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From the Lab to the Field : the Design and Performance of an Information Aggregation Mechanism inside Intel
| Content Provider | Semantic Scholar |
|---|---|
| Author | Gillen, Benjamin J. Plott, Charles R. Shum, Matthew |
| Copyright Year | 2013 |
| Abstract | We evaluate the performance of an information aggregation mechanism (IAM) implemented inside Intel to forecast unit sales for the company. Developed, refined and tested in the laboratory using experimental methods, the IAM is designed specifically to aggregate information. Its implementation at Intel allows us to test its performance in a much more complex field environment. The IAM provides not only a point forecast of future sales but also yields the full distribution of participants' beliefs regarding this variable. This predictive distribution very closely matches the distribution over outcomes at short horizons while slightly underweighting low-probability realizations of unit sales at long horizons. Compared to Intel's “official forecast,” the IAM forecasts perform well overall, even though they predate the official forecasts. The forecasts improvements are most prominent at short forecast horizons and in direct distribution channels, where the effective aggregation of individually-held information drives the IAM to be more accurate than the official forecast over 75% of the time. ∗The financial support of the Lee Center for Advanced Networking, the Gordon and Betty Moore Foundation, and the Laboratory of Experimental Economics and Political Science is gratefully acknowledged. We thank Dan Zhou for providing excellent research assistance, and Erik Snowberg and Allan Timmermann for helpful discussions and comments. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.hss.caltech.edu/SSPapers/sswp1367.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
