Flattening Firm: Evidence from Panel Data on the Changing Nature of Corporate Hierarchies
By: Raghuram G. Rajan and Julie Wulf
Using a detailed database of managerial job descriptions, reporting relationships, and compensation structures in over 300 large U.S. firms, we find that firm hierarchies are becoming flatter. The number of positions reporting directly to the CEO has gone up... View Details
Keywords: Geographic Location; Change; Business Ventures; Compensation and Benefits; Rank and Position; Wages; Motivation and Incentives; Organizational Change and Adaptation; Jobs and Positions; United States
Rajan, Raghuram G., and Julie Wulf. "The Flattening Firm: Evidence from Panel Data on the Changing Nature of Corporate Hierarchies." Review of Economics and Statistics 88, no. 4 (November 2006): 759–773.
- August 2018 (Revised April 2019)
- Case
Chateau Winery (A): Unsupervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case follows Bill Booth, marketing manager of a regional wine distributor, as he applies unsupervised learning on data about his customers’ purchases to better understand their preferences. Specifically, he uses the K-means clustering technique to identify groups... View Details
Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (A): Unsupervised Learning." Harvard Business School Case 119-023, August 2018. (Revised April 2019.)
- Article
Making Private Data Accessible in an Opaque Industry: The Experience of the Private Capital Research Institute
By: Josh Lerner and Leslie Jeng
Private markets are becoming an increasingly important way of financing rapidly growing and mature firms, and private investors are reputed to have far-reaching economic impacts. These important markets, however, are uniquely difficult to study. This paper explores... View Details
Lerner, Josh, and Leslie Jeng. "Making Private Data Accessible in an Opaque Industry: The Experience of the Private Capital Research Institute." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 157–160.
- February 2013
- Case
Recorded Future: Analyzing Internet Ideas About What Comes Next
Recorded Future is a "big data" startup company that uses Internet data to make predictions about events, people, and entities. The company primarily serves government intelligence agencies, but has some private sector clients and is considering taking on more. The... View Details
Keywords: Big Data; Analytics; Internet; Analytics and Data Science; Internet and the Web; Entrepreneurship; Forecasting and Prediction; Business Startups; Information Technology Industry
Davenport, Thomas H. "Recorded Future: Analyzing Internet Ideas About What Comes Next." Harvard Business School Case 613-083, February 2013.
- October 2017 (Revised November 2017)
- Case
NYC311
By: Constantine E. Kontokosta, Mitchell Weiss, Christine Snively and Sarah Gulick
Joe Morrisroe, executive director for NYC311, had some gut instincts but no definitive answer to the question he was just asked by one of the mayor’s deputies: “Are some communities being underserved by 311? How do we know we are hearing from the right people?” Founded... View Details
Keywords: New York City; NYC; 311; NYC311; Big Data; Equal Access; Bias; Data Analysis; Public Entrepreneurship; Urban Informatics; Predictive Analytics; Chief Data Officer; Data Analytics; Cities; City Leadership; Analytics and Data Science; Analysis; Prejudice and Bias; Entrepreneurship; Public Sector; City; Public Administration Industry; New York (city, NY)
- November 5, 2021
- Article
Leaders: Stop Confusing Correlation with Causation
By: Michael Luca
We’ve all been told that correlation does not imply causation. Yet many business leaders, elected officials, and media outlets still make causal claims based on misleading correlations. These claims are too often unscrutinized, amplified, and mistakenly used to guide... View Details
Keywords: Behavioral Economics; Data Analysis; Organizations; Decision Making; Analytics and Data Science; Analysis; Learning
Luca, Michael. "Leaders: Stop Confusing Correlation with Causation." Harvard Business Review Digital Articles (November 5, 2021).
- 2008
- Conference Presentation
Analyzing and Using Data From Global Positioning Systems and Digital Imagery in Mathematics Courses
By: F. Wattenberg, K. Erickson, J. Helms, K. DeGregory and Hise O. Gibson
Wattenberg, F., K. Erickson, J. Helms, K. DeGregory, and Hise O. Gibson. "Analyzing and Using Data From Global Positioning Systems and Digital Imagery in Mathematics Courses." Paper presented at the 20th International Conference for Technology in Collegiate Mathematics (ICTCM), San Antonio, TX, 2008.
