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(971)
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Show Results For
- All HBS Web
(971)
- News (133)
- Research (714)
- Events (8)
- Multimedia (4)
- Faculty Publications (547)
- 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
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.)
- 01 Dec 2014
- News
Making Big Data Fashionable
get designs to consumers in as little as four weeks—and at an affordable price. In 2012, Moon—who has a background in fashion design, investment banking, corporate strategy, and social commerce startups—launched Trendalytics, a visual View Details
- Teaching Interest
Overview
Paul is primarily interested in teaching data science to management students through the case method. This includes technical topics (programming and statistics) as well as higher-level management issues (digital transformation, data governance, etc.) As a research... View Details
Keywords: A/B Testing; AI; AI Algorithms; AI Creativity; Algorithm; Algorithm Bias; Algorithmic Bias; Algorithmic Fairness; Algorithms; Analytics; Application Program Interface; Artificial Intelligence; Causality; Causal Inference; Computing; Computers; Data Analysis; Data Analytics; Data Architecture; Data As A Service; Data Centers; Data Governance; Data Labeling; Data Management; Data Manipulation; Data Mining; Data Ownership; Data Privacy; Data Protection; Data Science; Data Science And Analytics Management; Data Scientists; Data Security; Data Sharing; Data Strategy; Data Visualization; Database; Data-driven Decision-making; Data-driven Management; Data-driven Operations; Datathon; Economics Of AI; Economics Of Innovation; Economics Of Information System; Economics Of Science; Forecast; Forecast Accuracy; Forecasting; Forecasting And Prediction; Information Technology; Machine Learning; Machine Learning Models; Prediction; Prediction Error; Predictive Analytics; Predictive Models; Analysis; AI and Machine Learning; Analytics and Data Science; Applications and Software; Digital Transformation; Information Management; Digital Strategy; Technology Adoption
- 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.
- August 2015 (Revised January 2017)
- Technical Note
From Correlation to Causation
By: Feng Zhu and Karim R. Lakhani
To make sound business decisions, managers must be comfortable with the concepts of correlation and causation. This background note provides an overview of correlation and causation using examples and explains why the former does not imply the latter. It also describes... View Details
Zhu, Feng, and Karim R. Lakhani. "From Correlation to Causation." Harvard Business School Technical Note 616-009, August 2015. (Revised January 2017.)
- January 2019
- Supplement
Understanding the Brand Equity of Nestlé Crunch Bar (B): Data Analysis
By: Jill Avery and Gerald Zaltman
In early 2018, Nestlé announced the sale of its U.S. candy-making division and a select collection of 20 of its confectionery brands, including the Nestlé Crunch Bar, to Ferrero SpA for $2.8 billion. Luckily, an old consumer research study on the Nestlé Crunch Bar... View Details
Keywords: Brand Management; Market Research; Brand Positioning; Value Proposition; Consumer Products; Fast Moving Consumer Goods; Qualitative Methods; Zaltman Metaphor Elicitation Technique; ZMET; Data Analysis; Marketing; Marketing Strategy; Brands and Branding; Consumer Behavior; Marketing Communications; Analytics and Data Science; Analysis; Consumer Products Industry; Food and Beverage Industry; Advertising Industry; United States; North America; Italy
Avery, Jill, and Gerald Zaltman. "Understanding the Brand Equity of Nestlé Crunch Bar (B): Data Analysis." Harvard Business School Supplement 519-062, January 2019.
- 21 Jun 2018
- Video
KPMA HBX Live Cracking the Data Aggregation Problem - Gabriel Eichler
- April 2006
- Background Note
Informing Service Management with Customer Data
By: Frances X. Frei and Dennis Campbell
Taught as the third module in a Harvard Business School course on Managing Service Operations. Explores the role of data analysis in ongoing service management. Describes how to realize the maximum amount of value from analyses and use this information in... View Details
Keywords: Decision Making; Design; Analytics and Data Science; Service Operations; Mathematical Methods; Value
Frei, Frances X., and Dennis Campbell. "Informing Service Management with Customer Data." Harvard Business School Background Note 606-097, April 2006.
