Filter Results:
(446)
Show Results For
- All HBS Web
(1,519)
- Faculty Publications (446)
Show Results For
- All HBS Web
(1,519)
- Faculty Publications (446)
- September–October 2020
- Article
Social-Impact Efforts That Create Real Value
By: George Serafeim
Until the mid-2010s few investors paid attention to environmental, social, and governance (ESG) data—information about companies’ carbon footprints, labor policies, board makeup, and so forth. Today the data is widely used by investors. How can organizations create... View Details
Keywords: Sustainability; Sustainability Management; ESG; ESG (Environmental, Social, Governance) Performance; ESG Disclosure; ESG Disclosure Metrics; ESG Ratings; ESG Reporting; Social Impact; Impact Measurement; Social Innovation; Purpose; Corporate Purpose; Corporate Social Responsibility; Strategy; Social Enterprise; Society; Accounting; Investment; Environmental Sustainability; Climate Change; Corporate Strategy; Mission and Purpose; Corporate Social Responsibility and Impact; Financial Services Industry; Chemical Industry; Technology Industry; Consumer Products Industry; Pharmaceutical Industry; North America; Europe; Japan; Australia
Serafeim, George. "Social-Impact Efforts That Create Real Value." Harvard Business Review 98, no. 5 (September–October 2020): 38–48.
- 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.)
- 2021
- Working Paper
Time and the Value of Data
By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti
Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details
Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
- August 2020
- Technical Note
Comparing Two Groups: Sampling and t-Testing
This note describes sampling and t-tests, two fundamental statistical concepts. View Details
Keywords: Statistics; Econometric Analyses; Experimental Methods; Data Analysis; Data Analytics; Analytics and Data Science; Analysis; Surveys; Mathematical Methods
Bojinov, Iavor I., Chiara Farronato, Yael Grushka-Cockayne, Willy C. Shih, and Michael W. Toffel. "Comparing Two Groups: Sampling and t-Testing." Harvard Business School Technical Note 621-044, August 2020.
- 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.... View Details
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).
- 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.
- June 2020
- Background Note
Customer Management Dynamics and Cohort Analysis
By: Elie Ofek, Barak Libai and Eitan Muller
The digital revolution has allowed companies to amass considerable amounts of data on their customers. Using this information to generate actionable insights is fast becoming a critical skill that firms must master if they wish to effectively compete and win in today’s... View Details
Keywords: Cohort Analysis; Customers; Analytics and Data Science; Segmentation; Analysis; Customer Value and Value Chain
Ofek, Elie, Barak Libai, and Eitan Muller. "Customer Management Dynamics and Cohort Analysis." Harvard Business School Background Note 520-122, June 2020.
- 2021
- Working Paper
The Project on Impact Investments' Impact Investment Database
By: M. Diane Burton, Shawn Cole, Abhishek Dev, Christina Jarymowycz, Leslie Jeng, Josh Lerner, Fanele Mashwama, Yue (Cynthia) Xu and T. Robert Zochowski
Impact investing has grown significantly over the past 15 years. From a niche investing segment with only $25 billion AUM in 2013 (WEF 2013), it experienced double-digit growth and developed into a market with an estimated $502 billion AUM (Mudaliapar and Dithrich... View Details
Burton, M. Diane, Shawn Cole, Abhishek Dev, Christina Jarymowycz, Leslie Jeng, Josh Lerner, Fanele Mashwama, Yue (Cynthia) Xu, and T. Robert Zochowski. "The Project on Impact Investments' Impact Investment Database." Harvard Business School Working Paper, No. 20-117, May 2020. (Revised August 2021.)
- May 8, 2020
- Article
Which Covid-19 Data Can You Trust?
By: Satchit Balsari, Caroline Buckee and Tarun Khanna
The COVID-19 pandemic has produced a tidal wave of data, but how much of it is any good? And as a layperson, how can you sort the good from the bad? The authors suggest a few strategies for dividing the useful data from the misleading: Beware of data that’s too broad... View Details
Balsari, Satchit, Caroline Buckee, and Tarun Khanna. "Which Covid-19 Data Can You Trust?" Harvard Business Review (website) (May 8, 2020).
