Private collaborative forecasting and benchmarking

Suppose a number of hospitals in a geographic area want to learn how their own heart-surgery unit is doing compared with the others in terms of mortality rates, subsequent complications, or any other quality metric. Similarly, a number of small businesses might want to use their recent pointof-sales data to cooperatively forecast future demand and thus make more informed decisions about inventory, capacity, employment, etc. These are simple examples of cooperative benchmarking and (respectively) forecasting that would benefit all participants as well as the public at large, as they would make it possible for participants to avail themselves of more precise and reliable data collected from many sources, to assess their own local performance in comparison to global trends, and to avoid many of the inefficiencies that currently arise because of having less information available for their decision-making. And yet, in spite of all these advantages, cooperative benchmarking and forecasting...

• Type: Conference
• Year: 2004
• Where: WPES
• Authors: Mikhail J. Atallah, Marina Bykova, Jiangtao Li, Keith B. Frikken, Mercan Topkara
• Keywords: Cooperative Benchmarking, