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- March 2022
- Module Note
Prediction & Machine Learning
By: Iavor I. Bojinov, Michael Parzen and Paul J. Hamilton
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional...
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- January 2022
- Technical Note
Introduction to Capital Structure Analytics
By: Samuel Antill and Ted Berk
This technical note provides an overview of key analytical approaches that are useful in assessing the appropriateness of a firm’s capital structure and funding plan. This note introduces basic quantitative tools and metrics that are commonly used as inputs to this...
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- Article
A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects
By: Edward McFowland III, Sandeep Gangarapu, Ravi Bapna and Tianshu Sun
We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing context, public...
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Keywords:
Prescriptive Analytics;
Heterogeneous Treatment Effects;
Optimization;
Observed Rank Utility Condition (OUR);
Between-treatment Heterogeneity;
Machine Learning;
Decision Making;
Analysis;
Mathematical Methods
McFowland III, Edward, Sandeep Gangarapu, Ravi Bapna, and Tianshu Sun. "A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects." MIS Quarterly 45, no. 4 (December 2021): 1807–1832.
- 2021
- Working Paper
Risk Sensitivity or Social Signaling? Unmasking Behaviors with Video Analytics
By: Shunyuan Zhang, Kaiquan Xu and Kannan Srinivasan
In 2020, as the novel coronavirus spread globally, face masks were recommended in public settings to protect against and slow down the spread of the coronavirus. Why did people comply, or not, while shopping in 2020? Do these motivations relate to their shopping...
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Keywords:
Video Analytics;
In-store Shopping;
Mask;
Sensitivity To Risk;
Social Perception;
COVID-19;
Health Pandemics;
Consumer Behavior;
Risk and Uncertainty;
Attitudes
Zhang, Shunyuan, Kaiquan Xu, and Kannan Srinivasan. "Risk Sensitivity or Social Signaling? Unmasking Behaviors with Video Analytics." Harvard Business School Working Paper, No. 21-143, June 2021. (SSRN Working Paper Series, No. 3871144, June 2021.)
- May 2021 (Revised February 2022)
- 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...
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Keywords:
Data;
Data Analytics;
Artificial Intelligence;
AI;
AI Algorithms;
AI Creativity;
Fashion;
Retail;
Retail Analytics;
E-commerce;
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;
Fashion Industry;
Retail Industry;
Apparel and Accessories Industry;
Consumer Products Industry;
United States
- March 2021 (Revised January 2022)
- Case
Philips: Redefining Telehealth
By: Regina E. Herzlinger, Alec Petersen, Natalie Kindred and Sara M. McKinley
As one of the world’s largest healthcare companies, Philips sought to reach beyond the walls of the hospital and expand its hospital-to-home program to gain future competitive advantage through technology solutions combining predictive analytics with care delivery. By...
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Keywords:
Health Care;
Philips;
Visicu;
Telemedicine;
eICU;
Accountable Care Organization;
ACO;
Bundled Payment;
Hospital To Home;
Patient Monitoring Devices;
Home Health Care;
Health Care and Treatment;
Communication Technology;
Quality;
Safety;
Performance Productivity;
Performance Capacity;
Performance Efficiency;
Consumer Behavior;
Emerging Markets;
Health Industry;
Telecommunications Industry;
Netherlands
Herzlinger, Regina E., Alec Petersen, Natalie Kindred, and Sara M. McKinley. "Philips: Redefining Telehealth." Harvard Business School Case 321-135, March 2021. (Revised January 2022.) (As companion reading for this case, see: Regina E. Herzlinger and Charles Huang. "Note on Bundled Payment in Health Care," HBS Background Note 312-032.)
- February 2021
- Case
Digital Manufacturing at Amgen
By: Shane Greenstein, Kyle R. Myers and Sarah Mehta
This case discusses efforts made by biotechnology (biotech) company Amgen to introduce digital technologies into its manufacturing processes. Doing so is complicated by the fact that the process for manufacturing biologics—or therapeutics made from living cells—is...
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Keywords:
Digital Technologies;
Change;
Change Management;
Decision Making;
Cost vs Benefits;
Decisions;
Information;
Analytics and Data Science;
Innovation and Invention;
Innovation and Management;
Innovation Leadership;
Innovation Strategy;
Technological Innovation;
Jobs and Positions;
Knowledge;
Leadership;
Organizational Culture;
Science;
Strategy;
Information Technology;
Technology Adoption;
Biotechnology Industry;
Pharmaceutical Industry;
United States;
California;
Puerto Rico;
Rhode Island
Greenstein, Shane, Kyle R. Myers, and Sarah Mehta. "Digital Manufacturing at Amgen." Harvard Business School Case 621-008, February 2021.
- 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...
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Keywords:
Data;
Data Analytics;
Artificial Intelligence;
AI;
AI Algorithms;
AI Creativity;
Fashion;
Retail;
Retail Analytics;
E-commerce;
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;
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.)
