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  • All HBS Web  (1,490)
    • News  (192)
    • Research  (1,061)
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    • Multimedia  (8)
  • Faculty Publications  (661)

Show Results For

  • All HBS Web  (1,490)
    • News  (192)
    • Research  (1,061)
    • Events  (20)
    • Multimedia  (8)
  • Faculty Publications  (661)
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  • 2012
  • Book

Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data

By: Thomas H. Davenport
This book, an edited collection of research papers from the International Institute of Analytics, addresses a wide variety of key topics in managing business analytics and big data at the enterprise level. It includes key applications of analytics, human and... View Details
Keywords: Business Analytics; Big Data; Business or Company Management; Analytics and Data Science; Management Practices and Processes; Mathematical Methods; Information Management
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Davenport, Thomas H., ed. Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data. FT Press, 2012.
  • October 2018 (Revised August 2023)
  • Case

Safecast: Bootstrapping Human Capital to Big Data

By: Ethan Bernstein and Stephanie Marton
On March 11, 2011, at 2:46pm, a 9.1-on-the-Richter-scale, six-minute long earthquake unleashed a tsunami that ravaged the Tohoku region of Japan, damaging the Fukushima Daiichi Nuclear Power facility and releasing sufficient radioactive material into the air and ocean... View Details
Keywords: Citizen Science; Creative Commons; Open Data; Open Architecture; Volunteer-based Organization; Fukushima Daiichi Nuclear Power Facility; 311; Nuclear; Radiation; Crowdsourcing; Bgeigie; Geiger Counters; Kickstarter; Sustainability; Sustainable Business And Innovation; Design; Energy Generation; Social Entrepreneurship; Human Capital; Innovation and Invention; Crisis Management; Organizational Structure; Organizational Design; Information Technology; Business Model; Energy Industry; Technology Industry; Japan; North and Central America; Europe
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Bernstein, Ethan, and Stephanie Marton. "Safecast: Bootstrapping Human Capital to Big Data." Harvard Business School Case 419-033, October 2018. (Revised August 2023.)
  • March 2022 (Revised January 2025)
  • Technical Note

Statistical Inference

By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an overview of statistical inference for an introductory data science course. First, the note discusses samples and populations. Next the note describes how to calculate confidence intervals for means and proportions. Then it walks through the logic... View Details
Keywords: Data Science; Statistics; Mathematical Modeling; Mathematical Methods; Analytics and Data Science
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Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Statistical Inference." Harvard Business School Technical Note 622-099, March 2022. (Revised January 2025.)
  • September 2018
  • Case

Verisk: Trailblazing in the Big Data Jungle

By: Andrew Wasynczuk, Francesca Gino and Karim Sameh
This case revolves around Verisk Analytics' initiatives to drive innovation throughout the firm's many business verticals. Verisk, originally named ISO, started life as an insurance rating agency in the early 1970s, acting as an intermediary between insurance companies... View Details
Keywords: Verisk; Argus; Wood Mackenzie; Insurance; Energy; Analytics; Data; Big Data; Acquisitions; Acquisition Strategy; Innovation; Organic Growth; Innovation Strategy; Innovation Leadership; Technological Innovation; Acquisition; Growth and Development Strategy; Analytics and Data Science; Insurance Industry; Energy Industry; Consulting Industry; United States; United Kingdom; New York (state, US); England
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Wasynczuk, Andrew, Francesca Gino, and Karim Sameh. "Verisk: Trailblazing in the Big Data Jungle." Harvard Business School Case 919-014, September 2018.
  • August 2018 (Revised September 2018)
  • Supplement

LendingClub (C): Gradient Boosting & Payoff Matrix

By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) and (B) cases. In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default... View Details
Keywords: Data Analytics; Data Science; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
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Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (C): Gradient Boosting & Payoff Matrix." Harvard Business School Supplement 119-022, August 2018. (Revised September 2018.)
  • March 2020
  • Article

