Many large organizations use a stage-gate process to manage new product development projects. In a typical stage-gate process project managers learn about potential ideas from research and exert effort in development while senior executives make intervening go/no-go decisions. This decentralized...

We explore some recent, and not so recent, developments concerning the use of probability forecasts and their combination in decision making. Despite these advances, challenges still exist. We expand on some important challenges influencing the “goodness” of combined probability forecasts...

We introduce an alternative to the popular linear opinion pool for combining individual probability forecasts. One of the well-known problems with the linear opinion pool is that it can be poorly calibrated. It tends toward underconfidence as the crowd’s diversity increases, i.e., as the...

We study the problem of forecasting a time series that evolves according to a dynamically changing, skewed life cycle. For instance, firms often need accurate distributional forecasts of product life cycles to make operational decisions about capacity and inventory management. These forecasts...

Probability forecasts of binary events are often gathered from multiple models and averaged to provide inputs regarding uncertainty in important decision-making problems. Averages of well calibrated probabilities are underconfident, and methods have been proposed to make them more extreme. To...

From forecasting competitions to conditional value-at-risk requirements, the use of multiple quantile assessments is growing in practice. To evaluate them, we use a rule from the general class of proper scoring rules for a forecaster's multiple quantiles of a single uncertain quantity of...

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 the challenges associated...

We consider two ways to aggregate expert opinions using simple averages: averaging probabilities and averaging quantiles. We examine analytical properties of these forecasts and compare their ability to harness the wisdom of the crowd. In terms of location, the two average forecasts have the...

Probability forecasters who are rewarded via a proper scoring rule may care not only about the score, but also about their performance relative to other forecasters. We model this type of preference and show that a competitive forecaster who wants to do better than another forecaster typically...

When several individuals are asked to forecast an uncertain quantity, they often face implicit or explicit incentives to be the most accurate. Despite the desire to elicit honest forecasts, such competition induces forecasters to report strategically and non-truthfully. The question we address...