- 2020
- Article
Public Sentiment and the Price of Corporate Sustainability
By: George Serafeim
Combining corporate sustainability performance scores based on environmental, social, and governance (ESG) data with big data measuring public sentiment about a company’s sustainability performance, I find that the valuation premium paid for companies with strong... View Details
Keywords: Sustainability; ESG; ESG (Environmental, Social, Governance) Performance; Investment Management; Investment Strategy; Big Data; Machine Learning; Environment; Environmental Sustainability; Corporate Governance; Performance; Asset Pricing; Investment; Management; Strategy; Human Capital; Public Opinion; Value; Analytics and Data Science
Serafeim, George. "Public Sentiment and the Price of Corporate Sustainability." Financial Analysts Journal 76, no. 2 (2020): 26–46.
- March 2020 (Revised June 2022)
- Case
GreenLight Fund
By: Brian Trelstad, Julia Kelley and Mel Martin
As Tara Noland, the Executive Director (ED) of GreenLight Cincinnati, reflected on her first few years on the job. Noland had delivered on what she had been hired to do in the city: work with leading philanthropists and nonprofit executives to use data and evidence to... View Details
Keywords: Philanthropy; Venture Philanthropy; Replication; Philanthropy and Charitable Giving; Venture Capital; Social Issues; Decision Making; Analytics and Data Science; Cincinnati
Trelstad, Brian, Julia Kelley, and Mel Martin. "GreenLight Fund." Harvard Business School Case 320-053, March 2020. (Revised June 2022.)
- March 2020
- Supplement
People Analytics at Teach For America (B)
By: Jeffrey T. Polzer and Julia Kelley
This is a supplement to the People Analytics at Teach For America (A) case. In this supplement, situated one year after the A case, Managing Director Michael Metzger must decide how to apply his team's predictive models generated from the previous year’s data. View Details
Keywords: Analytics; Human Resource Management; Data; Workforce; Hiring; Talent Management; Forecasting; Predictive Analytics; Organizational Behavior; Recruiting; Analytics and Data Science; Forecasting and Prediction; Recruitment; Selection and Staffing; Talent and Talent Management
Polzer, Jeffrey T., and Julia Kelley. "People Analytics at Teach For America (B)." Harvard Business School Supplement 420-086, March 2020.
- 2021
- Working Paper
Corporate Environmental Impact: Measurement, Data and Information
By: David Freiberg, DG Park, George Serafeim and T. Robert Zochowski
As an organization’s environmental impact has become a central societal consideration, thereby affecting industry and organizational competitiveness, interest in measuring and analyzing environmental impact has increased. We develop a methodology to derive comparable... View Details
Keywords: Environment; Impact; Measurement; Environmental Ratings; Corporate Valuation; Financial Materiality; Sustainability; Environmental Impact; Environmental Strategy; Impact-Weighted Accounts; IWAI; Environmental Sustainability; Corporate Social Responsibility and Impact; Measurement and Metrics; Valuation
Freiberg, David, DG Park, George Serafeim, and T. Robert Zochowski. "Corporate Environmental Impact: Measurement, Data and Information." Harvard Business School Working Paper, No. 20-098, March 2020. (Revised February 2021.)
- March 2020
- Article
Diagnosing Missing Always at Random in Multivariate Data
By: Iavor I. Bojinov, Natesh S. Pillai and Donald B. Rubin
Models for analyzing multivariate data sets with missing values require strong, often assessable, assumptions. The most common of these is that the mechanism that created the missing data is ignorable—a twofold assumption dependent on the mode of inference. The first... View Details
Keywords: Missing Data; Diagnostic Tools; Sensitivity Analysis; Hypothesis Testing; Missing At Random; Row Exchangeability; Analytics and Data Science; Mathematical Methods
Bojinov, Iavor I., Natesh S. Pillai, and Donald B. Rubin. "Diagnosing Missing Always at Random in Multivariate Data." Biometrika 107, no. 1 (March 2020): 246–253.
