Forecasting and Prediction - Publications - Faculty & Research - Harvard Business School

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2015
Working Paper

The Wisdom of Crowds in Operations: Forecasting Using Prediction Markets

By: Achal Bassamboo, Ruomeng Cui and Antonio Moreno

Prediction is an important activity in various business processes, but it becomes difficult when historical information is not available, such as forecasting demand of a new product. One approach that can be applied in such situations is to crowdsource opinions from... View Details

Keywords: Wisdom Of Crowds; Demand Forecasting; Price Forecasting; Forecasting and Prediction; Social and Collaborative Networks; Size; Performance

2013
Book

Fortune Tellers: The Story of America's First Economic Forecasters

By: Walter A. Friedman

The period leading up to the Great Depression witnessed the rise of the economic forecasters, pioneers who sought to use the tools of science to predict the future, with the aim of profiting from their forecasts. This book chronicles the lives and careers of the men... View Details

Keywords: Forecasting And Prediction; Economic History; Economics; History; Risk and Uncertainty; United States

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2014
Article

The Promise of Prediction Contests

By: Phillip E. Pfeifer, Yael Grushka-Cockayne and Kenneth C. Lichtendahl

This article examines the prediction contest as a vehicle for aggregating the opinions of a crowd of experts. After proposing a general definition distinguishing prediction contests from other mechanisms for harnessing the wisdom of crowds, we focus on... View Details

Keywords: Prediction; Forecasting and Prediction

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September 2020
Article

Analyst Forecast Bundling

By: Michael Drake, Peter Joos, Joseph Pacelli and Brady Twedt

Changing economic conditions over the past two decades have created incentives for sell-side analysts to both provide their institutional clients tiered services and to streamline their written research process. One manifestation of these changes is an increased... View Details

Keywords: Analysts; Earnings Forecasts; Forecast Accuracy; Forecast Bundling; Business Earnings; Forecasting and Prediction

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March 2024
Module Note

Navigating the Future: Managing Financial Forecasts

This module note guides instructors on delivering a course module that focuses on understanding, developing, and using financial forecasts from a chief financial officer’s (CFO) perspective. The cases in the module equip students with an understanding of the techniques... View Details

Keywords: CFO; Forecasting; Corporate Finance; Forecasting and Prediction; Financial Management; Revenue; United States

2018
Working Paper

Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning

By: Xiaojia Guo, Yael Grushka-Cockayne and Bert De Reyck

Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates quantile forecasts of transfer passengers’ connection times. Sampling from the distribution of individual passengers’ connection times, the system also produces... View Details

Keywords: Quantile Forecasts; Regression Tree; Copula; Passenger Flow Management; Data-driven Operations; Forecasting and Prediction; Data and Data Sets

2023
Working Paper

Auditing Predictive Models for Intersectional Biases

By: Kate S. Boxer, Edward McFowland III and Daniel B. Neill

Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for individuals at the intersection of two or more protected classes. To address this risk, we... View Details

Keywords: Predictive Models; Bias; AI and Machine Learning

February 2024
Teaching Note

AB InBev: Brewing Up Forecasts during COVID-19

By: Mark Egan and C. Fritz Foley

Teaching Note for HBS Case No. 224-020. In July 2021, the CEO of AB InBev's European operations and his team strategized to position the company for success post-pandemic. As the world's largest beer company, boasting over 500 brands, revenue of $46 billion, and a... View Details

Keywords: Forecasting; Investor Relations; Beverage Industry; Corporate Finance; Decisions; Forecasting and Prediction; Health Pandemics; Analytics and Data Science; Digital Transformation; Crisis Management; Business Model; Food and Beverage Industry; United States; Europe

January 2024 (Revised February 2024)
Case

Data-Driven Denim: Financial Forecasting at Levi Strauss

The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its... View Details

Keywords: Investor Relations; Forecasting; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Digital Transformation; Apparel and Accessories Industry; United States

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

September 2023 (Revised January 2024)
Case

AB InBev: Brewing Up Forecasts during COVID-19

By: Mark Egan, C. Fritz Foley, Esel Cekin and Emilie Billaud

In July 2021, the CEO of AB InBev's European operations and his team strategized to position the company for success post-pandemic. As the world's largest beer company, boasting over 500 brands, revenue of $46 billion, and a workforce of 160,000 in 2020, AB InBev... View Details

