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Show Results For
- All HBS Web
(970)
- News (133)
- Research (713)
- Events (8)
- Multimedia (4)
- Faculty Publications (546)
- February 2022
- Case
CityScore: Big Data Comes to Boston
By: Boris Groysberg and Sarah L. Abbott
In 2016, Martin “Marty” Walsh, the Mayor of Boston, introduced CityScore, a data dashboard that measured the city’s progress across a range of metrics. The dashboard was updated daily and publicly available. The mayor frequently discussed the CityScore targets in... View Details
Keywords: Analytics and Data Science; Government Administration; Leadership; Transformation; City; Measurement and Metrics; Public Administration Industry; Boston; United States
Groysberg, Boris, and Sarah L. Abbott. "CityScore: Big Data Comes to Boston." Harvard Business School Case 422-050, February 2022.
- November 2019
- Article
How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework
By: Doug J. Chung, Byungyeon Kim and Byoung G. Park
This paper evaluates the short- and long-term value of sales representatives’ detailing visits to different types of physicians. By understanding the dynamic effect of sales calls across heterogeneous physicians, we provide guidance on the design of optimal call... View Details
Keywords: Nerlove-Arrow Framework; Stock-of-goodwill; Dynamic Panel Data; Serial Correlation; Instrumental Variables; Sales Effectiveness; Detailing; Analytics and Data Science; Sales; Analysis; Performance Effectiveness; Pharmaceutical Industry
Chung, Doug J., Byungyeon Kim, and Byoung G. Park. "How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework." Management Science 65, no. 11 (November 2019): 5197–5218.
- 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... View Details
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.
- Winter 2016
- Article
Analytics for an Online Retailer: Demand Forecasting and Price Optimization
By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details
Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
- 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... View Details
- 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... View Details
Tadikonda, Satish. "HealthVerity: Real World Data and Evidence." Harvard Business School Case 824-019, July 2023.
- October 2018
- Case
BreezoMeter: Making Air Pollution Data Actionable
By: Frank V. Cespedes, Allison M. Ciechanover and Margot Eiran
The case focuses on an Israeli startup that provides actionable air pollution data and forecasts. The company has over 50 enterprise customers and its tool reached a million people daily in 67 countries. The co-founders wrestle with which markets and customers to focus... View Details
Keywords: Startups; Entrepreneurship; Business Startups; Pollutants; Analytics and Data Science; Sales; Marketing; Decision Choices and Conditions; Technology Industry; Israel; United States
Cespedes, Frank V., Allison M. Ciechanover, and Margot Eiran. "BreezoMeter: Making Air Pollution Data Actionable." Harvard Business School Case 819-058, October 2018.
- 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.
- July 2021
- Article
Big Data for Social Benefits: Innovation as a Mediator of the Relationship between Big Data and Corporate Social Performance
By: Goran Calic and Maryam Ghasemaghaei
Over the last decade, the use big data in firms has seen a rapid increase. Whilst scholars have begun to unpack the relationship between big data utilisation and financial performance, significant uncertainty exists about the ethical uses of this new asset. Whether... View Details
Keywords: Analytics and Data Science; AI and Machine Learning; Performance Improvement; Organizational Change and Adaptation
Calic, Goran, and Maryam Ghasemaghaei. "Big Data for Social Benefits: Innovation as a Mediator of the Relationship between Big Data and Corporate Social Performance." Journal of Business Research 131 (July 2021): 391–401.
- 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... View Details
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.
- 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... 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; 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... View Details
Keywords: Sasha Issenberg
- 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... View Details
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.)
- 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
- 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.)
- 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. 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... View Details
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.)
- 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... View Details
Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
- December 2011
- Article
Data Impediments to Empirical Work on Health Insurance Markets
By: Leemore S. Dafny, David Dranove, Frank Limbrock and Fiona Scott Morton
We compare four datasets that researchers might use to study competition in the health insurance industry. We show that the two datasets most commonly used to estimate market concentration differ considerably from each other (both in levels and in changes over time),... View Details
Dafny, Leemore S., David Dranove, Frank Limbrock, and Fiona Scott Morton. "Data Impediments to Empirical Work on Health Insurance Markets." B.E. Journal of Economic Analysis & Policy 11, no. 2 (December 2011).