Analytics and Data Science - Publications - Faculty & Research - Harvard Business School

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February 2021
Technical Note

Probability Distributions

By: Michael Parzen and Paul Hamilton

This technical note introduces students to the concept of random variables, and from there the normal and binomial distributions. After a brief introduction to random variables, the note describes the standard properties of the normal distribution: a single peak, and a... View Details

Keywords: Analysis; Risk and Uncertainty; Theory; Analytics and Data Science

February 2021
Case

Digital Manufacturing at Amgen

By: Shane Greenstein, Kyle R. Myers and Sarah Mehta

This case discusses efforts made by biotechnology (biotech) company Amgen to introduce digital technologies into its manufacturing processes. Doing so is complicated by the fact that the process for manufacturing biologics—or therapeutics made from living cells—is... View Details

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

January 2021 (Revised March 2021)
Case

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Jill Avery, Ayelet Israeli and Emma von Maur

THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details

Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States

January 2021 (Revised May 2021)
Case

Amazon Shopper Panel: Paying Customers for Their Data

By: Eva Ascarza and Ayelet Israeli

This case introduces a new Amazon program that has consumers upload their receipts from transactions outside of Amazon, in exchange for money. Through the discussion, the case aims to explore issues in customers’ privacy in the digital age, the value of customers’ own... View Details

January 2021 (Revised March 2021)
Supplement

E-Commerce Analytics for CPG Firms (A): Estimating Sales

By: Ayelet Israeli and Fedor (Ted) Lisitsyn

The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details

January 2021 (Revised March 2021)
Exercise

E-Commerce Analytics for CPG Firms (A): Estimating Sales

By: Ayelet Israeli and Fedor (Ted) Lisitsyn

The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details

January 2021
Supplement

E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer

By: Ayelet Israeli and Fedor (Ted) Lisitsyn

The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details

Keywords: Data Analysis; Data Analytics; CPG; Consumer Packaged Goods (CPG); Online Channel; Retail; Retail Analytics; Retailing Industry; Data; Data Sharing; Ecommerce; Assortment Optimization; Assortment Planning; Analytics and Data Science; Retention; Retail Industry; Consumer Products Industry; United States

January 2021
Exercise

E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer

By: Ayelet Israeli and Fedor (Ted) Lisitsyn

The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details

January 2021 (Revised March 2021)
Supplement

E-Commerce Analytics for CPG Firms (C): Free Delivery Terms

By: Ayelet Israeli and Fedor (Ted) Lisitsyn

The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details

January 2021 (Revised March 2021)
Exercise

E-Commerce Analytics for CPG Firms (C): Free Delivery Terms

By: Ayelet Israeli and Fedor (Ted) Lisitsyn

The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details

January 2021 (Revised June 2023)
Case

Biobot Analytics

By: Raymond Kluender, Joshua Krieger and Mitchell Weiss

In 2017, Newsha Ghaeli and Mariana Matus were deciding whether to leave their labs at the Massachusetts Institute of Technology, put other job opportunities aside, and dive full-time into founding a wastewater analysis start-up, Biobot. Ghaeli, an architect, and Matus,... View Details

Keywords: Entrepreneurship; Information Technology; City; Analytics and Data Science; Personal Development and Career; Technology Industry; Utilities Industry; Health Industry; Information Technology Industry; Information Industry; Biotechnology Industry; United States; Kuwait; Korean Peninsula

June 2021
Article

From Predictions to Prescriptions: A Data-driven Response to COVID-19

By: Dimitris Bertsimas, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg and Cynthia Zeng

The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at... View Details

Keywords: COVID-19; Health Pandemics; AI and Machine Learning; Forecasting and Prediction; Analytics and Data Science

January 2021
Article

Using Models to Persuade

By: Joshua Schwartzstein and Adi Sunderam

We present a framework where "model persuaders" influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model... View Details

Keywords: Model Persuasion; Analytics and Data Science; Forecasting and Prediction; Mathematical Methods; Framework

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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

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

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

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

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

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

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