- March 2022 (Revised January 2025)
- Technical Note
Prediction & Machine Learning
By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation; AI and Machine Learning
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)
- March 2019
- Case
Wattpad
By: John Deighton and Leora Kornfeld
How to run a platform to match four million writers of stories to 75 million readers? Use data science. Make money by doing deals with television and filmmakers and book publishers. The case describes the challenges of matching readers to stories and of helping writers... View Details
Keywords: Platform Businesses; Creative Industries; Publishing; Data Science; Machine Learning; Collaborative Filtering; Women And Leadership; Managing Data Scientists; Big Data; Recommender Systems; Digital Platforms; Information Technology; Intellectual Property; Analytics and Data Science; Publishing Industry; Entertainment and Recreation Industry; Canada; United States; Philippines; Viet Nam; Turkey; Indonesia; Brazil
Deighton, John, and Leora Kornfeld. "Wattpad." Harvard Business School Case 919-413, March 2019.
- 2011
- Chapter
Between Global and Local: The Invention of Data Privacy in the United States and France
Keywords: Social Issues; Knowledge Management; Information Management; Rights; United States; France
Trumbull, J. Gunnar. "Between Global and Local: The Invention of Data Privacy in the United States and France." In The Voice of the Citizen Consumer: A History of Market Research, Consumer Movements, and the Political Public Sphere, edited by Kerstin Bruckweh. Oxford: Oxford University Press, 2011.
- 2006
- Other Unpublished Work
The Impact of the SIC-NAICS Conversion on Industrial Organization Metrics: Evidence Building from Establishment Data
By: Glenn Ellison, Edward Glaeser and William R. Kerr
- 2004
- Case
Learning to Manage with Data in Duval County Public Schools: Lake Shore Middle School (A)
By: Allen Grossman, James P. Honan and Caroline Joan King
- 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.
- January 2021 (Revised March 2021)
- Exercise
E-Commerce Analytics for CPG Firms (C): Free Delivery Terms
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... 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; Grocery Delivery; Margins; Analytics and Data Science; Retention; E-commerce; Retail Industry; Consumer Products Industry; United States
Israeli, Ayelet, and Fedor (Ted) Lisitsyn. "E-Commerce Analytics for CPG Firms (C): Free Delivery Terms." Harvard Business School Exercise 521-080, January 2021. (Revised March 2021.)
- Teaching Interest
Overview
Teaching has been a lifelong passion of mine. As the third generation of academics in my family, I see good teaching as a means to give back and to encourage others to share my passion for discovery. I’ve been very lucky to have many teaching opportunities, both as an... View Details
Keywords: Big Data; Technology Strategy; Machine Learning; Data Science; "Marketing Analytics"; Data Visualization; Analysis; Technological Innovation; Innovation and Invention; Intellectual Property; Corporate Strategy; Software; Information Technology; Entrepreneurship; Marketing; Technology Industry; Information Technology Industry; Green Technology Industry; Computer Industry; Advertising Industry
- February 2021
- Case
Apple: Privacy vs. Safety (A)
By: Henry McGee, Nien-hê Hsieh, Sarah McAra and Christian Godwin
In 2015, Apple CEO Tim Cook debuted the iPhone 6S with enhanced security measures that enflamed a debate on privacy and public safety around the world. The iPhone 6S, amid a heightened concern for privacy following the 2013 revelation of clandestine U.S. surveillance... 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; National Security; Law; Law Enforcement; Leadership; Markets; Safety; Social Issues; Corporate Social Responsibility and Impact; Civil Society or Community; Mobile and Wireless Technology; Technology Industry; Consumer Products Industry; Telecommunications Industry; Electronics Industry; United States; China; Hong Kong
McGee, Henry, Nien-hê Hsieh, Sarah McAra, and Christian Godwin. "Apple: Privacy vs. Safety (A)." Harvard Business School Case 321-004, February 2021.