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  • All HBS Web  (7,124)
    • News  (1,270)
    • Research  (4,399)
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  • All HBS Web  (7,124)
    • News  (1,270)
    • Research  (4,399)
    • Events  (116)
    • Multimedia  (73)
  • Faculty Publications  (3,068)
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  • November 2019
  • Article

How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework

By: Doug J. Chung, Byungyeon Kim and Byoung G. Park
This paper evaluates the short- and long-term value of sales representatives’ detailing visits to different types of physicians. By understanding the dynamic effect of sales calls across heterogeneous physicians, we provide guidance on the design of optimal call... View Details
Keywords: Nerlove-Arrow Framework; Stock-of-goodwill; Dynamic Panel Data; Serial Correlation; Instrumental Variables; Sales Effectiveness; Detailing; Analytics and Data Science; Sales; Analysis; Performance Effectiveness; Pharmaceutical Industry
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Chung, Doug J., Byungyeon Kim, and Byoung G. Park. "How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework." Management Science 65, no. 11 (November 2019): 5197–5218.
  • June 2020
  • Supplement

New Product Sales Data

By: E. Ofek
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Ofek, E. "New Product Sales Data." Harvard Business School Spreadsheet Supplement 520-715, June 2020.
  • Article

Big Data and Discrimination

By: Talia B Gillis and Jann Spiess
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Gillis, Talia B., and Jann Spiess. "Big Data and Discrimination." University of Chicago Law Review 86, no. 2 (April 2019): 459–487.
  • November 1988 (Revised August 1989)
  • Supplement

Mead Data Central (C)

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Hertenstein, Julie H. "Mead Data Central (C)." Harvard Business School Supplement 189-080, November 1988. (Revised August 1989.)
  • November 1988 (Revised August 1989)
  • Supplement

Mead Data Central (B)

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Hertenstein, Julie H. "Mead Data Central (B)." Harvard Business School Supplement 189-079, November 1988. (Revised August 1989.)
  • March 1982 (Revised August 1985)
  • Case

Perkin-Elmer: Data Systems Group

By: Robert J. Dolan
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Dolan, Robert J. "Perkin-Elmer: Data Systems Group." Harvard Business School Case 582-101, March 1982. (Revised August 1985.)
  • 2022
  • Article

Data Poisoning Attacks on Off-Policy Evaluation Methods

By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats... View Details
Keywords: Analytics and Data Science; Cybersecurity; Mathematical Methods
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Lobo, Elita, Harvineet Singh, Marek Petrik, Cynthia Rudin, and Himabindu Lakkaraju. "Data Poisoning Attacks on Off-Policy Evaluation Methods." Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 38th (2022): 1264–1274.
  • 27 Sep 2018
  • Working Paper Summaries

Large-Scale Demand Estimation with Search Data

Keywords: by Tomomichi Amano, Andrew Rhodes, and Stephan Seiler; Retail
  • October 2018
  • Case

BreezoMeter: Making Air Pollution Data Actionable

By: Frank V. Cespedes, Allison M. Ciechanover and Margot Eiran
The case focuses on an Israeli startup that provides actionable air pollution data and forecasts. The company has over 50 enterprise customers and its tool reached a million people daily in 67 countries. The co-founders wrestle with which markets and customers to focus... View Details
Keywords: Startups; Entrepreneurship; Business Startups; Pollutants; Analytics and Data Science; Sales; Marketing; Decision Choices and Conditions; Technology Industry; Israel; United States
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Cespedes, Frank V., Allison M. Ciechanover, and Margot Eiran. "BreezoMeter: Making Air Pollution Data Actionable." Harvard Business School Case 819-058, October 2018.
  • September 2020 (Revised July 2022)
  • Exercise

Artea (B): Including Customer-Level Demographic Data

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: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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Ascarza, Eva, and Ayelet Israeli. "Artea (B): Including Customer-Level Demographic Data." Harvard Business School Exercise 521-022, September 2020. (Revised July 2022.)
  • 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
Keywords: Value Creation; Analytics and Data Science; Measurement and Metrics; Leadership
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Srinivasan, Suraj, and Robin Seibert. "How the Best Chief Data Officers Create Value." Harvard Business Review (website) (September 13, 2023).
  • March 2024 (Revised May 2024)
  • Case