Diagnosing Missing Always at Random in Multivariate Data

By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin
Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first... View Details
Keywords: Missing Data; Diagnostic Tools; Sensitivity Analysis; Hypothesis Testing; Missing At Random; Row Exchangeability; Analytics and Data Science; Mathematical Methods
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Bojinov, Iavor I., Natesh S. Pillai, and Donald B. Rubin. "Diagnosing Missing Always at Random in Multivariate Data." Biometrika 107, no. 1 (March 2020): 246–253.
  • February 2017
  • Case

Yemeksepeti: Growing and Expanding the Business Model through Data

By: William R. Kerr, Gamze Yucaoglu and Eren Kuzucu
In October 2016, Nevzat Aydin, co-founder and CEO of Yemeksepeti, the Turkish online food-ordering company, was looking over the company's quarterly results and projections for the upcoming year with his management team. It had been almost a year and a half since Aydin... View Details
Keywords: Entrepreneurial Management; Entrepreneurial Ventures; Turkey; Big Data; Customer Focused Organization; Service Management; Continuous Improvement; Data Analysis; Internet; Growth Strategy; Technological Change; Information Systems; Entrepreneurship; Corporate Strategy; Analytics and Data Science; Analysis; Customer Focus and Relationships; Emerging Markets; Service Operations; Competitive Advantage; Performance Improvement; Internet and the Web; Growth and Development Strategy; Information Technology; Value Creation; Food and Beverage Industry; Turkey
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Kerr, William R., Gamze Yucaoglu, and Eren Kuzucu. "Yemeksepeti: Growing and Expanding the Business Model through Data." Harvard Business School Case 817-095, February 2017.
  • April 29, 2014
  • Column

Corporate Reporting in the Big Data Era

By: George Serafeim
Advancements in information technology can improve corporate communication with shareholders, but not through incessant data dumps. Instead, companies will more likely be poised for continued success if they use digital platforms for long-term oriented engagement and... View Details
Keywords: Integrated Reporting; Big Data; Corporate Reporting; Sustainability; Corporate Social Responsibility; Corporate Governance; Accounting; Reporting; Organizational Change and Adaptation; Corporate Accountability; Analytics and Data Science; Information Technology; Communication; Financial Reporting; Business and Shareholder Relations
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Serafeim, George. "Corporate Reporting in the Big Data Era." IIRC Blog (April 29, 2014).

    The Elasticity of Science

    The adjustment costs of science -- getting scientists to study what you want them to -- are very large.

    Abstact: This paper identifies the degree to which scientists are willing to change the direction of their work in exchange for resources.... View Details
    • 07 Aug 2000
    • Research & Ideas

    Rocket Science Retailing

    Marshall Fisher of the Wharton School at the University of Pennsylvania, Ananth Raman of HBS and their colleague Anna Sheen McClelland recently completed a survey of 32 retail companies focusing on their practices and progress in four areas critical to what they call... View Details
    Keywords: by Marshall L. Fisher, Ananth Raman & Anna Sheen McClelland; Retail
    • August 2018 (Revised September 2018)
    • Case

    Predicting Purchasing Behavior at PriceMart (A)

    By: Srikant M. Datar and Caitlin N. Bowler
    This case follows VP of Marketing, Jill Wehunt, and analyst Mark Morse as they tackle a predictive analytics project to increase sales in the Mom & Baby unit of a nationally recognized retailer, PriceMart. Wehunt observed that in the midst of the chaos that surrounded... View Details
    Keywords: Data Science; Analytics and Data Science; Analysis; Consumer Behavior; Forecasting and Prediction
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    Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (A)." Harvard Business School Case 119-025, August 2018. (Revised September 2018.)
    • Article

