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    • All HBS Web  (299)
      • Faculty Publications  (73)

      Predictive Analytics Remove Predictive Analytics →

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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...  View Details
      Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation
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      Bojinov, Iavor I., Michael Parzen, and Paul J. Hamilton. "Prediction & Machine Learning." Harvard Business School Module Note 622-101, March 2022.
      • 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...  View Details
      Keywords: Budgets and Budgeting; Business Plan; Forecasting and Prediction; Borrowing and Debt; Corporate Finance; Capital Structure; Cash Flow; Financial Liquidity; Financial Management; Financing and Loans
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      Antill, Samuel, and Ted Berk. "Introduction to Capital Structure Analytics." Harvard Business School Technical Note 222-061, January 2022.
      • 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...  View Details
      Keywords: Prescriptive Analytics; Heterogeneous Treatment Effects; Optimization; Observed Rank Utility Condition (OUR); Between-treatment Heterogeneity; Machine Learning; Decision Making; Analysis; Mathematical Methods
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      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...  View Details
      Keywords: Video Analytics; In-store Shopping; Mask; Sensitivity To Risk; Social Perception; COVID-19; Health Pandemics; Consumer Behavior; Risk and Uncertainty; Attitudes
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      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...  View Details
      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
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      Israeli, Ayelet, and Jill Avery. "THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)." Harvard Business School Teaching Note 521-097, May 2021. (Revised February 2022.)
      • 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...  View Details
      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
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      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...  View Details
      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
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      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...  View Details
      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
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      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...  View Details
      Keywords: Model Persuasion; Analytics and Data Science; Forecasting and Prediction; Mathematical Methods; Framework
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      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...  View Details
      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
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      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...  View Details
      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
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      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...  View Details
      Keywords: Time-use; Subjective Well-being; COVID-19; Health Pandemics; Work-Life Balance; Gender; Equality and Inequality
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      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

      By: Michael W. Toffel, Natalie Epstein, Kris Ferreira and Yael Grushka-Cockayne
      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
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      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.  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
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      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...  View Details
      Keywords: Cognition and Thinking; Creativity; Forecasting and Prediction
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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
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      Toffel, Michael W., and Dan Levy. "Improving Worker Safety in the Era of Machine Learning: Introduction to Predictive Analytics." Harvard Business School PowerPoint Supplement 619-717, June 2019.
      • 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.  View Details
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      Toffel, Michael W., and Dan Levy. "Improving Worker Safety in the Era of Machine Learning: Introduction to Predictive Analytics." Harvard Business School Teaching Note 619-044, June 2019.
      • June 2019
      • Supplement

      Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics

      By: Michael W. Toffel and Dan Levy
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      Toffel, Michael W., and Dan Levy. "Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics." Harvard Business School Spreadsheet Supplement 619-719, June 2019.
      • June 2019
      • Supplement

      Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics

      By: Michael W. Toffel and Dan Levy
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      Toffel, Michael W., and Dan Levy. "Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics." Harvard Business School PowerPoint Supplement 619-718, June 2019.
      • 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.  View Details
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      Toffel, Michael W., and Dan Levy. "Improving Worker Safety in the Era of Machine Learning: Practicum in Predictive Analytics." Harvard Business School Teaching Note 619-071, June 2019.
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