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- November 2023
- Article
Federated Electronic Health Records for the European Health Data Space
By: René Raab, Arne Küderle, Anastasiya Zakreuskaya, Ariel Dora Stern, Jochen Klucken, Georgios Kaissis, Daniel Rueckert, Susanne Boll, Roland Eils, Harald Wagener and Bjoern Eskofier
The European Commission's draft for the European Health Data Space (EHDS) aims to empower citizens to access their personal health data and share it with physicians and other health-care providers. It further defines procedures for the secondary use of electronic...
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Keywords:
Analytics and Data Science;
Cybersecurity;
Information Management;
Knowledge Sharing;
Knowledge Use and Leverage;
Health Industry
Raab, René, Arne Küderle, Anastasiya Zakreuskaya, Ariel Dora Stern, Jochen Klucken, Georgios Kaissis, Daniel Rueckert, Susanne Boll, Roland Eils, Harald Wagener, and Bjoern Eskofier. "Federated Electronic Health Records for the European Health Data Space." Lancet Digital Health 5, no. 11 (November 2023): e840–e847.
- 2023
- Working Paper
Cost-Efficient Decarbonization of Portland Cement Production
By: Gunther Glenk, Anton Kelnhofer, Rebecca Meier and Stefan Reichelstein
Accounting for nearly 8% of global annual carbon dioxide (CO2) emissions, the cement industry is considered difficult to decarbonize. While a sizeable number of abatement levers for Portland cement production is becoming technologically ready for deployment, many are...
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Keywords:
Decarbonization;
Carbon Abatement;
Carbon Accounting;
Carbon Emissions;
Carbon Regulation;
Carbon Tax;
Net-zero Emissions;
Management;
Environmental Management;
Sustainable Cities;
Accounting;
Management Analysis, Tools, and Techniques;
Environmental Accounting;
Energy;
Environmental Sustainability;
Construction Industry;
Steel Industry;
Pulp and Paper Industry;
Real Estate Industry;
Consulting Industry;
Energy Industry;
Green Technology Industry;
Manufacturing Industry;
Utilities Industry;
Industrial Products Industry;
Europe;
North America;
South America;
Africa;
Asia
Glenk, Gunther, Anton Kelnhofer, Rebecca Meier, and Stefan Reichelstein. "Cost-Efficient Decarbonization of Portland Cement Production." Harvard Business School Working Paper, No. 24-025, October 2023. (TRR 266 Accounting for Transparency Working Paper Series, No. 120, May 2023.)
- September 2023 (Revised September 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...
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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...
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Srinivasan, Suraj, and Robin Seibert. "How the Best Chief Data Officers Create Value." Harvard Business Review (website) (September 13, 2023).
- 2023
- Working Paper
Large Shocks Travel Fast
By: Alberto Cavallo, Francesco Lippi and Ken Miyahara
We leverage the inflation upswing of 2022 and various granular datasets to identify robust price-setting patterns following a large supply shock. We show that the frequency of price changes increases dramatically after a large shock. We set up a parsimonious New...
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Keywords:
Macroeconomics;
Analytics and Data Science;
Inflation and Deflation;
Cost;
Mathematical Methods
Cavallo, Alberto, Francesco Lippi, and Ken Miyahara. "Large Shocks Travel Fast." NBER Working Paper Series, No. 31659, September 2023.
- 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...
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Meyer, Anna P., Dan Ley, Suraj Srinivas, and Himabindu Lakkaraju. "On Minimizing the Impact of Dataset Shifts on Actionable Explanations." Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 39th (2023): 1434–1444.
- August 2023
- Supplement
Arla Foods: Data-Driven Decarbonization (A)
By: Michael Parzen, Michael W. Toffel, Amram Migdal and Susan Pinckney
Arla implemented a data based price incentive systems to measure, track, and influence climate friendly changes to reduce CO2 emissions across the world’s fourth largest dairy cooperative.
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Keywords:
Dairy Industry;
Business Earnings;
Earnings Management;
Environmental Accounting;
Agribusiness;
Animal-Based Agribusiness;
Acquisition;
Mergers and Acquisitions;
Decision Making;
Decisions;
Voting;
Environmental Management;
Climate Change;
Environmental Regulation;
Environmental Sustainability;
Green Technology;
Pollution;
Moral Sensibility;
Values and Beliefs;
Financial Strategy;
Price;
Profit;
Revenue;
Food;
Geopolitical Units;
Global Strategy;
Ownership Type;
Cooperative Ownership;
Performance Efficiency;
Performance Evaluation;
Problems and Challenges;
Natural Environment;
Science-Based Business;
Business Strategy;
Commercialization;
Cooperation;
Corporate Strategy;
Food and Beverage Industry;
Agriculture and Agribusiness Industry;
Europe;
United Kingdom;
European Union;
Germany;
Denmark;
Sweden;
Luxembourg;
Belgium
- August 2023
- Case
Arla Foods: Data-Driven Decarbonization (A)
By: Michael Parzen, Michael W. Toffel, Susan Pinckney and Amram Migdal
Arla implemented a data based price incentive systems to measure, track, and influence climate friendly changes to reduce CO2 emissions across the world’s fourth largest dairy cooperative.
