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Show Results For
- All HBS Web
(6,692)
- News (1,179)
- Research (4,335)
- Events (107)
- Multimedia (62)
- Faculty Publications (2,956)
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- 2019
- Article
Can Big Data Improve Firm Decision Quality? The Role of Data Quality and Data Diagnosticity
By: Maryam Ghasemaghaei and Goran Calic
Anecdotal evidence suggests that, despite the large variety of data, the huge volume of generated data, and the fast velocity of obtaining data (i.e., big data), quality of big data is far from perfect. Therefore, many firms defer collecting and integrating big data as... View Details
Ghasemaghaei, Maryam, and Goran Calic. "Can Big Data Improve Firm Decision Quality? The Role of Data Quality and Data Diagnosticity." Decision Support Systems 120 (2019): 38–49.
Unanticipated Gains
Social capital theorists have shown that some people do better than others in part because they enjoy larger, more supportive, or otherwise more useful networks. But why do some people have better networks than others?
Unanticipated Gains argues... View Details- TeachingInterests
Data Science for Managers
By: Chiara Farronato
This new course is taught as a required course in the first year MBA curriculum as of a.y. 2023-2024. It provides students with the foundations of data science to become effective data-driven managers. The course covers the basics of visualization, statistical and... View Details
- March 2022 (Revised January 2025)
- Technical Note
Exploratory Data Analysis
This module note provides an overview of exploratory data analysis for an introduction to data science course. It begins by defining the term "data", and then describes the different types of data that companies work with (structured v. unstructured, categorical v.... View Details
Keywords: Data Analysis; Data Science; Statistics; Data Visualization; Exploratory Data Analysis; Analytics and Data Science; Analysis
Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Exploratory Data Analysis." Harvard Business School Technical Note 622-098, March 2022. (Revised January 2025.)
- 2019
- Article
Big Data
By: John A. Deighton
Big data is defined and distinguished from a mere moment in the “ancient quest to measure.” Specific discontinuities in the practice of information science are identified that, the paper argues, have large consequences for the social order. The infrastructure that runs... View Details
Keywords: Big Data; Digital Infrastructure; Privacy; Algorithm; Data Generators; Marketplace Icon; Analytics and Data Science; Infrastructure; Power and Influence; Society
Deighton, John A. "Big Data." Consumption, Markets & Culture 22, no. 1 (2019): 68–73.
- March 2018
- Article
Scraped Data and Sticky Prices
By: Alberto Cavallo
I use daily prices collected from online retailers in five countries to study the impact of measurement bias on three common price stickiness statistics. Relative to previous results, I find that online prices have longer durations, with fewer price changes close to... View Details
Keywords: Online Data; Scraped Data; Sticky Prices; Scanner Data; Consumer Price Index; Price; Data and Data Sets
Cavallo, Alberto. "Scraped Data and Sticky Prices." Review of Economics and Statistics 100, no. 1 (March 2018): 105–119.
- 2020
- Article
Assessing the Impact of Big Data on Firm Innovation Performance: Big Data is not Always Better Data
By: Maryam Ghasemaghaei and Goran Calic
In this study, we explore the impacts of big data’s main characteristics (i.e., volume, variety, and velocity) on innovation performance (i.e., innovation efficacy and efficiency), which eventually impacts firm performance (i.e., customer perspective, financial... View Details
Ghasemaghaei, Maryam, and Goran Calic. "Assessing the Impact of Big Data on Firm Innovation Performance: Big Data is not Always Better Data." Journal of Business Research 108 (2020): 147–162.
- July 2020
- Case
Applying Data Science and Analytics at P&G
By: Srikant M. Datar, Sarah Mehta and Paul Hamilton
Set in December 2019, this case explores how P&G has applied data science and analytics to cut costs and improve outcomes across its business units. The case provides an overview of P&G’s approach to data management and governance, and reviews the challenges associated... View Details
Keywords: Data Science; Analytics; Analysis; Information; Information Management; Information Types; Innovation and Invention; Strategy; Analytics and Data Science; Consumer Products Industry; United States; Ohio
Datar, Srikant M., Sarah Mehta, and Paul Hamilton. "Applying Data Science and Analytics at P&G." Harvard Business School Case 121-006, July 2020.
- October 2017 (Revised July 2018)
- Case
Data Science at Target
By: Srikant M. Datar and Caitlin N. Bowler
Paritosh Desai joined Target.com in 2013 as VP of Business Intelligence, Analytics & Testing to explore how the retailer could use its relatively small but thriving e-commerce arm to drive sales and win customers. The case explores the technological and organizational... View Details
Keywords: Data Science; Analytics and Data Science; Organizational Change and Adaptation; Competitive Strategy; Problems and Challenges; Innovation Leadership
Datar, Srikant M., and Caitlin N. Bowler. "Data Science at Target." Harvard Business School Case 118-016, October 2017. (Revised July 2018.)