- September 2016 (Revised May 2018)
- Case
Zurich Insurance: Global Job Structure and Data Analysis
By: Boris Groysberg and Katherine Connolly
Zurich Insurance was undergoing organizational change after implementing five new people practices focused on manager development, diversity and inclusion, job model and data analytics, recruitment, and talent pipeline. The case “Zurich Insurance: Fostering Key People... View Details
Keywords: Managing Change; Organizational Behavior; Organizational Architecture; Organizational Change and Adaptation; Leadership; Human Capital; Change Management; Organizational Structure; Insurance; Organizational Culture; Globalization; Human Resources; Insurance Industry
Groysberg, Boris, and Katherine Connolly. "Zurich Insurance: Global Job Structure and Data Analysis." Harvard Business School Case 417-038, September 2016. (Revised May 2018.)
- February 2017 (Revised August 2018)
- Case
Sarah Powers at Automated Precision Products
By: Jeffrey T. Polzer, Michael Norris, Julia Kelley and Kristina Tobio
In 2017, Sarah Powers, VP of Sales at an automation hardware firm, is trying to understand why some members of her sales team have been underperforming. She is tasked with analyzing her firm’s email and calendar data to try to find relationships between communications... View Details
Keywords: People Analytics; Sales Attainment; Communication Networks; Data; Human Resources; Business Processes; Sales; Communication; Analytics and Data Science; Analysis; Industrial Products Industry; Manufacturing Industry; United States
Polzer, Jeffrey T., Michael Norris, Julia Kelley, and Kristina Tobio. "Sarah Powers at Automated Precision Products." Harvard Business School Case 417-072, February 2017. (Revised August 2018.)
- February 2021
- Tutorial
T-tests: Theory and Practice
This video provides an introduction to hypothesis testing, sampling, t-tests, and p-values. It provides examples of A/B testing and t-testing to assess whether difference between two groups are statistically significant. This video can be assigned in conjunction with... View Details
- May 2014
- Article
Incorporating Field Data into Archival Research
By: Eugene F. Soltes
I explore the use of field data in conjunction with archival evidence by examining Iliev, Miller, and Roth's (2014) analysis of an amendment to the Securities Exchange Act of 1934. This regulatory amendment allowed depositary banks to cross-list firms without the... View Details
Soltes, Eugene F. "Incorporating Field Data into Archival Research." Journal of Accounting Research 52, no. 2 (May 2014): 521–540.
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
- 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
- 2022
- Article
Data Poisoning Attacks on Off-Policy Evaluation Methods
By: Elita Lobo, Harvineet Singh, Marek Petrik, Cynthia Rudin and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are a crucial tool for evaluating policies in high-stakes domains such as healthcare, where exploration is often infeasible, unethical, or expensive. However, the extent to which such methods can be trusted under adversarial threats... View Details
Lobo, Elita, Harvineet Singh, Marek Petrik, Cynthia Rudin, and Himabindu Lakkaraju. "Data Poisoning Attacks on Off-Policy Evaluation Methods." Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 38th (2022): 1264–1274.
- 01 Jun 2023
- News
Bridging the ESG Data Gap
ecosystem. It provides students and alumni from across Harvard’s 13 schools with wide-ranging resources and support for creating their own ventures and solving problems through innovation. During Metric’s incubation at the i-lab, Murday developed View Details
Keywords: Deborah Blagg
- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
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
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.
- November 2019
- Article
How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework
By: Doug J. Chung, Byungyeon Kim and Byoung G. Park
This paper evaluates the short- and long-term value of sales representatives’ detailing visits to different types of physicians. By understanding the dynamic effect of sales calls across heterogeneous physicians, we provide guidance on the design of optimal call... View Details
Keywords: Nerlove-Arrow Framework; Stock-of-goodwill; Dynamic Panel Data; Serial Correlation; Instrumental Variables; Sales Effectiveness; Detailing; Analytics and Data Science; Sales; Analysis; Performance Effectiveness; Pharmaceutical Industry
Chung, Doug J., Byungyeon Kim, and Byoung G. Park. "How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework." Management Science 65, no. 11 (November 2019): 5197–5218.
- September 2019
- Case
Starling Trust Sciences: Measuring Trust in Organizations
By: Aiyesha Dey, Jonas Heese and James Weber
Stephen Scott needed to decide whether to keep his behavioral analytics startup in the people analytics sector or shift his company into the RegTech sector. Starling had develop technology that enabled its customers to anticipate and shape the behavior of their... View Details
Keywords: Behavioral Analytics; Financial Institutions; Banks and Banking; Entrepreneurship; Strategy; Banking Industry; Consulting Industry; Information Technology Industry; United States; United Kingdom
Dey, Aiyesha, Jonas Heese, and James Weber. "Starling Trust Sciences: Measuring Trust in Organizations." Harvard Business School Case 120-006, September 2019.