Publications
Publications
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- All HBS Web
(323)
- Faculty Publications (107)
- 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
- 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
- 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
- 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
- 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
- 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
- 2019
- Article
Does Big Data Enhance Firm Innovation Competency? The Mediating Role of Data-driven Insights
By: Maryam Ghasemaghaei and Goran Calic
Grounded in gestalt insight learning theory and organizational learning theory, we collected data from 280 middle and top-level managers to investigate the impact of each big data characteristic (i.e., data volume, data velocity, data variety, and data veracity) on... View Details
- 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. View Details
- 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. View Details
- February 2019
- Case
Miroglio Fashion (A)
By: Sunil Gupta and David Lane
Francesco Cavarero, chief information officer of Miroglio Fashion, Italy’s third-largest retailer of women’s apparel, was trying to bring analytical rigor to the company’s forecasting and inventory management decisions. But fashion is inherently hard to predict. Can... View Details
- 2020
- Working Paper
Overcoming the Cold Start Problem of CRM Using a Probabilistic Machine Learning Approach
By: Eva Ascarza
The success of Customer Relationship Management (CRM) programs ultimately depends on the firm's ability to understand consumers' preferences and precisely capture how these preferences may differ across customers. Only by understanding customer heterogeneity, firms can... View Details
- November 2018
- Case
Komatsu Komtrax: Asset Tracking Meets Demand Forecasting
By: Willy Shih, Paul Hong and YoungWon Park
Komatsu's Komtrax system started as a way of remotely monitoring and tracking equipment for the purpose of improving operational efficiency. This case follows its evolution towards other uses including demand forecasting for its sales, marketing, and production... View Details
- August 2018 (Revised September 2018)
- Case
Predicting Purchasing Behavior at PriceMart (A)
By: Srikant M. Datar and Caitlin N. Bowler
This case follows VP of Marketing, Jill Wehunt, and analyst Mark Morse as they tackle a predictive analytics project to increase sales in the Mom & Baby unit of a nationally recognized retailer, PriceMart. Wehunt observed that in the midst of the chaos that surrounded... View Details
- August 2018 (Revised September 2018)
- Supplement
Predicting Purchasing Behavior at PriceMart (B)
By: Srikant M. Datar and Caitlin N. Bowler
Supplements the (A) case. In this case, Wehunt and Morse are concerned about the logistic regression model overfitting to the training data, so they explore two methods for reducing the sensitivity of the model to the data by regularizing the coefficients of the... View Details
- August 2018 (Revised April 2019)
- Supplement
Chateau Winery (B): Supervised Learning
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on “Chateau Winery (A).” In this case, Bill Booth, marketing manager of a regional wine distributor, shifts to supervised learning techniques to try to predict which deals he should offer to customers based on the purchasing behavior of those... View Details
- August 2018 (Revised September 2018)
- Case
LendingClub (A): Data Analytic Thinking (Abridged)
By: Srikant M. Datar and Caitlin N. Bowler
LendingClub was founded in 2006 as an alternative, peer-to-peer lending model to connect individual borrowers to individual investor-lenders through an online platform. Since 2014 the company has worked with institutional investors at scale. While the company assigns... View Details
- August 2018 (Revised September 2018)
- Supplement
LendingClub (B): Decision Trees & Random Forests
By: Srikant M. Datar and Caitlin N. Bowler
This case builds directly on the LendingClub (A) case. In this case students follow Emily Figel as she builds two tree-based models using historical LendingClub data to predict, with some probability, whether borrower will repay or default on his loan.
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