February 2024
Teaching Note

Data-Driven Denim: Financial Forecasting at Levi Strauss

Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to... View Details

Keywords: Forecasting; Regression; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Apparel and Accessories Industry; United States

February 2024
Teaching Note

Accelerating with Caution: Forecasting and Managing birddogs' Growth (A) and (B)

Teaching Note for HBS Case Nos. 224-023 and 224-024. As 2017 was drawing to a close, birddogs’ founder and CEO, Peter Baldwin, was working with his CFO Jack Sullivan to prepare for 2018. A nascent direct-to-consumer apparel brand, birddogs had carved its niche in men’s... View Details

Keywords: Inventory Management; Forecasting Demand; Financial Constraints; Apparel; Startups; Corporate Finance; Forecasting and Prediction; Working Capital; Financing and Loans; Organizational Change and Adaptation; Demand and Consumers; Apparel and Accessories Industry; United States

Article

Ensembles of Overfit and Overconfident Forecasts

By: Y. Grushka-Cockayne, V.R.R. Jose and K. C. Lichtendahl

Firms today average forecasts collected from multiple experts and models. Because of cognitive biases, strategic incentives, or the structure of machine-learning algorithms, these forecasts are often overfit to sample data and are overconfident. Little is known about... View Details

Keywords: Decision Analysis; Data Science; Forecasting and Prediction; Data and Data Sets

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December 2020 (Revised March 2022)
Teaching Note

Forecasting ClimaCell

By: Joshua Lev Krieger, Christopher Stanton and James Barnett

A weather technology startup, ClimaCell considers the R&D trade-offs and financing implications of pursuing a proposed contract with a major automobile maker, rather than continuing its focus on building a scalable, all-purpose weather prediction engine. View Details

Keywords: Weather; Forecasting and Prediction; Business Startups; Research and Development; Finance; Cost vs Benefits; Decision Making; Strategy; United States; Israel; Massachusetts; Colorado

Article

Cultural Diversity on Wall Street: Evidence from Consensus Earnings Forecasts

By: Kenneth Merkley, Roni Michaely and Joseph Pacelli

We examine how cultural differences among agents influence the aggregate outcome of a common forecasting task. Using both exogenous shocks to sell-side analyst diversity and panel regression methods, we find that increases in analyst cultural diversity positively... View Details

Keywords: Culture; Forecasting; Sell-side Analysts; Information Aggregation; Diversity; Forecasting and Prediction; Information; Performance Improvement

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May 2017 (Revised March 2018)
Case

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

September 2023 (Revised October 2024)
Case

Forecasting Climate Risks: Aviva’s Climate Calculus

By: Mark Egan and Peter Tufano

In late 2021, Ben Carr, Director of Analytics and Capital Modeling at Aviva Plc (Aviva)—a leading insurer with core operations in the UK, Ireland and Canada,—was preparing for an upcoming presentation before the company's board which included its CEO, Amanda Blanc,... View Details

Keywords: Climate Risk; Climate Finance; Forecasting; Insurance; Risk Measurement; Climate Change; Risk Management; Forecasting and Prediction; Insurance Industry; United States

Research Summary

Analyst Disagreement, Forecast Bias and Stock Returns

We present evidence of inefficient information processing in equity markets by documenting that biases in analysts' earnings forecasts are reflected in stock prices. In particular, investors fail to account for analysts' tendency to withhold negative views and to issue... View Details

2018
Working Paper

Quantile Forecasts of Product Life Cycles Using Exponential Smoothing.

By: Xiaojia Guo, Kenneth C. Lichtendahl Jr. and Yael Grushka-Cockayne

We introduce an exponential smoothing model that a manager can use to forecast the demand of a new product or service. The model has five features that make it suitable for accurately forecasting product life cycles at scale. First, the trend in our model follows the... View Details

Keywords: New Product Development; Demand Forecasting; Product Adoption; Innovation Diffusion; Product Development; Demand and Consumers; Forecasting and Prediction; Adoption

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