    Gathering Data for Archival, Field, Survey, and Experimental Accounting Research

    By: Robert Bloomfield, Mark W. Nelson and Eugene F. Soltes
    In the published proceedings of the first Journal of Accounting Research Conference, Vatter (1966) lamented that “Gathering direct and original facts is a tedious and difficult task, and it is not surprising that such work is avoided.” For the 50th JAR Conference,... View Details
    Keywords: Archival; Data; Experiment; Empirical Methods; Field Study; Analytics and Data Science; Surveys; Financial Reporting
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    Bloomfield, Robert, Mark W. Nelson, and Eugene F. Soltes. "Gathering Data for Archival, Field, Survey, and Experimental Accounting Research." Journal of Accounting Research 54, no. 2 (May 2016): 341–395.
    • Research Summary

    Reforming Social Science

    By: Max H. Bazerman

    Social science research affects all of us. When researchers learned organ donation rates are higher in countries where human organs are automatically available for donation unless you specifically “opt-out” of the system, as opposed to countries like the U.S., where... View Details

    • 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
    Keywords: Data Science; Data Analytics; Decision Trees; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
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    Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (B): Decision Trees & Random Forests." Harvard Business School Supplement 119-021, August 2018. (Revised September 2018.)
    • 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
    Keywords: Clustering; Data Science; Analytics and Data Science; Customers; Marketing; Analysis
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    Datar, Srikant M., and Caitlin N. Bowler. "Chateau Winery (A): Unsupervised Learning." Harvard Business School Case 119-023, August 2018. (Revised April 2019.)
    • October 2020
    • Article

    The Elasticity of Science

    By: Kyle Myers
    This paper identifies the degree to which scientists are willing to change the direction of their work in exchange for resources. Data from the National Institutes of Health are used to estimate how scientists respond to targeted funding opportunities. Inducing a... View Details
    Keywords: Scientists; Funding; Research; Change
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    Myers, Kyle. "The Elasticity of Science." American Economic Journal: Applied Economics 12, no. 4 (October 2020): 103–134.
    • Article

    Core Earnings: New Data and Evidence

    By: Ethan Rouen, Eric C. So and Charles C.Y. Wang
    Using a novel dataset, we show that components of firms' GAAP earnings stemming from ancillary business activities or transitory shocks are significant in frequency and magnitude. These components have grown over time and are dispersed across various sections of the... View Details
    Keywords: Core Earnings; Transitory Earnings; Non-operating Earnings; Quantitative Disclosures; Equity Valuation; Big Data; Business Earnings; Financial Reporting; Valuation; Analytics and Data Science
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    Rouen, Ethan, Eric C. So, and Charles C.Y. Wang. "Core Earnings: New Data and Evidence." Journal of Financial Economics 142, no. 3 (December 2021): 1068–1091.
    • February 2021 (Revised February 2021)
    • Background Note

    eGrocery and the Role of Data for CPG Firms

    By: Ayelet Israeli, Fedor (Ted) Lisitsyn and Mark A. Irwin
    This notes provides information about the eGrocery industry and how traditional CPG companies handle this channel and potential data. It is recommended to use together with a series of exercises entitled: "E-Commerce Analytics for CPG Firms (A), (B), and (C)." 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; Optimization; Analytics and Data Science; Analysis; Customer Value and Value Chain; Marketing Channels; E-commerce; Retail Industry; Consumer Products Industry; United States
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    Israeli, Ayelet, Fedor (Ted) Lisitsyn, and Mark A. Irwin. "eGrocery and the Role of Data for CPG Firms." Harvard Business School Background Note 521-077, February 2021. (Revised February 2021.)

      Rethinking the Profession Formerly Known as Advertising: How Data Science Is Disrupting the Work of Agencies

      Speaker's Box, Journal of Advertising Research
      “Speaker’s Box” invites academics and practitioners to identify potential areas of research affecting marketing and advertising. Its intention is to bridge the gap between the length... View Details
      • 30 May 2013
      • News

      Big Data Lessons from Silicon Valley

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