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Show Results For
- All HBS Web
(959)
- News (132)
- Research (690)
- Events (6)
- Multimedia (4)
- Faculty Publications (527)
- April 2023
- Technical Note
An Art & A Science: How to Apply Design Thinking to Data Science Challenges
By: Michael Parzen, Eddie Lin, Douglas Ng and Jessie Li
We hear it all the time as managers: “what is the data that backs up your decisions?” Even local mom-and-pop shops now have access to complex point-of-sale systems that can closely track sales and customer data. Social media influencers have turned into seven-figure... View Details
Parzen, Michael, Eddie Lin, Douglas Ng, and Jessie Li. "An Art & A Science: How to Apply Design Thinking to Data Science Challenges." Harvard Business School Technical Note 623-070, April 2023.
- August 2017 (Revised July 2019)
- Case
GROW: Using Artificial Intelligence to Screen Human Intelligence
By: Ethan Bernstein, Paul McKinnon and Paul Yarabe
Over 10% of all 2017 university graduates in Japan used GROW, an artificial intelligence platform and mobile app developed by Tokyo-based people analytics startup IGS, to recruit for a job. This case puts participants in the shoes of IGS founder and CEO Masahiro... View Details
Keywords: Big Data; Artificial Intelligence; Talent and Talent Management; Recruitment; Selection and Staffing; Human Resources; Information Technology; AI and Machine Learning; Analytics and Data Science; Financial Services Industry; Air Transportation Industry; Advertising Industry; Manufacturing Industry; Technology Industry; Japan
Bernstein, Ethan, Paul McKinnon, and Paul Yarabe. "GROW: Using Artificial Intelligence to Screen Human Intelligence." Harvard Business School Case 418-020, August 2017. (Revised July 2019.)
- January 2021 (Revised March 2021)
- Case
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Jill Avery, Ayelet Israeli and Emma von Maur
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Preference Prediction; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
Avery, Jill, Ayelet Israeli, and Emma von Maur. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Case 521-070, January 2021. (Revised March 2021.)
- 2024
- Working Paper
Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python
By: Melissa Ouellet and Michael W. Toffel
This paper describes a range of best practices to compile and analyze datasets, and includes some examples in Stata, R, and Python. It is meant to serve as a reference for those getting started in econometrics, and especially those seeking to conduct data analyses in... View Details
Keywords: Empirical Methods; Empirical Operations; Statistical Methods And Machine Learning; Statistical Interferences; Research Analysts; Analytics and Data Science; Mathematical Methods
Ouellet, Melissa, and Michael W. Toffel. "Empirical Guidance: Data Processing and Analysis with Applications in Stata, R, and Python." Harvard Business School Working Paper, No. 25-010, August 2024.
- October 2018
- Case
Fundraising at St. Camillus Hospital
By: Srikant M. Datar and Caitlin N. Bowler
St. Camillus is a fictional non-profit hospital in rural Maine facing a serious budget deficit. As Director of Marketing, Victoria Stern is building a team to modernize the hospital fundraising efforts. An interview with a promising candidate, who is also a digital... View Details
Keywords: Data Analysis; Data Privacy; Data Governance; Non-profit; Health Care; Fundraising; Data Security; Analytics and Data Science; Safety; Governance; Ethics; Health Care and Treatment; Cybersecurity
Datar, Srikant M., and Caitlin N. Bowler. "Fundraising at St. Camillus Hospital." Harvard Business School Case 119-027, October 2018.
- February 25, 2016
- Article
The Hodgepodge Principle in U.S. Privacy Policy
By: John A. Deighton
Data, says Professor Lawrence Summers, is the new oil, "a hugely valuable asset essential to economic life." Personal data, the kind of data that invites thoughts of privacy, is a big part of that. The European Union saw this economic fuel source coming long ago and... View Details
Keywords: Data; Privacy; Technology; Big Data; Personal Data; Marketing; Information Technology; Analytics and Data Science
Deighton, John A. "The Hodgepodge Principle in U.S. Privacy Policy." Harvard Law and Policy Review Blog (March 2, 2016). http://harvardlpr.com/2016/03/02/the-hodgepodge-principle-in-us-privacy-policy/.
- August 2001
- Article
Technology as a Complex Adaptive System: Evidence from Patent Data
Fleming, L., and O. Sorenson. "Technology as a Complex Adaptive System: Evidence from Patent Data." Research Policy 30, no. 7 (August 2001).
