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Show Results For
- All HBS Web
(1,934)
- News (299)
- Research (1,298)
- Events (27)
- Multimedia (11)
- Faculty Publications (775)
- 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.
- April 2015
- Case
Carolinas HealthCare System: Consumer Analytics
By: John A. Quelch and Margaret L. Rodriguez
In 2014, Dr. Michael Dulin, chief clinical officer for analytics and outcomes research and head of the Dickson Advanced Analytics (DA2) group at Carolinas HealthCare System (CHS), successfully unified all analytics talent and resources into one group over a three year... View Details
Keywords: Consumer Segmentation; Big Data; Management Information Systems; Hospital Management; Health Care and Treatment; Marketing; Segmentation; Analytics and Data Science; Information Management; Information Technology; Health; Health Industry; United States
Quelch, John A., and Margaret L. Rodriguez. "Carolinas HealthCare System: Consumer Analytics." Harvard Business School Case 515-060, April 2015.
- July 9, 2019
- Article
Setting Better Sales Goals with Analytics
By: Doug J. Chung, Isabel Huber, Vinay Murthy, Varun Sunku and Marije Weber
Sales compensation is a critical lever in motivating a salesforce and driving growth in the business-to-business sector: Studies show that revising compensation in line with market trends can have a 50% greater impact on sales than advertisements have, for instance. A... View Details
Keywords: Analytics; Salesforce Management; Compensation and Benefits; Motivation and Incentives; Goals and Objectives
Chung, Doug J., Isabel Huber, Vinay Murthy, Varun Sunku, and Marije Weber. "Setting Better Sales Goals with Analytics." Harvard Business Review (website) (July 9, 2019).
- September 22, 2020
- Article
Improving Data Access Democratizes and Diversifies Science
By: Abhishek Nagaraj, Mathijs de Vaan and Esther Shears
Nagaraj, Abhishek, Mathijs de Vaan, and Esther Shears. "Improving Data Access Democratizes and Diversifies Science." Proceedings of the National Academy of Sciences 117, no. 38 (September 22, 2020).
- January 2021
- Exercise
E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer
By: Ayelet Israeli and Fedor (Ted) Lisitsyn
The E-Commerce Analytics group at the traditional CPG firm was in charge of compiling various online sales reports, as well as making data-driven recommendations for sales and marketing tactics. In a series of exercises, students address different data challenges for... View Details
Keywords: Data Analysis; Data Analytics; CPG; Consumer Packaged Goods (CPG); Online Channel; Retail Analytics; Retail; Retailing Industry; Data; Data Sharing; Ecommerce; CRM; Loyalty Management; Assortment Planning; Assortment Optimization; Lifetime Value (LTV); Analytics and Data Science; Analysis; Retention; E-commerce; Retail Industry; Consumer Products Industry; United States
Israeli, Ayelet, and Fedor (Ted) Lisitsyn. "E-Commerce Analytics for CPG Firms (B): Optimizing Assortment for a New Retailer." Harvard Business School Exercise 521-079, January 2021.
- August 2017 (Revised December 2018)
- Case
Tamarin App: Natural Language Processing
By: Srikant M. Datar and Caitlin N. Bowler
In this case, students explore the challenges of using sentiment analysis to monitor and understand public perception around a software application, Tamarin SEO App. Technical topics include building a filtering classifier using naive Bayes and sentiment analysis This... View Details
Keywords: Data Science; Branding; Data Analytics; Analytics and Data Science; Brands and Branding; Analysis; Perception; Planning
Datar, Srikant M., and Caitlin N. Bowler. "Tamarin App: Natural Language Processing." Harvard Business School Case 118-015, August 2017. (Revised December 2018.)
- September 1985 (Revised August 1992)
- Background Note
Note on Marketing Data Diskettes and MAT (Marketing Analytical Tools)
Kaufmann, Patrick J. "Note on Marketing Data Diskettes and MAT (Marketing Analytical Tools)." Harvard Business School Background Note 586-056, September 1985. (Revised August 1992.)
