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

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2023
Working Paper

The Customer Journey as a Source of Information

By: Nicolas Padilla, Eva Ascarza and Oded Netzer

In the face of heightened data privacy concerns and diminishing third-party data access, firms are placing increased emphasis on first-party data (1PD) for marketing decisions. However, in environments with infrequent purchases, reliance on past purchases 1PD... View Details

Keywords: Customer Journey; Privacy; Consumer Behavior; Analytics and Data Science; AI and Machine Learning; Customer Focus and Relationships

September 2023 (Revised January 2024)
Case

AB InBev: Brewing Up Forecasts during COVID-19

By: Mark Egan, C. Fritz Foley, Esel Cekin and Emilie Billaud

In July 2021, the CEO of AB InBev's European operations and his team strategized to position the company for success post-pandemic. As the world's largest beer company, boasting over 500 brands, revenue of $46 billion, and a workforce of 160,000 in 2020, AB InBev... View Details

September 2023 (Revised December 2023)
Case

TetraScience: Noise and Signal

By: Thomas R. Eisenmann and Tom Quinn

In 2019, TetraScience CEO “Spin” Wang needed advice. Five years earlier, he had cofounded a startup that saw early success with a hardware product designed to help laboratory scientists in the biotechnology and pharmaceutical spaces more easily collect data from... View Details

Keywords: Entrepreneurship; Business Growth and Maturation; Business Organization; Restructuring; Forecasting and Prediction; Digital Platforms; Analytics and Data Science; AI and Machine Learning; Organizational Structure; Network Effects; Competitive Strategy; Biotechnology Industry; Pharmaceutical Industry; United States; Boston

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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2025
Working Paper

Global Harms, Local Profits: How the Uneven Costs of Natural Disasters Affect Support for Green Political Platforms

By: Silvia Pianta and Paula Rettl

Large-scale fires are becoming increasingly common due to climate change. While conventional wisdom suggests that firsthand experiences with natural disasters foster green coalitions by raising awareness of environmental degradation, we propose an alternative... View Details

Keywords: Climate Impact; Politics; Environmental Issues; Environmental Protection; Economic Analysis; Economic Behavior; Economic Geography; Economy; Economics; Climate Change; Environmental Management; Political Elections; Natural Disasters; Green Technology; Environmental Sustainability; Latin America; Brazil

2023
Article

On Minimizing the Impact of Dataset Shifts on Actionable Explanations

By: Anna P. Meyer, Dan Ley, Suraj Srinivas and Himabindu Lakkaraju

The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical challenges arise when providing such actionable explanations in practice. For instance, models... View Details

Keywords: Mathematical Methods; Analytics and Data Science

August 2023 (Revised March 2024)
Case

Arla Foods: Data-Driven Decarbonization (A)

By: Michael Parzen, Michael W. Toffel, Susan Pinckney and Amram Migdal

The case describes Arla’s history, in particular its climate change mitigation efforts, and how it implemented a price incentive system to motivate individual farms to implement scope 1 greenhouse gas emissions mitigation measures and receive a higher milk price. The... View Details

August 2023 (Revised January 2024)
Supplement

Arla Foods: Data-Driven Decarbonization (B)

By: Michael Parzen, Michael W. Toffel, Susan Pinckney and Amram Migdal

The case describes Arla’s history, in particular its climate change mitigation efforts, and how it implemented a price incentive system to motivate individual farms to implement scope 1 greenhouse gas emissions mitigation measures and receive a higher milk price. The... View Details

August 2023
Case

Beamery: Using Skills and AI to Modernize HR

By: Boris Groysberg, Alexis Lefort, Susan Pinckney and Carolina Bartunek

Unicorn human relationships startup Beamery evaluates it's growth versus depth strategy as its strategic partners and customers could become future competitors in a quickly changing AI based human resources and talent management industry View Details

2023
Article

Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten

By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma

The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details

Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms

July 2023 (Revised May 2024)
Case

Vytal: Packaging-as-a-Service

By: George Serafeim, Michael W. Toffel, Lena Duchene and Daniela Beyersdorfer

The Germany-based startup Vytal operated the largest digital-native reusable packaging-as-a-service network globally, having raised nearly €15 million, established a large network of restaurant partners, and prevented the use of millions of single-use take-out food... View Details

July 2023
Case

HealthVerity: Real World Data and Evidence

By: Satish Tadikonda

Andrew Kress (CEO and founder) and his team had built a promising marketplace business at HealthVerity serving its core market in healthcare, with a focus on pharmaceutical R&D and services. Thus far, HealthVerity’s products had been unique to the pharma and pharma... View Details

Keywords: Growth and Development Strategy; Market Entry and Exit; Product Marketing

July 2023 (Revised July 2023)
Background Note

Generative AI Value Chain

By: Andy Wu and Matt Higgins

Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details

Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value

2023
Chapter

Inflation and Misallocation in New Keynesian Models

By: Alberto Cavallo, Francesco Lippi and Ken Miyahara

The New Keynesian framework implies that sluggish price adjustment results in a distorted allocation of resources. We use a simple model to quantify these unobservable distortions, using data that depict the price-setting behavior of firms, specifically the frequency... View Details

Keywords: Macroeconomics; Inflation and Deflation; Price; Analytics and Data Science; Cost

July 2023
Article

So, Who Likes You? Evidence from a Randomized Field Experiment

By: Ravi Bapna, Edward McFowland III, Probal Mojumder, Jui Ramaprasad and Akhmed Umyarov

With one-third of marriages in the United States beginning online, online dating platforms have become important curators of the modern social fabric. Prior work on online dating has elicited two critical frictions in the heterosexual dating market. Women, governed by... View Details

Keywords: Online Dating; Internet and the Web; Analytics and Data Science; Gender; Emotions; Social and Collaborative Networks

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July 2023
Article

Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations

By: Dawson Beutler, Alex Billias, Sam Holt, Josh Lerner and TzuHwan Seet

In 2001, Dean Takahashi and Seth Alexander of the Yale University Investments Office developed a deterministic model for estimating future cash flows and valuations for the Yale endowment’s private equity portfolio. Their model, which is simple and intuitive, is still... View Details

Keywords: Forecasting and Prediction; Investment Portfolio; Analytics and Data Science

June 2023
Simulation

Artea Dashboard and Targeting Policy Evaluation

By: Ayelet Israeli and Eva Ascarza

Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea... View Details

2023
Working Paper

Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation

By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov

Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to... View Details

Keywords: Performance Evaluation; Research and Development; Analytics and Data Science; Consumer Behavior

May–June 2023
Article

Analytics for Marketers: When to Rely on Algorithms and When to Trust Your Gut

By: Fabrizio Fantini and Das Narayandas

Advanced analytics can help companies solve a host of management problems, including those related to marketing, sales, and supply-chain operations, which can lead to a sustainable competitive advantage. But as more data becomes available and advanced analytics are... View Details

Keywords: Analytics and Data Science; Decision Making

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2023
Article

Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators

By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill

Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details

Keywords: Regression Discontinuity Design; Analytics and Data Science; AI and Machine Learning

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