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August 2018 (Revised September 2018)
Supplement

Predicting Purchasing Behavior at PriceMart (B)

By: Srikant M. Datar and Caitlin N. Bowler

Supplements the (A) case. In this case, Wehunt and Morse are concerned about the logistic regression model overfitting to the training data, so they explore two methods for reducing the sensitivity of the model to the data by regularizing the coefficients of the... View Details

Keywords: Data Science; Analytics and Data Science; Analysis; Customers; Household; Forecasting and Prediction

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

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

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

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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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

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

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

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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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

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

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

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

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

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

August 2021
Case

Precision Paint Co.

By: Iavor I. Bojinov, Chiara Farronato, Janice H. Hammond, Michael Parzen and Paul Hamilton

Describes a marketing director about to launch a new process for demand forecasting. Provides data that allow students to do a multivariable regression analysis. A rewritten version of an earlier case. View Details

Keywords: Regression; Prediction; Forecasting; Data Science; Analysis; Forecasting and Prediction

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

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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October 2020
Article

The Elasticity of Science

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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