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All HBS Web
(269)
- People (1)
- News (64)
- Research (143)
- Events (5)
- Multimedia (2)
- Faculty Publications (22)
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- October 2012
- Article
Data Scientist: The Sexiest Job of the 21st Century
Key to the effective use of big data are the analytical professionals known as "data scientists," who can both manipulate large and unstructured data sources and create insights from them. Data scientists are difficult to hire and retain, but their skills will be...
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Keywords:
Big Data;
Data Scientists;
Business Analytics;
Analytics and Data Science;
Mathematical Methods;
Jobs and Positions
Davenport, Thomas H., and D. J. Patil. "Data Scientist: The Sexiest Job of the 21st Century." Harvard Business Review 90, no. 10 (October 2012): 70–76.
- Winter 2017
- Article
Why Big Data Isn't Enough
By: Sen Chai and Willy C. Shih
There is a growing belief that sophisticated algorithms can explore huge databases and find relationships independent of any preconceived hypotheses. But in businesses that involve scientific research and technological innovation, this approach is misguided and...
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Keywords:
Big Data;
Science-based;
Science;
Scientific Research;
Data Analytics;
Data Science;
Data-driven Management;
Data Scientists;
Technological Innovation;
Analytics and Data Science;
Mathematical Methods;
Theory
Chai, Sen, and Willy C. Shih. "Why Big Data Isn't Enough." Art. 58227. MIT Sloan Management Review 58, no. 2 (Winter 2017): 57–61.
- 22 Feb 2022
- Research & Ideas
Lack of Female Scientists Means Fewer Medical Treatments for Women
Women are more likely to invent medical treatments for endometriosis, cervical cancer, and other female conditions, but the dearth of women scientists limits the potential for such life-saving innovations. Female research teams are 35...
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Keywords:
by Kristen Senz
- October 2020
- Article
The Elasticity of Science
By: Kyle Myers
This paper identifies the degree to which scientists are willing to change the direction of their work in exchange for resources. Data from the National Institutes of Health are used to estimate how scientists respond to targeted funding opportunities. Inducing a...
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Myers, Kyle. "The Elasticity of Science." American Economic Journal: Applied Economics 12, no. 4 (October 2020): 103–134.
- 26 Jul 2017
- Cold Call Podcast
The Revolution in Advertising: From Don Draper to Big Data
- March 2019
- Case
Wattpad
By: John Deighton and Leora Kornfeld
How to run a platform to match four million writers of stories to 75 million readers? Use data science. Make money by doing deals with television and filmmakers and book publishers. The case describes the challenges of matching readers to stories and of helping writers...
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Keywords:
Platform Businesses;
Creative Industries;
Publishing;
Data Science;
Machine Learning;
Collaborative Filtering;
Women And Leadership;
Managing Data Scientists;
Big Data;
Recommender Systems;
Digital Platforms;
Information Technology;
Intellectual Property;
Analytics and Data Science;
Publishing Industry;
Entertainment and Recreation Industry;
Canada;
United States;
Philippines;
Viet Nam;
Turkey;
Indonesia;
Brazil
Deighton, John, and Leora Kornfeld. "Wattpad." Harvard Business School Case 919-413, March 2019.
- 21 Aug 2017
- Lessons from the Classroom
Companies Love Big Data But Lack the Strategy To Use It Effectively
managers, HR specialists, and data scientists work together to use data to improve employee-related decisions and practices. New analytic approaches and new sources of digital...
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Keywords:
by Dina Gerdeman
- 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...
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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
- April 2002
- Case
In vivo to in vitro to in silico: Coping with Tidal Waves of Data at Biogen
By: Juan Enriquez-Cabot, Gary P. Pisano and Gaye Bok
Biogen is a successful biotech company facing a critical juncture. CEO John Mullen ponders how technological changes introduced into the research function will shape larger corporate decisions. This world in which biotechnology companies operated had changed...
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Keywords:
Change;
Decisions;
Product Development;
Research and Development;
Expansion;
Technology;
Biotechnology Industry
Enriquez-Cabot, Juan, Gary P. Pisano, and Gaye Bok. "In vivo to in vitro to in silico: Coping with Tidal Waves of Data at Biogen." Harvard Business School Case 602-122, April 2002.
- August 2018
- Article
Growth Through Heterogeneous Innovations
By: Ufuk Akcigit and William R. Kerr
We build a tractable growth model where multi-product incumbents invest in internal innovations to improve their existing products, while new entrants and incumbents invest in external innovations to acquire new product lines. External and internal innovations generate...
