Filter Results:
(971)
Show Results For
- All HBS Web
(971)
- News (133)
- Research (714)
- Events (8)
- Multimedia (4)
- Faculty Publications (547)
Show Results For
- All HBS Web
(971)
- News (133)
- Research (714)
- Events (8)
- Multimedia (4)
- Faculty Publications (547)
- August 2018 (Revised September 2018)
- Supplement
LendingClub (B): Decision Trees & Random Forests
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) case. In this case students follow Emily Figel as she builds two tree-based models using historical LendingClub data to predict, with some probability, whether borrower will repay or default on his loan.
... View Details
... View Details
Keywords: Data Science; Data Analytics; Decision Trees; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (B): Decision Trees & Random Forests." Harvard Business School Supplement 119-021, August 2018. (Revised September 2018.)
- September 13, 2023
- Article
How the Best Chief Data Officers Create Value
By: Suraj Srinivasan and Robin Seibert
Despite the rapidly increasing prominence of data and analytics functions, the majority of chief data officers (CDOs) fail to value and price the business outcomes created by their data and analytics capabilities. It comes as no surprise then that many CDOs fall behind... View Details
Srinivasan, Suraj, and Robin Seibert. "How the Best Chief Data Officers Create Value." Harvard Business Review (website) (September 13, 2023).
- December 2017
- Teaching Note
Yemeksepeti: Growing and Expanding the Business Model through Data
By: William R. Kerr and Alexis Brownell
Teaching Note for HBS No. 817-095. View Details
- December 2020
- Case
VIA Science (A)
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; Markets; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (A)." Harvard Business School Case 721-367, December 2020.
- December 2021
- Case
Burning Glass Technologies: From Data to Product
By: Suraj Srinivasan and Amy Klopfenstein
In May 2021, Matt Sigelman, CEO of Burning Glass Technologies, a company that provided labor market analytics for a variety of markets, navigates his company’s transition from data company to product company. Burning Glass originated as a service that used artificial... View Details
Keywords: Information Technology; Applications and Software; Digital Platforms; Internet and the Web; Strategy; Expansion; Business Strategy; Labor; Employment; Human Capital; Jobs and Positions; Job Design and Levels; Job Search; Human Resources; Selection and Staffing; Recruitment; Employees; Retention; Competency and Skills; Experience and Expertise; Talent and Talent Management; Analytics and Data Science; Business Model; Technology Industry; North and Central America; United States
Srinivasan, Suraj, and Amy Klopfenstein. "Burning Glass Technologies: From Data to Product." Harvard Business School Case 122-015, December 2021.
- February 2021
- Tutorial
Getting Started in RStudio Cloud
By: Chiara Farronato and Caleb Kwon
This video provides an introduction to the free programming language R using an online cloud version of RStudio, which is the most popular editor and interface for writing and executing R code. The video begins by providing a brief background of R and RStudio and... View Details
- 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.
- 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.
How the Best Chief Data Officers Create Value
Despite the rapidly increasing prominence of data and analytics functions, the majority of chief data officers (CDOs) fail to value and price the business outcomes created by their data and analytics capabilities. It comes as no surprise then that many CDOs fall... View Details
- 11 Jun 2013
- News
How Managers Should Use Data
- April 2022
- Teaching Note
Banorte Móvil: Data-Driven Mobile Growth
By: Ayelet Israeli and Carla Larangeira
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
- Article
One Obstacle to Curing Cancer: Patient Data Isn't Shared
By: Richard G. Hamermesh and Kathy Giusti
Precision Medicine requires large datasets to identify the mutations that lead to various cancers. Currently, genomic information is hoarded in fragmented silos within numerous academic medical centers, pharmaceutical companies, and some disease-based foundations. For... View Details
Keywords: Healthcare; Technological And Scientific Innovation; Cancer Care In The U.S.; Cancer Treatment; Precision Medicine; Personalized Medicine; Data Sharing; Technological Innovation; Analytics and Data Science; Health Disorders; Medical Specialties; Research and Development; Customization and Personalization; Health Industry; United States
Hamermesh, Richard G., and Kathy Giusti. "One Obstacle to Curing Cancer: Patient Data Isn't Shared." Harvard Business Review (website) (November 28, 2016).
- 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.
- 2021
- Chapter
Building Small Business Utopia: How Artificial Intelligence and Big Data Can Increase Small Business Success
By: Karen G. Mills and Annie Dang
Small business lending has remained unchanged for decades, laden with frictions and barriers that prevent many small businesses from accessing the capital they need to succeed. Financial technology, or “fintech,” promises to change this trajectory. In 2010, new fintech... View Details
Keywords: Big Data; Fintech; Artificial Intelligence; Small Business; Financing and Loans; Capital; Success; AI and Machine Learning; Analytics and Data Science
Mills, Karen G., and Annie Dang. "Building Small Business Utopia: How Artificial Intelligence and Big Data Can Increase Small Business Success." In Big Data in Small Business, edited by Carsten Lund Pedersen, Adam Lindgreen, Thomas Ritter, and Torsten Ringberg. Edward Elgar Publishing, 2021.
- July 2022
- Case
Operation Overlord
By: Boris Groysberg, Greg Goullet, Katherine Connolly Baden and Sarah L. Abbott
On June 6, 1944, nearly 5,000 ships, 11,000 planes, and 160,000 infantrymen under an Allied joint-command of American, British, and Canadian leaders were sent across the English Channel, with hopes of re-establishing a foothold in Nazi-occupied France. Known as D-Day,... View Details
Keywords: Execution; Data Analytics; Leadership; Planning; Operations; Crisis Management; War; Organizational Structure; Decision Choices and Conditions; Information Management; France; England
Groysberg, Boris, Greg Goullet, Katherine Connolly Baden, and Sarah L. Abbott. "Operation Overlord." Harvard Business School Case 422-098, July 2022.
- May 1983 (Revised November 1987)
- Case
Technical Data Corp.: Business Plan
Contains materials extracted from a business plan developed by the company in 1980. The purpose of the business plan was to raise $100,000 to finance the commencement of operations. The firm intended to provide analytical services to bond market traders. The product... View Details
Keywords: Business Plan
Sahlman, William A. "Technical Data Corp.: Business Plan." Harvard Business School Case 283-073, May 1983. (Revised November 1987.)
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
Keywords: Price; Demand and Consumers; AI and Machine Learning; Investment Return; Entertainment and Recreation Industry; Sports Industry
Alley, Michael, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, and Georgia Perakis. "Pricing for Heterogeneous Products: Analytics for Ticket Reselling." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 409–426.
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
- May 8, 2020
- Article
Which Covid-19 Data Can You Trust?
By: Satchit Balsari, Caroline Buckee and Tarun Khanna
The COVID-19 pandemic has produced a tidal wave of data, but how much of it is any good? And as a layperson, how can you sort the good from the bad? The authors suggest a few strategies for dividing the useful data from the misleading: Beware of data that’s too broad... View Details
Balsari, Satchit, Caroline Buckee, and Tarun Khanna. "Which Covid-19 Data Can You Trust?" Harvard Business Review (website) (May 8, 2020).
- 13 Aug 2014
- News