- August 2022
- Supplement
Zalora: Data-Driven Pricing Recommendations
By: Ayelet Israeli
This exercise can be used in conjunction with the main case "Zalora: Data-Driven Pricing" to facilitate class discussion without requiring data analysis from the students. Instead, the exercise presents reports that were created by the data science team to answer the... View Details
Keywords: Pricing; Pricing Algorithms; Dynamic Pricing; Ecommerce; Pricing Strategy; Pricing And Revenue Management; Apparel; Singapore; Startup; Demand Estimation; Data Analysis; Data Analytics; Exercise; Price; Internet and the Web; Apparel and Accessories Industry; Retail Industry; Fashion Industry; Singapore
Israeli, Ayelet. "Zalora: Data-Driven Pricing Recommendations." Harvard Business School Supplement 523-032, August 2022.
- January 2018
- Article
Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life
By: Edward L. Glaeser, Scott Duke Kominers, Michael Luca and Nikhil Naik
New, "big" data sources allow measurement of city characteristics and outcome variables at higher frequencies and finer geographic scales than ever before. However, big data will not solve large urban social science questions on its own. Big data has the most value for... View Details
Glaeser, Edward L., Scott Duke Kominers, Michael Luca, and Nikhil Naik. "Big Data and Big Cities: The Promises and Limitations of Improved Measures of Urban Life." Economic Inquiry 56, no. 1 (January 2018): 114–137.
- June 2021
- Article
Developing a Value Framework: Utilizing Administrative Data to Assess an Enhanced Care Initiative
By: Casey J. Allen, Jarrod S. Eska, Nikhil G. Thaker, Thomas W. Feeley, Robert S. Kaplan, Ryan W. Huey, Ching-Wei D. Tzeng, Jeffrey E. Lee, Steven J. Frank, Thomas A. Aloia, Vijaya Gottumukkala and Matthew H.G. Katz
We used national administrative data to assess multiple domains of value associated with enhanced recovery pathways for patients undergoing pancreatic surgery. Value metrics included in-hospital mortality, complication rates, length of stay (LOS), 30-day readmission... View Details
Keywords: Value-based Health Care; Health Care and Treatment; Analytics and Data Science; Outcome or Result; Measurement and Metrics; Performance Improvement
Allen, Casey J., Jarrod S. Eska, Nikhil G. Thaker, Thomas W. Feeley, Robert S. Kaplan, Ryan W. Huey, Ching-Wei D. Tzeng, Jeffrey E. Lee, Steven J. Frank, Thomas A. Aloia, Vijaya Gottumukkala, and Matthew H.G. Katz. "Developing a Value Framework: Utilizing Administrative Data to Assess an Enhanced Care Initiative." Journal of Surgical Research 262 (June 2021): 115–120.
- August 2018 (Revised September 2018)
- Case
Predicting Purchasing Behavior at PriceMart (A)
By: Srikant M. Datar and Caitlin N. Bowler
This case follows VP of Marketing, Jill Wehunt, and analyst Mark Morse as they tackle a predictive analytics project to increase sales in the Mom & Baby unit of a nationally recognized retailer, PriceMart. Wehunt observed that in the midst of the chaos that surrounded... View Details
Keywords: Data Science; Analytics and Data Science; Analysis; Consumer Behavior; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "Predicting Purchasing Behavior at PriceMart (A)." Harvard Business School Case 119-025, August 2018. (Revised September 2018.)
- May–June 2015
- Article
Big Data: Big Deal or Big Hype?
By: Sunil Gupta
Google Flu Trends article of November 2008 heralded a new age for big data where it is possible to leverage the vast amount of data to speak for itself, without theory or expert knowledge of the subject matter. However, in a short span the pendulum swung from big data... View Details
Gupta, Sunil. "Big Data: Big Deal or Big Hype?" European Business Review (May–June 2015).
- Article
Private and Civil Society Governors of Mercury Pollution from Artisanal and Small-scale Gold Mining: A Network Analytic Approach
By: Kristin Sippl
Artisanal and small-scale gold mining (ASGM) is both a subsistence livelihood for millions of people and the leading source of mercury pollution globally. The United Nation’s 2013 Minamata Convention on Mercury aims to address this challenge, but such public regulatory... View Details
Keywords: Artisanal And Small-scale Mining (ASM); Private Governance; Gold; Mercury; Mining; Governance; Networks; Pollutants; Research
Sippl, Kristin. "Private and Civil Society Governors of Mercury Pollution from Artisanal and Small-scale Gold Mining: A Network Analytic Approach." Extractive Industries and Society 2, no. 2 (April 2015): 198–208.
