Comment: 29 pages, 6 figuresThe Kalman Filter has been called one of the greatest inventions in statistics during the 20th century. Its purpose is to measure the state of a system by processing the noisy data received from different electronic sensors. In comparison, a useful resource for managers in their effort to make the right decisions is the wisdom of crowds. This phenomenon allows managers to combine judgments by different employees to get estimates that are often more accurate and reliable than estimates, which managers produce alone. Since harnessing the collective intelligence of employees, and filtering signals from multiple noisy sensors appear related, we looked at the possibility of using the Kalman Filter on estimates by people. Our predictions suggest, and our findings based on the Survey of Professional Forecasters reveal, that the Kalman Filter can help managers solve their decision-making problems by giving them stronger signals before they choose. Indeed, when used on a subset of forecasters identified by the Contribution Weighted Model, the Kalman Filter beat that rule clearly, across all the forecasting horizons in the survey.