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Keywords:
Dairy Industry;
Business Earnings;
Agribusiness;
Animal-Based Agribusiness;
Acquisition;
Mergers and Acquisitions;
Decision Making;
Decisions;
Voting;
Environmental Management;
Climate Change;
Environmental Regulation;
Environmental Sustainability;
Green Technology;
Pollution;
Moral Sensibility;
Values and Beliefs;
Financial Strategy;
Price;
Profit;
Revenue;
Food;
Geopolitical Units;
Global Strategy;
Ownership Type;
Cooperative Ownership;
Performance Efficiency;
Performance Evaluation;
Problems and Challenges;
Natural Environment;
Science-Based Business;
Business Strategy;
Commercialization;
Cooperation;
Corporate Strategy;
Food and Beverage Industry;
Europe;
United Kingdom;
European Union;
Germany;
Denmark;
Sweden;
Luxembourg;
Belgium
- 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
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Keywords:
Acquisition;
Business Growth and Maturation;
Business Startups;
Competency and Skills;
Experience and Expertise;
Talent and Talent Management;
Customers;
Nationality;
Learning;
Entrepreneurship;
Corporate Entrepreneurship;
Social Entrepreneurship;
Human Resources;
Employee Relationship Management;
Recruitment;
Retention;
Selection and Staffing;
Values and Beliefs;
Cross-Cultural and Cross-Border Issues;
Analytics and Data Science;
Applications and Software;
Disruptive Innovation;
Technological Innovation;
Job Offer;
Job Search;
Job Design and Levels;
Employment;
Human Capital;
Europe;
United Kingdom;
United States
Groysberg, Boris, Alexis Lefort, Susan Pinckney, and Carolina Bartunek. "Beamery: Using Skills and AI to Modernize HR." Harvard Business School Case 424-004, August 2023.
- 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...
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Keywords:
Analytics and Data Science;
AI and Machine Learning;
Decision Making;
Governing Rules, Regulations, and Reforms
Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
- July 2023
- 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...
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Keywords:
Climate Change;
Climate Risk;
Digital;
Platform Strategies;
Data;
Packaging;
Sustainability;
Start-up;
Startup;
Entrepreneurship;
Entrepreneur;
Impact;
Circular;
Growth Strategy;
Innovation;
Environmental Sustainability;
Innovation and Invention;
Business Growth and Maturation;
Growth and Development Strategy;
Business Startups;
Resource Allocation;
Risk Management;
Adoption;
Strategy;
Performance Productivity;
Service Delivery;
Service Operations;
Supply Chain;
Distribution;
Green Technology Industry;
Service Industry;
Retail Industry;
Germany;
Europe
- 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...
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Keywords:
AI;
Artificial Intelligence;
Model;
Hardware;
Data Centers;
AI and Machine Learning;
Applications and Software;
Analytics and Data Science;
Value
Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
- 2022
- Article
Science-based Entrepreneurship in India: A Policy Glass (as yet) Quarter-Full
By: Tarun Khanna
India is celebrated for a resurgence of de novo entrepreneurship in recent decades. Entrants have engaged in creative risk-taking to provide market-based solutions for private or social needs despite not being scions of wealthy industrial or business families. In this...
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Khanna, Tarun. "Science-based Entrepreneurship in India: A Policy Glass (as yet) Quarter-Full." India Policy Forum 19 (2022): 1–53.
- 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...
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Keywords:
Online Dating;
Internet and the Web;
Analytics and Data Science;
Gender;
Emotions;
Social and Collaborative Networks
Bapna, Ravi, Edward McFowland III, Probal Mojumder, Jui Ramaprasad, and Akhmed Umyarov. "So, Who Likes You? Evidence from a Randomized Field Experiment." Management Science 69, no. 7 (July 2023): 3939–3957.
- 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...
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Beutler, Dawson, Alex Billias, Sam Holt, Josh Lerner, and TzuHwan Seet. "Takahashi-Alexander Revisited: Modeling Private Equity Portfolio Outcomes Using Historical Simulations." Journal of Portfolio Management 49, no. 7 (July 2023): 144–158.
- 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...
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Keywords:
Algorithm Bias;
Algorithmic Data;
Race And Ethnicity;
Experimentation;
Promotion;
Marketing And Society;
Big Data;
Privacy;
Data-driven Management;
Data Analysis;
Data Analytics;
E-Commerce Strategy;
Discrimination;
Targeted Advertising;
Targeted Policies;
Pricing Algorithms;
A/B Testing;
Ethical Decision Making;
Customer Base Analysis;
Customer Heterogeneity;
Coupons;
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
- 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...
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Keywords:
Performance Evaluation;
Research and Development;
Analytics and Data Science;
Consumer Behavior
Ham, Dae Woong, Michael Lindon, Martin Tingley, and Iavor Bojinov. "Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation." Harvard Business School Working Paper, No. 23-070, May 2023.
- 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...
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Fantini, Fabrizio, and Das Narayandas. "Analytics for Marketers: When to Rely on Algorithms and When to Trust Your Gut." Harvard Business Review 101, no. 3 (May–June 2023): 82–91.
- June 2020
- Article
Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure
By: Omar Isaac Asensio, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer and Sooji Ha
By displacing gasoline and diesel fuels, electric cars and fleets reduce emissions from the transportation sector, thus offering important public health benefits. However, public confidence in the reliability of charging infrastructure remains a fundamental barrier to...
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Keywords:
Environmental Sustainability;
Transportation;
Infrastructure;
Behavior;
AI and Machine Learning;
Demand and Consumers
Asensio, Omar Isaac, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer, and Sooji Ha. "Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure." Nature Sustainability 3, no. 6 (June 2020): 463–471.
- 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...
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Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.