- 2020
- Book
The Power of Experiments: Decision-Making in a Data-Driven World
By: Michael Luca and Max H. Bazerman
Have you logged into Facebook recently? Searched for something on Google? Chosen a movie on Netflix? If so, you've probably been an unwitting participant in a variety of experiments—also known as randomized controlled trials—designed to test the impact of changes to an... View Details
Keywords: Experiments; Randomized Controlled Trials; Organizations; Decision Making; Analytics and Data Science; Management Analysis, Tools, and Techniques
Luca, Michael, and Max H. Bazerman. The Power of Experiments: Decision-Making in a Data-Driven World. Cambridge, MA: MIT Press, 2020.
- 2020
- Working Paper
A General Theory of Identification
By: Iavor Bojinov and Guillaume Basse
What does it mean to say that a quantity is identifiable from the data? Statisticians seem to agree
on a definition in the context of parametric statistical models — roughly, a parameter θ in a model
P = {Pθ : θ ∈ Θ} is identifiable if the mapping θ 7→ Pθ is injective.... View Details
Bojinov, Iavor, and Guillaume Basse. "A General Theory of Identification." Harvard Business School Working Paper, No. 20-086, February 2020.
- February 2020 (Revised April 2021)
- Case
StockX: The Stock Market of Things
By: Chiara Farronato, John J. Horton, Annelena Lobb and Julia Kelley
Founded in 2015 by Dan Gilbert, Josh Luber, and Greg Schwartz, StockX was an online platform where users could buy and sell unworn luxury and limited-edition sneakers. Sneaker resale prices often fluctuated over time based on supply and demand, creating a robust... View Details
Keywords: Markets; Auctions; Bids and Bidding; Demand and Consumers; Consumer Behavior; Analytics and Data Science; Market Design; Digital Platforms; Market Transactions; Marketplace Matching; Supply and Industry; Analysis; Price; Product Marketing; Product Launch; Apparel and Accessories Industry; Fashion Industry; North and Central America; United States; Michigan; Detroit
Farronato, Chiara, John J. Horton, Annelena Lobb, and Julia Kelley. "StockX: The Stock Market of Things." Harvard Business School Case 620-062, February 2020. (Revised April 2021.)
- 2020
- Book
Experimentation Works: The Surprising Power of Business Experiments
By: Stefan Thomke
Don’t fly blind. See how the power of experiments works for you. When it comes to improving customer experiences, trying out new business models, or developing new products, even the most experienced managers often get it wrong. They discover that intuition,... View Details
Keywords: Experimentation; Experiments; Market Research; Innovation and Invention; Innovation and Management; Customers; Research
Thomke, Stefan. Experimentation Works: The Surprising Power of Business Experiments. Boston, MA: Harvard Business Review Press, 2020.
- July 2020
- Article
Exploring the Effect of Environmental Orientation on Financial Decisions of Businesses at the Bottom of the Pyramid: Evidence from the Microlending Context
By: Anton Shevchenko, Xiaodan Pan and Goran Calic
Existing research has accumulated substantial evidence on the effect that an environmental orientation has on businesses' economic performance. Yet this research does not cover small businesses from bottom‐of‐the‐pyramid (BOP) markets. In fact, despite increasing... View Details
Keywords: Micro-lending; Environmental Sustainability; Financing and Loans; Corporate Social Responsibility and Impact; Small Business
Shevchenko, Anton, Xiaodan Pan, and Goran Calic. "Exploring the Effect of Environmental Orientation on Financial Decisions of Businesses at the Bottom of the Pyramid: Evidence from the Microlending Context." Business Strategy and the Environment 29, no. 5 (July 2020): 1876–1886.
- 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.