Amperity: First-Party Data at a Crossroads

By: Elie Ofek, Hema Yoganarasimhan and Alexis Lefort
In the summer of 2023, Amperity management was facing a critical decision on its future direction. Given the dramatic changes occurring within the digital advertising ecosystem, as concerns over consumer privacy placed limits on the ability to engage in third-party... View Details
Keywords: AI and Machine Learning; Technology Adoption; Business Strategy; Digital Marketing; Price; Product; Business or Company Management; Advertising Industry
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Ofek, Elie, Hema Yoganarasimhan, and Alexis Lefort. "Amperity: First-Party Data at a Crossroads." Harvard Business School Case 524-017, March 2024. (Revised May 2024.)
  • July 2021
  • Article

Big Data for Social Benefits: Innovation as a Mediator of the Relationship between Big Data and Corporate Social Performance

By: Goran Calic and Maryam Ghasemaghaei
Over the last decade, the use big data in firms has seen a rapid increase. Whilst scholars have begun to unpack the relationship between big data utilisation and financial performance, significant uncertainty exists about the ethical uses of this new asset. Whether... View Details
Keywords: Analytics and Data Science; AI and Machine Learning; Performance Improvement; Organizational Change and Adaptation
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Calic, Goran, and Maryam Ghasemaghaei. "Big Data for Social Benefits: Innovation as a Mediator of the Relationship between Big Data and Corporate Social Performance." Journal of Business Research 131 (July 2021): 391–401.
  • January 2018 (Revised November 2018)
  • Case

Acumen and Lean Data 2018

By: Shawn Cole, V. Kasturi Rangan, Alnoor Ebrahim and Caitlin Reimers Brumme
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Cole, Shawn, V. Kasturi Rangan, Alnoor Ebrahim, and Caitlin Reimers Brumme. "Acumen and Lean Data 2018." Harvard Business School Case 218-086, January 2018. (Revised November 2018.)
  • February 2024
  • Supplement

Data Science at the Warriors

By: Iavor I Bojinov
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Bojinov, Iavor I. "Data Science at the Warriors." Harvard Business School Spreadsheet Supplement 624-712, February 2024.
  • 1995
  • Book

Data Analysis, Regression, and Forecasting

By: A. Schleifer Jr. and D. E. Bell
Keywords: Forecasting and Prediction
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Schleifer, A., Jr., and D. E. Bell. Data Analysis, Regression, and Forecasting. Cambridge, MA: Course Technology Inc. (CTI), 1995.
  • May 1983 (Revised November 1987)
  • Case

Technical Data Corp.: Business Plan

By: William A. Sahlman
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
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Sahlman, William A. "Technical Data Corp.: Business Plan." Harvard Business School Case 283-073, May 1983. (Revised November 1987.)
  • January 2020
  • Case

Kaggle 2019 Data Science Survey

By: Yael Grushka-Cockayne, Michael Parzen, Paul Hamilton and Steven Randazzo
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Grushka-Cockayne, Yael, Michael Parzen, Paul Hamilton, and Steven Randazzo. "Kaggle 2019 Data Science Survey." Harvard Business School Case 620-091, January 2020.
  • August 1981
  • Background Note

Overview of Data Communications Technology

By: James I. Cash Jr.
Keywords: Information Technology
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Cash, James I., Jr. "Overview of Data Communications Technology." Harvard Business School Background Note 182-018, August 1981.
  • October 2023 (Revised April 2024)
  • Case

TetraScience: Unlocking the Power of Scientific Data

By: Satish Tadikonda and William Marks
After pivoting from a focus on hardware to a focus on scientific data, TetraScience, led by veteran SaaS executive, Patrick Grady and Founder Spin Wang, has embarked on a journey from nearly cash-out to a player in the scientific data management space. This case... View Details
Keywords: Business Model; Change Management; Entrepreneurship; Information Management; Business Strategy; Market Entry and Exit; Information Technology Industry
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Tadikonda, Satish, and William Marks. "TetraScience: Unlocking the Power of Scientific Data." Harvard Business School Case 824-072, October 2023. (Revised April 2024.)
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