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- January 1986 (Revised April 1987)
- Background Note
Models for Updating Demand Forecasts
Keywords: Forecasting and Prediction
Schleifer, Arthur, Jr. "Models for Updating Demand Forecasts." Harvard Business School Background Note 186-180, January 1986. (Revised April 1987.)
- 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
- 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
Guo, Xiaojia, Kenneth C. Lichtendahl Jr., and Yael Grushka-Cockayne. "Quantile Forecasts of Product Life Cycles Using Exponential Smoothing." Harvard Business School Working Paper, No. 19-038, October 2018. (Darden Business School Working Paper, No. 2805244, July 2016.)
- 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
Egan, Mark, and Peter Tufano. "Forecasting Climate Risks: Aviva’s Climate Calculus." Harvard Business School Case 224-025, September 2023. (Revised October 2024.)
- 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
Schwartzstein, Joshua, and Adi Sunderam. "Using Models to Persuade." American Economic Review 111, no. 1 (January 2021): 276–323.
- June 2015
- Supplement
Generating Higher Value at IBM (A): EPS Forecasting Model
By: Benjamin C. Esty and Scott Mayfield
This case analyzes IBM's financial performance and its capital allocation decisions over a 10-year period from 2004-2013, during which IBM returned more than $140B to shareholders through a combination of dividends and share repurchases. During this time, CEO Sam... View Details
- 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
Guo, Xiaojia, Yael Grushka-Cockayne, and Bert De Reyck. "Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning." Harvard Business School Working Paper, No. 19-040, October 2018.
- January 2008 (Revised July 2009)
- Case
Forecasting the Great Depression
What is proper role of professional economic forecasting in financial decision making? The case presents excerpts from three leading economic forecasters on the eve of, and just after, the stock market crash of October 1929. The first set of excerpts is from Roger... View Details
Keywords: History; Mathematical Methods; Personal Development and Career; Forecasting and Prediction; Financial Crisis
Friedman, Walter A. "Forecasting the Great Depression." Harvard Business School Case 708-046, January 2008. (Revised July 2009.)
- May 2005
- Exercise
Forecasting the Adoption of E-books
By: Elie Ofek
Gives students an opportunity to understand the challenges inherent in forecasting the diffusions of innovations. Provides data for forecasting the adoption of electronic books. Students are encouraged to use the Bass Model framework, while being cognizant of its... View Details
Keywords: Forecasting and Prediction; Framework; Books; Analytics and Data Science; Product Launch; Internet and the Web; Technology Adoption
Ofek, Elie. "Forecasting the Adoption of E-books." Harvard Business School Exercise 505-063, May 2005.
- Research Summary
Estimating Demand Uncertainty Using Judgmental Forecasts
Measuring demand uncertainty is a key activity in supply chain planning, but is difficult when demand history is unavailable such as for new products. One method that can be applied in such cases uses dispersion among forecasting experts as a measure of demand... View Details
- January 1983 (Revised September 1983)
- Case
E.T. Phone Home, Inc.: Forecasting Business Demand
By: John F. Cady and Frank V. Cespedes
Describes a process for forecasting market demand for an emerging technology--cellular radio. The student must critically evaluate the demand model and the market estimates, and modify them as appropriate in order to develop a marketing plan and budget. View Details
Keywords: Budgets and Budgeting; Forecasting and Prediction; Marketing Strategy; Demand and Consumers; Business Processes; Technology
Cady, John F., and Frank V. Cespedes. "E.T. Phone Home, Inc.: Forecasting Business Demand." Harvard Business School Case 583-121, January 1983. (Revised September 1983.)