- 2019
- Working Paper
Large-Scale Demand Estimation with Search Data
By: Tomomichi Amano, Andrew Rhodes and Stephan Seiler
In many online markets, traditional methods of demand estimation are difficult to implement because assortments are very large and individual products are sold infrequently. At the same time, data on consumer search (i.e., browsing) behavior are often available and are... View Details
Amano, Tomomichi, Andrew Rhodes, and Stephan Seiler. "Large-Scale Demand Estimation with Search Data." Harvard Business School Working Paper, No. 19-022, September 2018. (Revised June 2019. Stanford University Research Paper, No. 18-36, 8-20 2018.)
- January 2018
- Case
Viacom: Democratization of Data Science
By: Shane Greenstein and Christine Snively
In two short years, Viacom’s Data Science & Advanced Analytics team built a web platform called Science Central that allowed employees from Viacom’s 20+ cable networks to access television audience insights through three data science apps. In the past, employees would... View Details
Keywords: Data Science; Big Data; Digital Platforms; Analytics and Data Science; Expansion; Strategic Planning
Greenstein, Shane, and Christine Snively. "Viacom: Democratization of Data Science." Harvard Business School Case 618-016, January 2018.
- 2021
- Working Paper
Time Dependency, Data Flow, and Competitive Advantage
Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government... View Details
Keywords: Economics Of AI; Value Of Data; Perishability; Time Dependency; Flow Of Data; Data Strategy; Analytics and Data Science; Value; Strategy; Competitive Advantage
Valavi, Ehsan, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, and Karim R. Lakhani. "Time Dependency, Data Flow, and Competitive Advantage." Harvard Business School Working Paper, No. 21-099, March 2021.
- August 2017 (Revised August 2018)
- Case
Busbud: Building a Data Company
By: Srikant M. Datar, Alistair Croll and Caitlin N. Bowler
The case features the work of LP Maurice (HBS '08) as he decides to take on the fragmented bus travel industry and launch an online business that aggregates and shares bus schedules for routes around the world. His first challenge: finding that the data he needs is... View Details
Keywords: Data Science; Analytics and Data Science; Business Startups; Knowledge Acquisition; Customers; Measurement and Metrics; Transportation Industry
Datar, Srikant M., Alistair Croll, and Caitlin N. Bowler. "Busbud: Building a Data Company." Harvard Business School Case 118-011, August 2017. (Revised August 2018.)
- May 2018
- Exercise
Data Visualization & Communication Exercise
By: Srikant M. Datar and Caitlin N. Bowler
This exercise uses the 1986 Challenger shuttle disaster to explore the relationship between data visualization, effective communication, and decision-making. Students review and analyze excerpts from the 13 charts engineers presented to NASA executives the night before... View Details
Keywords: Visualization; Data; Analytics and Data Science; Communication; Performance Effectiveness; Decision Making; Analysis
Datar, Srikant M., and Caitlin N. Bowler. "Data Visualization & Communication Exercise." Harvard Business School Exercise 118-107, May 2018.
- Research Summary
Personal Data in Marketing
By: John A. Deighton
Between 10% and 20% of all marketing activity in the United States, and a smaller proportion internationally, relies on data about individuals, whether personally identifying or pseudonomized. These data flow across a system of established and emerging firms operating... View Details
- August 2021 (Revised February 2024)
- Case
Data Science at the Warriors
By: Iavor I. Bojinov and Michael Parzen
The case explores the development and early growth of a data science team at the Golden State Warriors, an NBA team based in San Francisco. The case begins by explaining the initial rationale for investing in data science, then covers a debate on the appropriate team... View Details
Keywords: Data Science; Digital Marketing; Analysis; Forecasting and Prediction; Technological Innovation; Information Technology; Sports Industry; San Francisco; United States
Bojinov, Iavor I., and Michael Parzen. "Data Science at the Warriors." Harvard Business School Case 622-048, August 2021. (Revised February 2024.)
- 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... View Details
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.
- TeachingInterests
Big Data Analytics and Machine Learning
Big data in the context of marketing, management, and innovation strategy. Machine Learning algorithms and tools.
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- August 2018 (Revised September 2018)
- Case
LendingClub (A): Data Analytic Thinking (Abridged)
By: Srikant M. Datar and Caitlin N. Bowler
LendingClub was founded in 2006 as an alternative, peer-to-peer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns... View Details
Keywords: Data Science; Data Analytics; Investing; Loans; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction; Business Model
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (A): Data Analytic Thinking (Abridged)." Harvard Business School Case 119-020, August 2018. (Revised September 2018.)
- May 2018 (Revised June 2018)
- Case
Cowen Inc.: Leveraging Data
By: Boris Groysberg, Sarah Abbott and Annelena Lobb
Cowen Inc.’s broker-dealer, Cowen and Company, LLC, boasted a number of analysts who had made prescient stock calls on the basis of creative data analysis. Now Cowen Inc. had opened a new subsidiary, Kyber, which would attempt to monetize new data science products.... View Details
Keywords: Data Science; Equity Research; Research Analysts; Investment; Analytics and Data Science; Equity; Research; Analysis; Competitive Strategy
Groysberg, Boris, Sarah Abbott, and Annelena Lobb. "Cowen Inc.: Leveraging Data." Harvard Business School Case 418-035, May 2018. (Revised June 2018.)