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Publications

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      • 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
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      Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (B)." Harvard Business School Supplement 721-368, December 2020.
      • 2020
      • Working Paper

      An Empirical Guide to Investor-Level Private Equity Data from Preqin

      By: Juliane Begenau, Claudia Robles-Garcia, Emil Siriwardane and Lulu Wang
      This note provides guidance on the use of investor-level private equity data from Preqin for empirical research. Preqin primarily sources its cash flow data through Freedom of Information Act (FOIA) requests with U.S. public pensions. Our focus is on the components of... View Details
      Keywords: Private Equity Returns; Prequin Data; Private Equity; Analytics and Data Science; Investment Return
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      Begenau, Juliane, Claudia Robles-Garcia, Emil Siriwardane, and Lulu Wang. "An Empirical Guide to Investor-Level Private Equity Data from Preqin." Working Paper, December 2020.
      • 2020
      • Working Paper

      Prioritarianism and Optimal Taxation

      By: Matti Tuomala and Matthew C. Weinzierl
      Prioritarianism has been at the center of the formal approach to optimal tax theory since its modern starting point in Mirrlees (1971), but most theorists’ use of it is motivated by tractability rather than explicit normative reasoning. We characterize analytically and... View Details
      Keywords: Prioritarianism; Optimal Taxation; Utilitarianism; Redistribution; Inverse-optimum; Taxation; Theory
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      Tuomala, Matti, and Matthew C. Weinzierl. "Prioritarianism and Optimal Taxation." Harvard Business School Working Paper, December 2020.
      • 2021
      • Working Paper

      The Value of Descriptive Analytics: Evidence from Online Retailers

      By: Ron Berman and Ayelet Israeli
      Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we find an... View Details
      Keywords: Descriptive Analytics; Big Data; Synthetic Control; E-commerce; Online Retail; Difference-in-differences; Martech; Internet and the Web; Analytics and Data Science; Performance; Retail Industry
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      Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Harvard Business School Working Paper, No. 21-067, November 2020. (Revised December 2021. Accepted at Marketing Science.)
      • October 2020 (Revised November 2020)
      • Case

      Wilderness Safaris: Impact Investing and Ecotourism Conservation in Africa

      By: James E. Austin, Megan Epler Wood and Herman B. "Dutch" Leonard
      In 2018 the majority ownership of publicly owned Wilderness Safaris, the leading high-end ecotourism company in Africa with safari operations in eight countries, was acquired by The Rise Fund, one of the world’s largest private social impact investing funds, and by FS... View Details
      Keywords: Investing; Investing For Impact; Ecotourism; COVID-19; Equity Financing; Strategy Formulation; Profitability; Environmental And Social Sustainability; Sustainability; Conservation Planning; Corporate Social Responsibility; Investment; Social Enterprise; Social Entrepreneurship; Environmental Sustainability; Strategy; Financing and Loans; Corporate Social Responsibility and Impact; Health Pandemics; Tourism Industry; Africa; Rwanda; Angola
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      Austin, James E., Megan Epler Wood, and Herman B. "Dutch" Leonard. "Wilderness Safaris: Impact Investing and Ecotourism Conservation in Africa." Harvard Business School Case 321-020, October 2020. (Revised November 2020.)
      • 2020
      • Working Paper

      Reverse Information Sharing: Reducing Costs in Supply Chains with Yield Uncertainty

      By: Pavithra Harsha, Ashish Jagmohan, Retsef Levi, Elisabeth Paulson and Georgia Perakis
      Supply uncertainty in produce supply chains presents major challenges to retailers. Supply shortages create frequent disruptions in terms of promised delivery times, quantity and quality delivered. To alleviate these challenges, dual sourcing--a strategy in which... View Details
      Keywords: Information Sharing; Yield Uncertainty; Ration Gaming; Blockchain; Supply Chain; Risk and Uncertainty
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      Harsha, Pavithra, Ashish Jagmohan, Retsef Levi, Elisabeth Paulson, and Georgia Perakis. "Reverse Information Sharing: Reducing Costs in Supply Chains with Yield Uncertainty." MIT Sloan Research Paper, No. 6172-20, October 2020.
      • September 2020 (Revised July 2022)
      • Technical Note

