Filter Results:
(419)
Show Results For
- All HBS Web
(1,010)
- Faculty Publications (419)
Show Results For
- All HBS Web
(1,010)
- Faculty Publications (419)
- March 2024
- Supplement
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Bruce Hardie, Peter S. Fader and Michael Ross
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an... View Details
- March 2024
- Supplement
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Bruce Hardie, Peter S. Fader and Michael Ross
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an... View Details
- March 2024
- Teaching Note
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Peter S. Fader, Bruce Hardie and Michael Ross
Teaching Note for HBS Case No. 524-046. This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in... View Details
- March 2024
- Case
Madrigal: Conducting a Customer-Base Audit
By: Eva Ascarza, Bruce Hardie, Michael Ross and Peter S. Fader
This case presents a scenario where Madrigal, a U.S. retailer with a rich 20-year history and a solid loyalty program, faces a turning point with the arrival of a new CEO. This leadership change reveals a critical gap in understanding the customer base, prompting an... View Details
Keywords: Customer Relationship Management; Analytics and Data Science; Growth and Development Strategy; Customer Value and Value Chain; Retail Industry; United States
Ascarza, Eva, Bruce Hardie, Michael Ross, and Peter S. Fader. "Madrigal: Conducting a Customer-Base Audit." Harvard Business School Case 524-046, March 2024.
- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I. Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details
Liang, Biyonka, and Iavor I. Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
- 2024
- Working Paper
Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference
By: Michael Lindon, Dae Woong Ham, Martin Tingley and Iavor I. Bojinov
Linear regression adjustment is commonly used to analyze randomized controlled experiments due to its efficiency and robustness against model misspecification. Current testing and interval estimation procedures leverage the asymptotic distribution of such estimators to... View Details
Lindon, Michael, Dae Woong Ham, Martin Tingley, and Iavor I. Bojinov. "Anytime-Valid Inference in Linear Models and Regression-Adjusted Causal Inference." Harvard Business School Working Paper, No. 24-060, March 2024.
- 2023
- Working Paper
Design-Based Inference for Multi-arm Bandits
By: Dae Woong Ham, Iavor I. Bojinov, Michael Lindon and Martin Tingley
Multi-arm bandits are gaining popularity as they enable real-world sequential decision-making across application areas, including clinical trials, recommender systems, and online decision-making. Consequently, there is an increased desire to use the available... View Details
Ham, Dae Woong, Iavor I. Bojinov, Michael Lindon, and Martin Tingley. "Design-Based Inference for Multi-arm Bandits." Harvard Business School Working Paper, No. 24-056, March 2024.
- February 2024
- Teaching Note
AB InBev: Brewing Up Forecasts during COVID-19
By: Mark Egan and C. Fritz Foley
Teaching Note for HBS Case No. 224-020. 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... View Details
- February 6, 2024
- Article
Find the AI Approach That Fits the Problem You’re Trying to Solve
By: George Westerman, Sam Ransbotham and Chiara Farronato
AI moves quickly, but organizations change much more slowly. What works in a lab may be wrong for your company right now. If you know the right questions to ask, you can make better decisions, regardless of how fast technology changes. You can work with your technical... View Details
Keywords: Technology Adoption; AI and Machine Learning; Organizational Change and Adaptation; Technological Innovation; Analytics and Data Science
Westerman, George, Sam Ransbotham, and Chiara Farronato. "Find the AI Approach That Fits the Problem You’re Trying to Solve." Harvard Business Review Digital Articles (February 6, 2024).
- February 2024
- Case
ReSpo.Vision: The Kickstart of an AI Sports Revolution
By: Paul A. Gompers, Elena Corsi and Nikolina Jonsson
This case study explores the growth journey of Polish computer vision sports start-up ReSpo.Vision in an emerging entrepreneurial ecosystem. By providing 3D data and analysis to soccer clubs, ReSpo.Vision achieved significant milestones with a €1 million seed round, an... View Details
Keywords: Business Startups; Business Plan; Experience and Expertise; Talent and Talent Management; Decisions; Decision Choices and Conditions; Forecasting and Prediction; Entrepreneurship; Venture Capital; AI and Machine Learning; Analytics and Data Science; Applications and Software; Business Strategy; Sports Industry; Technology Industry; Poland; Europe
Gompers, Paul A., Elena Corsi, and Nikolina Jonsson. "ReSpo.Vision: The Kickstart of an AI Sports Revolution." Harvard Business School Case 824-151, February 2024.