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Keywords:
Endogenous Growth;
Innovation;
Citations;
Scientists;
Entrepreneurs;
External;
Internal;
Patents;
Innovation Strategy;
Entrepreneurship;
Economic Growth;
Research and Development;
Science
Akcigit, Ufuk, and William R. Kerr. "Growth Through Heterogeneous Innovations." Journal of Political Economy 126, no. 4 (August 2018): 1374–1443.
- 2020
- Working Paper
Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?
By: Jacqueline N. Lane, Ina Ganguli, Patrick Gaule, Eva C. Guinan and Karim R. Lakhani
We investigate how knowledge similarity between two individuals is systematically related to the likelihood that a serendipitous encounter results in knowledge production. We conduct a natural field experiment at a medical research symposium, where we exogenously...
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Keywords:
Cognitive Similarity;
Knowledge Creation;
Knowledge Sharing;
Knowledge Dissemination;
Relationships
Lane, Jacqueline N., Ina Ganguli, Patrick Gaule, Eva C. Guinan, and Karim R. Lakhani. "Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?" Harvard Business School Working Paper, No. 20-058, November 2019. (Revised July 2020.)
- February 2014
- Case
BGI: Data-driven Research
By: Willy Shih and Sen Chai
BGI has the largest installed gene-sequencing capacity in the world, and to Zhang Gengyun, general manager of the Life Sciences Division, this represented an opportunity to apply his training as a plant breeder and his early career work as a biochemist to improving...
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Keywords:
Genomics;
Gene Sequencing;
Life Sciences;
Plant Breeding;
Human Genome Program;
Beijing Genomics Institute;
BGI;
Rice Genome;
Technological Innovation;
Innovation Strategy;
Research;
Research and Development;
Science;
Genetics;
Science-Based Business;
Strategy;
Commercialization;
Corporate Strategy;
Information Technology;
Applications and Software;
Agriculture and Agribusiness Industry;
Biotechnology Industry;
Food and Beverage Industry;
China;
United States
Shih, Willy, and Sen Chai. "BGI: Data-driven Research." Harvard Business School Case 614-056, February 2014.
- June 2021
- Article
Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?
By: Jacqueline N. Lane, Ina Ganguli, Patrick Gaule, Eva C. Guinan and Karim R. Lakhani
We investigate how knowledge similarity between two individuals is systematically related to the likelihood that a serendipitous encounter results in knowledge production. We conduct a natural field experiment at a medical research symposium, where we exogenously...
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Keywords:
Cognitive Similarity;
Innovation;
Knowledge Production;
Natural Field Experiment;
Knowledge Acquisition;
Knowledge Sharing;
Relationships
Lane, Jacqueline N., Ina Ganguli, Patrick Gaule, Eva C. Guinan, and Karim R. Lakhani. "Engineering Serendipity: When Does Knowledge Sharing Lead to Knowledge Production?" Strategic Management Journal 42, no. 6 (June 2021).
- 05 Nov 2007
- Research & Ideas
The Changing Face of American Innovation
A better understanding of these deeper relationships is the most important outcome of this work. Q: Your data shows the ethnic composition of U.S. scientists and engineers undergoing a significant...
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- 14 Sep 2011
- Working Paper Summaries
Ethnic Innovation and US Multinational Firm Activity
Keywords:
by C. Fritz Foley & William R. Kerr
- 29 Nov 2004
- Research & Ideas
Caves, Clusters, and Weak Ties: The Six Degrees World of Inventors
about these ideas. We gathered thirty years of U.S. patent data and wrote up some code that identifies the inventors and links them to each other for three million patents and two million inventors. Our first cut was to look at the...
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- Article
The Importance of Being Causal
By: Iavor I Bojinov, Albert Chen and Min Liu
Causal inference is the study of how actions, interventions, or treatments affect outcomes of interest. The methods that have received the lion’s share of attention in the data science literature for establishing causation are variations of randomized experiments....
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Keywords:
Causal Inference;
Observational Studies;
Cross-sectional Studies;
Panel Studies;
Interrupted Time-series;
Instrumental Variables
Bojinov, Iavor I., Albert Chen, and Min Liu. "The Importance of Being Causal." Harvard Data Science Review 2.3 (July 30, 2020).
- 2022
- Working Paper
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective
By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju
As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how...
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Krishna, Satyapriya, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu, and Himabindu Lakkaraju. "The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective." Working Paper, 2022.
- 14 Aug 2008
- Working Paper Summaries
The Agglomeration of U.S. Ethnic Inventors
- 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...
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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
Eisenmann, Thomas R., and Tom Quinn. "TetraScience: Noise and Signal." Harvard Business School Case 824-024, September 2023. (Revised December 2023.)