      Algorithmic Bias in Marketing

      By: Ayelet Israeli and Eva Ascarza
      This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and product—characterizing the marketing... View Details
      Keywords: Algorithmic Data; Race And Ethnicity; Promotion; "Marketing Analytics"; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analysis; Data Analytics; E-Commerce Strategy; Discrimination; Targeting; Targeted Advertising; Pricing Algorithms; Ethical Decision Making; Customer Heterogeneity; Marketing; Race; Ethnicity; Gender; Diversity; Prejudice and Bias; Marketing Communications; Analytics and Data Science; Analysis; Decision Making; Ethics; Customer Relationship Management; E-commerce; Retail Industry; Apparel and Accessories Industry; United States
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      Israeli, Ayelet, and Eva Ascarza. "Algorithmic Bias in Marketing." Harvard Business School Technical Note 521-020, September 2020. (Revised July 2022.)
      • September 2020 (Revised February 2024)
      • Teaching Note

      Artea (A), (B), (C), and (D): Designing Targeting Strategies

      By: Eva Ascarza and Ayelet Israeli
      Teaching Note for HBS No. 521-021,521-022,521-037,521-043. 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... View Details
      Keywords: Targeted Advertising; Targeting; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (A), (B), (C), and (D): Designing Targeting Strategies." Harvard Business School Teaching Note 521-041, September 2020. (Revised February 2024.)
      • September 2020 (Revised July 2022)
      • Exercise

      Artea (D): Discrimination through Algorithmic Bias in Targeting

      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: Targeted Advertising; Discrimination; Algorithmic Data; Bias; Advertising; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea (D): Discrimination through Algorithmic Bias in Targeting." Harvard Business School Exercise 521-043, September 2020. (Revised July 2022.)
      • September 2020 (Revised June 2023)
      • Exercise

      Artea: Designing Targeting Strategies

      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: Algorithmic Data; Race And Ethnicity; Experimentation; Promotion; "Marketing Analytics"; Marketing And Society; Big Data; Privacy; Data-driven Management; Data Analytics; Data Analysis; E-Commerce Strategy; Discrimination; Targeted Advertising; Targeted Policies; Targeting; Pricing Algorithms; A/B Testing; Ethical Decision Making; Customer Base Analysis; Customer Heterogeneity; Coupons; Algorithmic Bias; Marketing; Race; Gender; Diversity; Customer Relationship Management; Marketing Communications; Advertising; Decision Making; Ethics; E-commerce; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Artea: Designing Targeting Strategies." Harvard Business School Exercise 521-021, September 2020. (Revised June 2023.)
      • September 2020 (Revised June 2023)
      • Supplement

      Spreadsheet Supplement to Artea Teaching Note

      By: Eva Ascarza and Ayelet Israeli
      Spreadsheet Supplement to Artea Teaching Note 521-041. 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... View Details
      Keywords: Targeted Advertising; Algorithmic Data; Bias; Advertising; Race; Gender; Diversity; Marketing; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
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      Ascarza, Eva, and Ayelet Israeli. "Spreadsheet Supplement to Artea Teaching Note." Harvard Business School Spreadsheet Supplement 521-705, September 2020. (Revised June 2023.)
      • September 2020 (Revised September 2021)
      • Case

      Student Success at Georgia State University (A)

      By: Michael W. Toffel, Robin Mendelson and Julia Kelley
      Georgia State University had developed a reputation for driving student success by nearly doubling its graduation rate for students of all racial, ethnic, and socioeconomic backgrounds. It did so while growing its student body and the proportion of Black/African... View Details
      Keywords: Education; Higher Education; Learning; Curriculum and Courses; Demographics; Diversity; Ethnicity; Income; Race; Leadership; Goals and Objectives; Measurement and Metrics; Operations; Organizations; Mission and Purpose; Organizational Culture; Outcome or Result; Performance; Performance Effectiveness; Performance Evaluation; Service Operations; Performance Improvement; Planning; Strategic Planning; Social Enterprise; Nonprofit Organizations; Social Issues; Wealth and Poverty; Equality and Inequality; Information Technology; Digital Platforms; Education Industry; Atlanta
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      Toffel, Michael W., Robin Mendelson, and Julia Kelley. "Student Success at Georgia State University (A)." Harvard Business School Case 621-006, September 2020. (Revised September 2021.)
      • September 2020 (Revised March 2022)
      • Case