- 07 Jan 2019
- Research & Ideas
The Better Way to Forecast the Future
“overfitting” a statistical model, ensuring the model hits every historical data point and thus making it overly specific and lacking room for future variables. Another problem can develop with miscalibration, failing to consider whether... View Details
- February 2005 (Revised November 2016)
- Background Note
Forecasting the Adoption of a New Product
By: Elie Ofek
Provides tools and methodologies that allow forecasting demand for innovative new products. Highlights the Bass model—the theory behind it and ways to determine its parameters. Provides a detailed example of how to use the Bass model to forecast demand for satellite... View Details
Keywords: Forecasting and Prediction; Innovation and Invention; Marketing; Demand and Consumers; Mathematical Methods; Competition
Ofek, Elie. "Forecasting the Adoption of a New Product." Harvard Business School Background Note 505-062, February 2005. (Revised November 2016.)
- 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
Grushka-Cockayne, Y., V.R.R. Jose, and K. C. Lichtendahl. "Ensembles of Overfit and Overconfident Forecasts." Management Science 63, no. 4 (April 2017): 1110–1130.
- 2020
- Working Paper
Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective
We provide a comprehensive examination of whether, to what extent, and which accounting variables are useful for improving the predictive accuracy of GDP growth forecasts. We leverage statistical models that accommodate a broad set of (341) variables—outnumbering the... View Details
Keywords: Big Data; Elastic Net; GDP Growth; Machine Learning; Macro Forecasting; Short Fat Data; Accounting; Economic Growth; Forecasting and Prediction; Analytics and Data Science
Datar, Srikant, Apurv Jain, Charles C.Y. Wang, and Siyu Zhang. "Is Accounting Useful for Forecasting GDP Growth? A Machine Learning Perspective." Harvard Business School Working Paper, No. 21-113, December 2020.
- January 1996
- Article
Real Business Cycle Models and the Forecastable Movements in Output, Hours and Consumption
By: J. J. Rotemberg and Michael Woodford
Keywords: Forecasting and Prediction
Rotemberg, J. J., and Michael Woodford. "Real Business Cycle Models and the Forecastable Movements in Output, Hours and Consumption." American Economic Review 86, no. 1 (January 1996): 71–89.
- July–August 2013
- Article
A Joint Model of Usage and Churn in Contractual Settings
By: Eva Ascarza and Bruce G.S. Hardie
As firms become more customer-centric, concepts such as customer equity come to the fore. Any serious attempt to quantify customer equity requires modeling techniques that can provide accurate multiperiod forecasts of customer behavior. Although a number of researchers... View Details
Keywords: Churn; Retention; Contractual Settings; Access Services; Hidden Markov Models; RFM; Latent Variable Models; Customer Value and Value Chain; Consumer Behavior
Ascarza, Eva, and Bruce G.S. Hardie. "A Joint Model of Usage and Churn in Contractual Settings." Marketing Science 32, no. 4 (July–August 2013): 570–590.
- 2024
- Working Paper
Pitfalls of Demographic Forecasts of U.S. Elections
By: Richard Calvo, Vincent Pons and Jesse M. Shapiro
Many observers have forecast large partisan shifts in the US electorate based on demographic trends. Such forecasts are appealing because demographic trends are often predictable even over long horizons. We backtest demographic forecasts using data on US elections... View Details
Keywords: Mathematical Methods; Voting; Political Elections; Trends; Forecasting and Prediction; Demographics
Calvo, Richard, Vincent Pons, and Jesse M. Shapiro. "Pitfalls of Demographic Forecasts of U.S. Elections." NBER Working Paper Series, No. 33016, October 2024.
- 17 Oct 2018
- Working Paper Summaries
Quantile Forecasts of Product Life Cycles Using Exponential Smoothing
- July 1999
- Article
Analysts' Forecast Accuracy: Do Ability and Portfolio Complexity Matter
By: Michael B. Clement
Prior studies have identified systematic and time persistent differences in analysts’ earnings forecast accuracy, but have not explained why the differences exist. Using the I/B/E/S Detail History database, this study finds that forecast accuracy is positively... View Details
Clement, Michael B. "Analysts' Forecast Accuracy: Do Ability and Portfolio Complexity Matter." Journal of Accounting & Economics 27, no. 3 (July 1999): 285–303.