Forecasting and Prediction
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- 02 Aug 2020
- What Do You Think?
Is the 'Experimentation Organization' Becoming the Competitive Gold Standard?
SUMMING UP: Digital experimentation is gaining momentum as an everyday habit in many organizations, especially those in high tech, say James Heskett's readers. Open for comment; Comment(s) posted.
- 21 Jul 2020
- Working Paper Summaries
Business Reopening Decisions and Demand Forecasts During the COVID-19 Pandemic
Findings from a nationwide survey underscore the importance of demand projections and interdependencies among businesses for owners’ reopening decisions. Businesses expect the demand for their services will be greatly depressed for many months to come.
- 04 May 2020
- Research & Ideas
Predictions, Prophets, and Restarting Your Business
Businesses are starting to plan their re-entry into the market, but how do they know what that market will look like? Frank V. Cespedes warns against putting too much trust in forecasters. Open for comment; Comment(s) posted.
- 04 Dec 2019
- Book
Creating the Experimentation Organization
New tools allow companies to innovate on an unprecedented scale, in every aspect of business. But the organization must also change. Stefan Thomke previews his forthcoming book, Experimentation Works. Open for comment; Comment(s) posted.
- 13 Nov 2019
- Research & Ideas
Don't Turn Your Marketing Function Over to AI Just Yet
Lacking human insight, artificial intelligence will be limited when it comes to helping marketers open the black box of market prediction, says Tomomichi Amano. Open for comment; Comment(s) posted.
- 22 Oct 2019
- Research & Ideas
Use Artificial Intelligence to Set Sales Targets That Motivate
Setting sales targets has always been an inexact science, with serious consequences if done poorly. Using AI-based advanced analytics might be the answer, argues Doug Chung. Open for comment; Comment(s) posted.
- 18 Sep 2019
- Working Paper Summaries
Using Models to Persuade
“Model persuasion” happens when would-be persuaders offer receivers a streamlined way of understanding data they already know, especially when the data is open to interpretation. Using examples from finance, politics, and law, the authors find that truthtellers do not eliminate the impact of misleading persuasion because wrong models may better fit the past than correct models.
- 07 Jun 2019
- Working Paper Summaries
Reflexivity in Credit Markets
Investors’ biases and market outcomes affect each other in a two-way feedback loop. This study develops a model of a credit market feedback loop, finding that when investors become more bullish this can predict positive returns in the short run, even if expected returns become more negative at longer horizons.
- 10 May 2019
- Working Paper Summaries
Consumer Inertia and Market Power
Consumers are often more likely to buy a product if they have purchased it previously. This paper provides a means to estimate the magnitude of this phenomenon (i.e., consumer inertia) and shows how it affects the prices of firms in competitive settings. Perhaps surprisingly, greater consumer inertia can result in smaller price increases after a merger.
- 27 Feb 2019
- Working Paper Summaries
Judgment Aggregation in Creative Production: Evidence from the Movie Industry
Selecting early-stage ideas in creative industries is challenging because consumer taste is hard to predict and the quantity to sift through is large. Using The Black List that ranks scripts annually based on nominations from film executives, this study shows that aggregating expert opinions helps reduce quality uncertainty and can influence high-budget production.
- 07 Jan 2019
- Research & Ideas
The Better Way to Forecast the Future
We can forecast hurricane paths with great certainty, yet many businesses can't predict a supply chain snafu just around the corner. Yael Grushka-Cockayne says crowdsourcing can help. Open for comment; Comment(s) posted.
- 26 Nov 2018
- Working Paper Summaries
Demand Estimation in Models of Imperfect Competition
The study shows how knowledge about firm behavior can be modeled to better predict demand. Firms tend to raise prices in response to higher demand, so observed relationships between price and quantity can be quite misleading. The authors provide an adjustment that can be used when price experiments or instrumental variables are not available.
- 01 Nov 2018
- Working Paper Summaries
Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning
Passengers arriving at international hubs often endure delays, especially at immigration and security. This study of London’s Heathrow Airport develops a system to provide real-time information about transfer passengers’ journeys through the airport to better serve passengers, airlines, and their employees. It shows how advanced machine learning could be accessible to managers.
- 17 Oct 2018
- Working Paper Summaries
Quantile Forecasts of Product Life Cycles Using Exponential Smoothing
Many important business decisions rely on a manager’s forecast of a product or service’s life cycle. One of the most widely used forecasting techniques is exponential smoothing models. This paper introduces a model suitable for large-scale forecasting environments where key operational decisions depend on quantile forecasts.
- 05 Mar 2018
- Working Paper Summaries
Nowcasting Gentrification: Using Yelp Data to Quantify Neighborhood Change
This study finds that data from digital platforms (in this case, Yelp) can help forecast which neighborhoods are gentrifying and provide new ways to measure business landscape changes that accompany demographic changes.
- 23 Sep 2017
- Working Paper Summaries
Nowcasting the Local Economy: Using Yelp Data to Measure Economic Activity at Scale
Data from online platforms ranging from Yelp to Zillow offer the potential for improved measurement of the local economy. This paper finds that Yelp data can predict business growth, as measured by the Census Bureau, before official statistics are released. Predictive power increases with population density, income, and education level.
- 20 Mar 2017
- Working Paper Summaries
Bubbles for Fama
Nobel laureate Eugene F. Fama has famously claimed that there is no such thing as a bubble, which he defines as a large price run-up that predictably crashes. Analyzing industry data for the US and internationally, the authors find that Fama is mostly right that a sharp price increase of an industry portfolio does not, on average, predict unusually low returns going forward. Yet the authors show that there is much more to a bubble than merely increases in prices; they show a number of characteristics that predict an end to the bubble.
- 25 Jul 2016
- Working Paper Summaries
Bias in Official Fiscal Forecasts: Can Private Forecasts Help?
Why do countries find it so hard to get their deficits under control? The authors bring together data on private sector forecasts with official government forecasts of 26 countries, and identify systematic patterns in errors that official budget agencies make in their forecasts—particularly over-optimistic forecasts of GDP growth and budget balances. Incorporating private sector forecasts into the budget process could reduce violations of limits set by fiscal rules by identifying errors ahead of time rather than just afterwards.
- 21 Oct 2015
- Research & Ideas
How to Predict if a New Business Idea is Any Good
Professor Pian Shu tackles one of the most difficult questions in the startup world: How can you tell if a new business will succeed? Open for comment; Comment(s) posted.
Financial Meltdowns Are More Predictable Than We Thought
Robin Greenwood and Samuel G. Hanson discuss new research that shows economic crises follow predictable patterns. Open for comment; Comment(s) posted.