      JOANN: Joannalytics Inventory Allocation Tool

      By: Kris Ferreira and Srikanth Jagabathula
      Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and... View Details
      Keywords: Analytics; Machine Learning; Optimization; Inventory Management; Mathematical Methods; Decision Making; Operations; Supply Chain Management; Resource Allocation; Distribution; Technology Adoption; Applications and Software; Change Management; Fashion Industry; Consumer Products Industry; Retail Industry; United States; Ohio
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      Ferreira, Kris, and Srikanth Jagabathula. "JOANN: Joannalytics Inventory Allocation Tool." Harvard Business School Case 621-055, September 2020. (Revised March 2022.)
      • August 2020 (Revised September 2020)
      • Technical Note

      Assessing Prediction Accuracy of Machine Learning Models

      By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne
      The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools... View Details
      Keywords: Machine Learning; Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Forecasting and Prediction; Analytics and Data Science; Analysis; Mathematical Methods
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      Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
      • 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
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      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.)
      • August 2020
      • Technical Note

      Comparing Two Groups: Sampling and t-Testing

      By: Iavor I Bojinov, Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih and Michael W. Toffel
      This note describes sampling and t-tests, two fundamental statistical concepts. View Details
      Keywords: Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Analytics and Data Science; Analysis; Surveys; Mathematical Methods
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      Bojinov, Iavor I., Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih, and Michael W. Toffel. "Comparing Two Groups: Sampling and t-Testing." Harvard Business School Technical Note 621-044, August 2020.
      • August 2020
      • Teaching Note

      People Analytics at McKinsey

      By: Jeffrey T. Polzer and Olivia Hull
      Teaching note to accompany "People Analytics at McKinsey," HBS No. 418-023. View Details
      Keywords: People Analytics; Analytics; Human Resource Management; Business Analytics
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      Polzer, Jeffrey T., and Olivia Hull. "People Analytics at McKinsey." Harvard Business School Teaching Note 421-022, August 2020.
      • July 2020
      • Case

      Karen Bruck: Growing Managers at MercadoLibre

      By: Joshua D. Margolis, Fernanda Miguel and Mariana Cal
      Karen Bruck, Corporate Sales Director at MercadoLibre, Latin America's largest e-commerce platform, needs to make a decision about one of her managers, who, while analytically savvy, has an approach that does not fit in with the company's culture. View Details
      Keywords: Performance Evaluation; Employee Relationship Management; Decision Making; Interpersonal Communication; Organizational Culture; Retail Industry; Latin America; Argentina
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      Margolis, Joshua D., Fernanda Miguel, and Mariana Cal. "Karen Bruck: Growing Managers at MercadoLibre." Harvard Business School Case 421-013, July 2020.
      • July 2020
      • Case

      Applying Data Science and Analytics at P&G

      By: Srikant M. Datar, Sarah Mehta and Paul Hamilton
      Set in December 2019, this case explores how P&G has applied data science and analytics to cut costs and improve outcomes across its business units. The case provides an overview of P&G’s approach to data management and governance, and reviews the challenges associated... View Details
      Keywords: Data Science; Analytics; Analysis; Information; Information Management; Information Types; Innovation and Invention; Strategy; Analytics and Data Science; Consumer Products Industry; United States; Ohio
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      Datar, Srikant M., Sarah Mehta, and Paul Hamilton. "Applying Data Science and Analytics at P&G." Harvard Business School Case 121-006, July 2020.
      • July 2020
      • Case

      Driving Transformation at the Majid Al Futtaim Group

      By: Suraj Srinivasan and Esel Çekin
      The case opens with Alain Bejjani, CEO of Majid Al Futtaim (MAF) Holding, anticipating on the Group’s next phase in the multi-year transformation journey and reflecting on the initiatives he implemented to create the Group’s growth-oriented culture. Founded in 1995,... View Details
      Keywords: Transformation; Organizational Change and Adaptation; Organizational Culture; Growth and Development Strategy; Retail Industry; United Arab Emirates; Middle East; Dubai
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      Srinivasan, Suraj, and Esel Çekin. "Driving Transformation at the Majid Al Futtaim Group." Harvard Business School Case 121-002, July 2020.
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