- January 2021
- Article
Using Models to Persuade
By: Joshua Schwartzstein and Adi Sunderam
We present a framework where "model persuaders" influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model...
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Keywords:
Model Persuasion;
Analytics and Data Science;
Forecasting and Prediction;
Mathematical Methods;
Framework
Schwartzstein, Joshua, and Adi Sunderam. "Using Models to Persuade." American Economic Review 111, no. 1 (January 2021): 276–323.
- September 2020 (Revised September 2021)
- Case
Student Success at Georgia State University (A)
By: Michael W. Toffel, Robin Mendelson and Julia Kelley
Georgia State University had developed a reputation for driving student success by nearly doubling its graduation rate for students of all racial, ethnic, and socioeconomic backgrounds. It did so while growing its student body and the proportion of Black/African...
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Keywords:
Education;
Higher Education;
Learning;
Curriculum and Courses;
Demographics;
Diversity;
Ethnicity;
Income;
Race;
Leadership;
Goals and Objectives;
Measurement and Metrics;
Operations;
Organizations;
Mission and Purpose;
Organizational Culture;
Outcome or Result;
Performance;
Performance Effectiveness;
Performance Evaluation;
Service Operations;
Performance Improvement;
Planning;
Strategic Planning;
Social Enterprise;
Nonprofit Organizations;
Social Issues;
Wealth and Poverty;
Equality and Inequality;
Information Technology;
Digital Platforms;
Education Industry;
Atlanta
Toffel, Michael W., Robin Mendelson, and Julia Kelley. "Student Success at Georgia State University (A)." Harvard Business School Case 621-006, September 2020. (Revised September 2021.)
- September 2020 (Revised March 2022)
- Case
JOANN: Joannalytics Inventory Allocation Tool
By: Kris Ferreira and Srikanth Jagabathula
Michael Joyce, Vice President of Inventory Management at JOANN, championed an effort to develop and implement an inventory allocation analytics tool that used advanced analytics to predict in-season demand of seasonal items for each of JOANN’s nearly 900 stores and...
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Keywords:
Analytics;
Machine Learning;
Optimization;
Inventory Management;
Mathematical Methods;
Decision Making;
Operations;
Supply Chain Management;
Resource Allocation;
Distribution;
Technology Adoption;
Applications and Software;
Change Management;
Fashion Industry;
Consumer Products Industry;
Retail Industry;
United States;
Ohio
Ferreira, Kris, and Srikanth Jagabathula. "JOANN: Joannalytics Inventory Allocation Tool." Harvard Business School Case 621-055, September 2020. (Revised March 2022.)
- 2020
- Working Paper
Uncovering Inequalities in Time-Use and Well-Being during COVID-19: A Multi-Country Investigation
By: Laura M. Giurge, Ayse Yemiscigil, Joseph Sherlock and Ashley V. Whillans
The COVID-19 global pandemic continues to alter how people spend their time, with possible downstream consequences for subjective well-being. Using diverse samples from the United States, Canada, Denmark, Brazil, and Spain (n = 30,018) and following a preregistered...
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Keywords:
Time-use;
Subjective Well-being;
COVID-19;
Health Pandemics;
Work-Life Balance;
Gender;
Equality and Inequality
Giurge, Laura M., Ayse Yemiscigil, Joseph Sherlock, and Ashley V. Whillans. "Uncovering Inequalities in Time-Use and Well-Being during COVID-19: A Multi-Country Investigation." Harvard Business School Working Paper, No. 21-037, September 2020.
- 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...
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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.)
- 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.
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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.
- July 2019
- Article
'Forward Flow': A New Measure to Quantify Free Thought and Predict Creativity
By: Kurt Gray, Stephen Anderson, Eric Evan Chen, John Michael Kelly, Michael S. Christian, John Patrick, Laura Huang, Yoed N. Kenett and Kevin Lewis
When the human mind is free to roam, its subjective experience is characterized by a continuously evolving stream of thought. Although there is a technique that captures people’s streams of free thought—free association—its utility for scientific research is undermined...
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Gray, Kurt, Stephen Anderson, Eric Evan Chen, John Michael Kelly, Michael S. Christian, John Patrick, Laura Huang, Yoed N. Kenett, and Kevin Lewis. "'Forward Flow': A New Measure to Quantify Free Thought and Predict Creativity." American Psychologist 74, no. 5 (July 2019): 539–554.
- June 2019
- Supplement
Improving Worker Safety in the Era of Machine Learning: Introduction to Predictive Analytics
By: Michael W. Toffel and Dan Levy
- June 2019
- Teaching Note
Improving Worker Safety in the Era of Machine Learning: Introduction to Predictive Analytics
By: Michael W. Toffel and Dan Levy
Teaching Note for HBS No. 618-019.
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- June 2019
- Supplement
Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics
By: Michael W. Toffel and Dan Levy
- June 2019
- Supplement
Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics
By: Michael W. Toffel and Dan Levy
- June 2019
- Teaching Note
Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics
By: Michael W. Toffel and Dan Levy
Teaching Note for HBS No. 618-019.
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