- April 2013
- Case
Managing with Analytics at Procter & Gamble
By: Thomas H. Davenport, Marco Iansiti and Alain Serels
Senior management at P&G has put a strong emphasis on using data to make "better, smarter, real-time business decisions." The Global Business Services (GBS) organization has developed tools, systems and processes to provide managers throughout P&G with direct access to... View Details
Keywords: Analytics; Data Management; Forecasting; Shared Services; Procter ＆ Gamble; Laundry Detergent; Information Management; Forecasting and Prediction; Information Technology; Mathematical Methods; Consumer Products Industry; North America
Davenport, Thomas H., Marco Iansiti, and Alain Serels. "Managing with Analytics at Procter & Gamble." Harvard Business School Case 613-045, April 2013.
- January 2024 (Revised May 2024)
- Case
PortageBay and ESG Analytics
By: Vikram S. Gandhi and Radhika Kak
In 2023, sustainable investors faced several challenges. The first was the lack of access to standardized and vetted environmental, social, and governance (ESG) data, and equally, the interpretation of this data into investment-useful insights. Reducing reliance on... View Details
Keywords: ESG Ratings; Investment Funds; Governance; Environmental Sustainability; Corporate Social Responsibility and Impact
Gandhi, Vikram S., and Radhika Kak. "PortageBay and ESG Analytics." Harvard Business School Case 324-065, January 2024. (Revised May 2024.)
- 2010
- Book
The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance
By: Marshall Fisher and Ananth Raman
Retailers today are drowning in data but lacking in insight: They have huge volumes of information at their disposal. But they're unsure of how to sort through it and use it to make smart decisions. The result? They're struggling with profit-sapping supply chain... View Details
Keywords: Profit; Knowledge Use and Leverage; Logistics; Supply Chain Management; Mathematical Methods; Retail Industry
Fisher, Marshall, and Ananth Raman. The New Science of Retailing: How Analytics Are Transforming the Supply Chain and Improving Performance. Harvard Business Press, 2010.
- January 2020
- Case
Kaggle 2019 Data Science Survey
By: Yael Grushka-Cockayne, Michael Parzen, Paul Hamilton and Steven Randazzo
Grushka-Cockayne, Yael, Michael Parzen, Paul Hamilton, and Steven Randazzo. "Kaggle 2019 Data Science Survey." Harvard Business School Case 620-091, January 2020.
- 12 Oct 2022
- Video
James Mickens: Why All Data Science is Political
- July 2022
- Supplement
Solution for E-Commerce Analytics for CPG Firms (A): Estimating Sales
By: Ayelet Israeli
Keywords: Data Analysis; Data Analytics; CPG; Consumer Packaged Goods (CPG); Estimation; Online Channel; Retail Analytics; Retail; Retailing Industry; Data; Data Sharing; Bricks And Mortar; Ecommerce; Analytics and Data Science; Analysis; Sales; Goods and Commodities; Retail Industry; Consumer Products Industry; United States
- 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.
- February 2024
- Teaching Note
Data Science at the Warriors
By: Iavor I Bojinov and Jessie Li
Teaching Note for HBS Case No. 622-048. View Details
- May 2017 (Revised March 2018)
- Case
Predicting Consumer Tastes with Big Data at Gap
By: Ayelet Israeli and Jill Avery
CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details
Keywords: Retailing; Preference Elicitation; Big Data; Predictive Analytics; Artificial Intelligence; Fashion; Marketing; Marketing Strategy; Marketing Channels; Brands and Branding; Consumer Behavior; Demand and Consumers; Analytics and Data Science; Forecasting and Prediction; E-commerce; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; Apparel and Accessories Industry; United States; Canada; North America
Israeli, Ayelet, and Jill Avery. "Predicting Consumer Tastes with Big Data at Gap." Harvard Business School Case 517-115, May 2017. (Revised March 2018.)
- 14 Jan 2021
- News
Why All Data Science Is Political
- August 2018 (Revised September 2018)
- Supplement
LendingClub (C): Gradient Boosting & Payoff Matrix
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) and (B) cases. In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default... View Details
Keywords: Data Analytics; Data Science; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction
Datar, Srikant M., and Caitlin N. Bowler. "LendingClub (C): Gradient Boosting & Payoff Matrix." Harvard Business School Supplement 119-022, August 2018. (Revised September 2018.)
- 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.