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Show Results For
-
All HBS Web
(975)
- News (139)
- Research (672)
- Events (6)
- Multimedia (4)
- Faculty Publications (515)
- Research Summary
Overview
By: Ayelet Israeli
Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data...
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- 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...
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Tadikonda, Satish. "HealthVerity: Real World Data and Evidence." Harvard Business School Case 824-019, July 2023.
- October 2017 (Revised November 2017)
- Case
NYC311
By: Constantine E. Kontokosta, Mitchell Weiss, Christine Snively and Sarah Gulick
Joe Morrisroe, executive director for NYC311, had some gut instincts but no definitive answer to the question he was just asked by one of the mayor’s deputies: “Are some communities being underserved by 311? How do we know we are hearing from the right people?” Founded...
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Keywords:
New York City;
NYC;
311;
NYC311;
Big Data;
Equal Access;
Bias;
Data Analysis;
Public Entrepreneurship;
Urban Informatics;
Predictive Analytics;
Chief Data Officer;
Data Analytics;
Cities;
City Leadership;
Analytics and Data Science;
Analysis;
Prejudice and Bias;
Entrepreneurship;
Public Sector;
City;
Public Administration Industry;
New York (city, NY)
- November–December 2022
- Article
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...
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Keywords:
Descriptive Analytics;
Big Data;
Synthetic Control;
E-commerce;
Online Retail;
Difference-in-differences;
Martech;
Internet and the Web;
Analytics and Data Science;
Performance;
Marketing;
Retail Industry
Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Marketing Science 41, no. 6 (November–December 2022): 1074–1096.
- 01 Mar 2018
- News
Democratizing Data to Favor Farmers
as much for the same seeds. That knowledge would help farmers haggle with dealers, but the real insight would come from analytics that go beyond consolidating seed prices to measuring a seed variety’s potential success. The most important...
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Keywords:
Sasha Issenberg
- Web
Analytics | Baker Library | Bloomberg Center | Harvard Business School
refine the tracking, analysis and reporting of user behaviors on your website or other digital initiative. We are available to train you or your team to use Adobe Analytics, and can work with you to set up custom reports and with IT to implement View Details
- Article
Algorithms Need Managers, Too
By: Michael Luca, Jon Kleinberg and Sendhil Mullainathan
Algorithms are powerful predictive tools, but they can run amok when not applied properly. Consider what often happens with social media sites. Today many use algorithms to decide which ads and links to show users. But when these algorithms focus too narrowly on...
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Keywords:
Machine Learning;
Algorithms;
Predictive Analytics;
Management;
Big Data;
Analytics and Data Science
Luca, Michael, Jon Kleinberg, and Sendhil Mullainathan. "Algorithms Need Managers, Too." Harvard Business Review 94, nos. 1/2 (January–February 2016): 96–101.
- 15 May 2017
- Sharpening Your Skills
The Promises and Limitations of Big Data
Source: peterhowell Although many people claim we have entered the era of big data, research firms tell us that most collected information is never used. It sits uncleaned, unanalyzed, unused in databases. But when data View Details
- August 2020 (Revised September 2020)
- Technical Note
Assessing Prediction Accuracy of Machine Learning Models
The note introduces a variety of methods to assess the accuracy of machine learning prediction models. The note begins by briefly introducing machine learning, overfitting, training versus test datasets, and cross validation. The following accuracy metrics and tools...
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Keywords:
Machine Learning;
Statistics;
Econometric Analyses;
Experimental Methods;
Data Analysis;
Data Analytics;
Forecasting and Prediction;
Analytics and Data Science;
Analysis;
Mathematical Methods
Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.)
- July 2013
- Case
Sample6: Innovating to Make Food Safer
By: Robert F. Higgins and Kirsten Kester
Tim Curran, CEO of Sample6, a start-up biotechnology company developing a novel food safety diagnostics platform, must decide how to partner with food industry players. How can he best convince leaders in this mature industry to adopt a new technology and improve food...
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Keywords:
Data Analytics;
Food Safety;
Biotechnology;
Nutrition;
Entrepreneurship;
Product;
Partners and Partnerships;
Food;
Technological Innovation;
Business Startups;
Governing Rules, Regulations, and Reforms;
Product Development;
Agribusiness;
Information Technology;
Globalization;
Performance Improvement;
Safety;
Technology Adoption;
Agriculture and Agribusiness Industry;
Food and Beverage Industry;
Biotechnology Industry;
Information Industry;
United States;
Boston;
Massachusetts
Higgins, Robert F., and Kirsten Kester. "Sample6: Innovating to Make Food Safer." Harvard Business School Case 814-014, July 2013.
- Teaching Interest
Overview
By: John A. Deighton
I teach about the ecosystem of big data, the role of data in advertising and creative industries, and customer management and personal privacy in an era of individual addressability.
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- 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
Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Harvard Business School Working Paper, No. 21-067, November 2020. (Revised December 2021. Accepted at Marketing Science.)
- 2023
- Working Paper
Feature Importance Disparities for Data Bias Investigations
By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection...
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Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
- November 1998
- Article
Modeling Large Data Sets in Marketing
By: Sridhar Balasubramanian, Sunil Gupta, Wagner Kamakura and Michel Wedel
Balasubramanian, Sridhar, Sunil Gupta, Wagner Kamakura, and Michel Wedel. "Modeling Large Data Sets in Marketing." Special Issue on Large Data Sets in Business Economics. Statistica Neerlandica 52, no. 3 (November 1998).
- Article
Mitigating Bias in Adaptive Data Gathering via Differential Privacy
By: Seth Neel and Aaron Leon Roth
Data that is gathered adaptively—via bandit algorithms, for example—exhibits bias. This is true both when gathering simple numeric valued data—the empirical means kept track of by stochastic bandit algorithms are biased downwards—and when gathering more complicated...
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Neel, Seth, and Aaron Leon Roth. "Mitigating Bias in Adaptive Data Gathering via Differential Privacy." Proceedings of the International Conference on Machine Learning (ICML) 35th (2018).
- Article
Digital Ubiquity: How Connections, Sensors, and Data Are Revolutionizing Business
By: Marco Iansiti and Karim R. Lakhani
When Google bought Nest, a maker of digital thermostats, for $3.2 billion just a few months ago, it was a clear indication that digital transformation and connection are spreading across even the most traditional industrial segments and creating a staggering array of...
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Keywords:
Digital Innovation;
Digitization;
Industrial Internet;
Technological Innovation;
Production;
Competitive Strategy;
Engineering;
Aerospace Industry
Iansiti, Marco, and Karim R. Lakhani. "Digital Ubiquity: How Connections, Sensors, and Data Are Revolutionizing Business." Harvard Business Review 92, no. 11 (November 2014): 90–99.
- October 2015 (Revised October 2016)
- Case
Building Watson: Not So Elementary, My Dear! (Abridged)
By: Willy C. Shih
This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the...
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Keywords:
Analytics;
Big Data;
Business Analytics;
Product Development Strategy;
Machine Learning;
Machine Intelligence;
Artificial Intelligence;
Product Development;
AI and Machine Learning;
Information Technology;
Analytics and Data Science;
Information Technology Industry;
United States
Shih, Willy C. "Building Watson: Not So Elementary, My Dear! (Abridged)." Harvard Business School Case 616-025, October 2015. (Revised October 2016.)
- 22 May 2014
- News
For Website Personalization, Simple Is the New Sexy
- 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.