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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

Keywords: Data Science; Analytics and Data Science; Analysis; Consumer Behavior; Forecasting and Prediction

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

Keywords: Data Science; Analytics and Data Science; Analysis; Customers; Household; Forecasting and Prediction

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

Keywords: Data Science; Data Analytics; Investing; Loans; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction; Business Model

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.
... View Details

Keywords: Data Science; Data Analytics; Decision Trees; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction

August 2018 (Revised September 2018)
Supplement

LendingClub (C): Gradient Boosting & Payoff Matrix

By: Srikant M. Datar and Caitlin N. Bowler

This case builds directly on the LendingClub (A) and (B) cases. In this case students follow Emily Figel as she builds an even more sophisticated model using the gradient boosted tree method to predict, with some probability, whether a borrower would repay or default... View Details

Keywords: Data Analytics; Data Science; Investment; Financing and Loans; Analytics and Data Science; Analysis; Forecasting and Prediction

August 2018
Case

BlackBuck (A)

By: Shikhar Ghosh and Shweta Bagai

The case presents the challenges of scaling an asset-heavy company (that relies on its operations). It highlights how decisions on the early team impact a company’s ability to scale, linkage between growth and cash flows, as well the organizational impact of high... View Details

Keywords: Founders; Entrepreneurship; Growth and Development Strategy; Service Delivery; Cash Flow; Growth Management; Truck Transportation; Online Technology; India

June 2018 (Revised October 2018)
Teaching Note

Valuing Snap After the IPO Quiet Period (A), (B), and (C)

By: Marco Di Maggio and Benjamin C. Esty

Teaching Note for HBS Nos. 218-095, 218-096, and 218-116. View Details

June 2018
Case

Forta Furniture: International Expansion

By: John A. Quelch and Karthik Easwar

The Forta Furniture case highlights the need to consider new market expansion to grow a firm. It demonstrates that simply doing what has always been done is not sustainable when other competitors enter the market with differentiated or potentially superior offerings.... View Details

Keywords: Market Entry and Exit; Global Range; Decision Making; Analysis; Cross-Cultural and Cross-Border Issues; Growth and Development Strategy; Brands and Branding; Expansion

June 2018 (Revised April 2021)
Supplement

Valuing Snap After the IPO Quiet Period

By: Benjamin C. Esty, Marco Di Maggio and Greg Saldutte

June 2018 (Revised April 2021)
Case

Valuing Snap After the IPO Quiet Period (A)

By: Marco Di Maggio, Benjamin C. Esty and Gregory Saldutte

Snap, the disappearing message app, went public at $17 per share on March 2, 2017, making its two 20-something founders the youngest self-made billionaires in the country. Over the next three weeks, 14 analysts made investment recommendations on Snap: two with buy... View Details

June 2018
Supplement

Valuing Snap After the IPO Quiet Period (B)

By: Marco Di Maggio and Benjamin C. Esty

Analyzes Snap’s value and analyst recommendations following the events described in the (A) case. View Details

June 2018
Supplement

Valuing Snap After the IPO Quiet Period (C)

By: Marco Di Maggio, Benjamin C. Esty and Gregory Saldutte

Analyzes Snap’s value and analyst recommendations following the events described in the (B) case. View Details

May 2018 (Revised October 2019)
Case

Managing the Future of Work

By: William R. Kerr, Allison Ciechanover and Jeff Huizinga

By 2019, leaders from the public and private sector had become increasingly anxious about how advanced technologies and aging global populations could affect labor markets, workplaces, and workers’ lives. Some analysts forecasted that hundreds of millions of workers... View Details

Keywords: Labor Markets; Workplace; Employment; Technological Innovation; Demographics; Organizational Change and Adaptation; Change Management; Problems and Challenges; Opportunities

2025
Working Paper

Government-Brokerage Analysts and Market Stabilization: Evidence from China

By: Sheng Cao, Xianjie He, Charles C.Y. Wang and Huifang Yin

We show analysts at government-controlled brokerage firms serve as a market stabilization tool in China. Using earnings forecasts from 2005–2019, we find government-brokerage analysts issue relatively more optimistic—yet less accurate and timely—forecasts during... View Details

Keywords: Sell-side Analysts; Forecast Optimism; Forecast Accuracy; Government Incentives; Market Stabilization; Government Ownership; Coordinated Economies; Stocks; Forecasting and Prediction; Business and Government Relations; Emerging Markets

February 2018 (Revised December 2020)
Supplement

People Analytics at Teach For America (Data Set)

By: Jeffrey T. Polzer

This data set is a supplement to the People Analytics at Teach For America (A) case. View Details

Keywords: Analytics; Human Resource Management; Data; Workforce; Hiring; Talent Management; Forecasting; Predictive Analytics; Organizational Behavior; Recruiting

February 2018 (Revised December 2020)
Case

People Analytics at Teach For America (A)

By: Jeffrey T. Polzer and Julia Kelley

As of mid-2016, national nonprofit Teach For America (TFA) had struggled with three consecutive years of declining application totals, and senior management was re-examining the organization's strategy, including recruitment and selection. A few months earlier, former... View Details

Keywords: Recruitment; Selection and Staffing; Analysis; Forecasting and Prediction

February 2018
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, Managing Director Michael Metzger must decide how to extend his team’s predictive analytics work using Natural Language Processing (NLP) techniques. View Details

Keywords: Analytics and Data Science; Forecasting and Prediction; Recruitment; Analysis

January 2018 (Revised January 2020)
Case

People Analytics at McKinsey

By: Jeffrey T. Polzer and Olivia Hull

A private equity–backed fast food chain has hired McKinsey’s new People Analytics group to help it improve performance. As the final client workshop approaches, Associate Partner Alex DiLeonardo ponders the best way to present the team’s findings, especially those that... View Details

Keywords: Talent and Talent Management; Customer Relationship Management; Forecasting and Prediction; Cost Management; Human Resources; Employees; Recruitment; Retention; Selection and Staffing; Measurement and Metrics; Performance; Performance Capacity; Performance Efficiency; Performance Evaluation; Performance Improvement; Consulting Industry; Service Industry

Article

Scenario Generation for Long Run Interest Rate Risk Assessment

By: Robert F. Engle, Guillaume Roussellet and Emil N. Siriwardane

We propose a statistical model of the term structure of U.S. treasury yields tailored for long-term probability-based scenario generation and forecasts. Our model is easy to estimate and is able to simultaneously reproduce the positivity, persistence, and factor... View Details

Keywords: Forecasting; Stress Testing; Interest Rates; Forecasting and Prediction; Risk Management; United States

Find at Harvard

November 2017
Teaching Note

Predicting Consumer Tastes with Big Data at Gap

By: Ayelet Israeli and Jill Avery

CEO Art Peck was eliminating his creative directors for The Gap, Old Navy, and Banana Republic brands and promoting a collective creative ecosystem fueled by the input of big data. Rather than relying on artistic vision, Peck wanted the company to use the mining of big... View Details

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