- May 2021 (Revised February 2024)
- Teaching Note
THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)
By: Ayelet Israeli and Jill Avery
THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details
Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States
- Article
Considerations of Fairness and Strategy: Experimental Data from Sequential Games
By: V. Prasnikar and A. E. Roth
Prasnikar, V., and A. E. Roth. "Considerations of Fairness and Strategy: Experimental Data from Sequential Games." Quarterly Journal of Economics 107, no. 3 (August 1992): 865–888.
- March 1987
- Article
Using Survey Data to Test Standard Propositions Regarding Exchange Rate Expectations
By: J. Frankel and K. A. Froot
Keywords: Currencies; Exchange Rates; Asset Pricing; International Macroeconomics; Monetary Policy; Currency Controls; Fixed Exchange Rates; Floating Exchange Rates; Currency Bands; Currency Zones; Currency Areas; Rational Expectations; Analytics and Data Science; Finance
Frankel, J., and K. A. Froot. "Using Survey Data to Test Standard Propositions Regarding Exchange Rate Expectations." American Economic Review 77, no. 1 (March 1987): 133–153. (Revised from NBER Working Paper No. 1672.)
- July 2021
- Article
Electronic Trace Data and Legal Outcomes: The Effect of Electronic Medical Records on Malpractice Claim Resolution Time
By: Sam Ransbotham, Eric Overby and Michael C. Jernigan
Information systems generate copious trace data about what individuals do and when they do it. Trace data may affect the resolution of lawsuits by, for example, changing the time needed for legal discovery. Trace data might speed resolution by clarifying what events... View Details
Keywords: Analytics and Data Science; Lawsuits and Litigation; Digital Transformation; Welfare; Health Industry
Ransbotham, Sam, Eric Overby, and Michael C. Jernigan. "Electronic Trace Data and Legal Outcomes: The Effect of Electronic Medical Records on Malpractice Claim Resolution Time." Management Science 67, no. 7 (July 2021): 4341–4361.
- Article
Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications
By: Daniel Elsner, Pouya Aleatrati Khosroshahi, Alan MacCormack and Robert Lagerström
Existing application performance management (APM) solutions lack robust anomaly detection capabilities and root cause analysis techniques that do not require manual efforts and domain knowledge. In this paper, we develop a density-based unsupervised machine learning... View Details
Keywords: Big Data; Data Science And Analytics Management; Governance And Compliance; Organizational Systems And Technology; Anomaly Detection; Application Performance Management; Machine Learning; Enterprise Architecture; Analytics and Data Science
Elsner, Daniel, Pouya Aleatrati Khosroshahi, Alan MacCormack, and Robert Lagerström. "Multivariate Unsupervised Machine Learning for Anomaly Detection in Enterprise Applications." Proceedings of the Hawaii International Conference on System Sciences 52nd (2019): 5827–5836.
- June 2012
- Article
A Reexamination of Tunneling and Business Groups: New Data and New Methods
By: Jordan I. Siegel and Prithwiraj Choudhury
One of the most rigorous methodologies in the corporate governance literature uses firms' reactions to industry shocks to characterize the quality of governance. This methodology can produce the wrong answer unless one considers the ways firms compete. Because... View Details
Keywords: Corporate Governance; Mergers And Acquisitions; Business Economics; Firm Organization; Firm Performance; Groups and Teams; Analytics and Data Science
Siegel, Jordan I., and Prithwiraj Choudhury. "A Reexamination of Tunneling and Business Groups: New Data and New Methods." Review of Financial Studies 25, no. 6 (June 2012): 1763–1798.
- April 2015 (Revised March 2017)
- Case
Instacart and the New Wave of Grocery Startups
By: John Deighton and Leora Kornfeld
Instacart is testing an Uber-style solution to the challenge of building a home-delivered grocery business. It is backed by $220 million of venture funding. Will this model succeed where businessses like Webvan failed? What are the questions that this exploratory... View Details
Keywords: Food Retailing; Outsourced Grocery Delivery; Online Ordering; Dynamic Pricing; Data Analytics; Marketing Strategy; Food; Distribution Channels; Business Startups; Food and Beverage Industry; California
Deighton, John, and Leora Kornfeld. "Instacart and the New Wave of Grocery Startups." Harvard Business School Case 515-089, April 2015. (Revised March 2017.)