- February 2024 (Revised February 2024)
- Teaching Note
Travelogo: Understanding Customer Journeys
By: Eva Ascarza and Ta-Wei Huang
Teaching Note for HBS Exercise 524-044. The exercise aims to teach students about 1) Customer Segmentation; and 2) constructing buying personas, 3) Get actionable insights from clickstream data. View Details
- February 2024
- Teaching Note
CityScore: Big Data Comes to Boston
By: Boris Groysberg and Sarah L. Abbott
Teaching Note for HBS Case No. 422-050. In 2016, Mayor Marty Walsh of Boston introduced CityScore, a data dashboard that measured the city’s progress across a range of metrics. View Details
- February 2024
- Module Note
Data-Driven Marketing in Retail Markets
By: Ayelet Israeli
This note describes an eight-class sessions module on data-driven marketing in retail markets. The module aims to familiarize students with core concepts of data-driven marketing in retail, including exploring the opportunities and challenges, adopting best practices,... View Details
Keywords: Data; Data Analytics; Retail; Retail Analytics; Data Science; Business Analytics; "Marketing Analytics"; Omnichannel; Omnichannel Retailing; Omnichannel Retail; DTC; Direct To Consumer Marketing; Ethical Decision Making; Algorithmic Bias; Privacy; A/B Testing; Descriptive Analytics; Prescriptive Analytics; Predictive Analytics; Analytics and Data Science; E-commerce; Marketing Channels; Demand and Consumers; Marketing Strategy; Retail Industry
Israeli, Ayelet. "Data-Driven Marketing in Retail Markets." Harvard Business School Module Note 524-062, February 2024.
- January 2024
- Supplement
Winning Business at Russell Reynolds
By: Ethan Bernstein and Cara Mazzucco
In an effort to make compensation drive collaboration, Russell Reynolds Associates’ (RRA) CEO Clarke Murphy sought to re-engineer the bonus system for his executive search consultants in 2016. As his HR analytics guru, Kelly Smith, points out, that risks upsetting—and... View Details
Keywords: Restructuring; Talent and Talent Management; Compensation and Benefits; Growth and Development Strategy; Organizational Change and Adaptation; Organizational Culture; Performance Evaluation; Motivation and Incentives; Consulting Industry
Bernstein, Ethan, and Cara Mazzucco. "Winning Business at Russell Reynolds." Harvard Business School Multimedia/Video Supplement 424-704, January 2024.
- January 2024 (Revised February 2024)
- Course Overview Note
Managing Customers for Growth: Course Overview for Students
By: Eva Ascarza
Managing Customers for Growth (MCG) is a 14-session elective course for second-year MBA students at Harvard Business School. It is designed for business professionals engaged in roles centered on customer-driven growth activities. The course explores the dynamics of... View Details
Keywords: Customer Relationship Management; Decision Making; Analytics and Data Science; Growth Management; Telecommunications Industry; Technology Industry; Financial Services Industry; Education Industry; Travel Industry
Ascarza, Eva. "Managing Customers for Growth: Course Overview for Students." Harvard Business School Course Overview Note 524-032, January 2024. (Revised February 2024.)
- January 2024 (Revised February 2024)
- Exercise
Travelogo: Understanding Customer Journeys
By: Eva Ascarza, Nicolas Padilla and Oded Netzer
In late May 2023, Sarah Merino, the newly appointed manager of the Customer Insights group at Travelogo—an online travel booking platform—initiates a comprehensive analysis of clickstream data to understand the varied behaviors and needs of their users. In preparation... View Details
Keywords: Customer Relationship Management; Analysis; Analytics and Data Science; Marketing Strategy; Segmentation; Consumer Behavior; Travel Industry; United States
Ascarza, Eva, Nicolas Padilla, and Oded Netzer. "Travelogo: Understanding Customer Journeys." Harvard Business School Exercise 524-044, January 2024. (Revised February 2024.)
- January 2024 (Revised May 2024)
- Case
PortageBay and ESG Analytics
By: Vikram S. Gandhi and Radhika Kak
In 2023, sustainable investors faced several challenges. The first was the lack of access to standardized and vetted environmental, social, and governance (ESG) data, and equally, the interpretation of this data into investment-useful insights. Reducing reliance on... View Details
Keywords: ESG Ratings; Investment Funds; Governance; Environmental Sustainability; Corporate Social Responsibility and Impact
Gandhi, Vikram S., and Radhika Kak. "PortageBay and ESG Analytics." Harvard Business School Case 324-065, January 2024. (Revised May 2024.)
- 2024
- Working Paper
The Impact of Culture Consistency on Subunit Outcomes
By: Jasmijn Bol, Robert Grasser, Serena Loftus and Tatiana Sandino
We examine the association between subunit culture consistency—defined as the congruence between the organizational values espoused by top management and those perceived and practiced by subunit employees—and subunit outcomes. Using data from 235 subunits of a... View Details
Bol, Jasmijn, Robert Grasser, Serena Loftus, and Tatiana Sandino. "The Impact of Culture Consistency on Subunit Outcomes." Working Paper, December 2024.
- 2023
- Working Paper
Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach
By: Ta-Wei Huang and Eva Ascarza
Data-driven targeted interventions have become a powerful tool for organizations to optimize business outcomes
by utilizing individual-level data from experiments. A key element of this process is the estimation
of Conditional Average Treatment Effects (CATE), which... View Details
Huang, Ta-Wei, and Eva Ascarza. "Debiasing Treatment Effect Estimation for Privacy-Protected Data: A Model Auditing and Calibration Approach." Harvard Business School Working Paper, No. 24-034, December 2023.
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
Keywords: Large Language Model; AI and Machine Learning; Analytics and Data Science; Health Industry
Liu, Junling, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. "Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset." Conference on Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track 36 (2023).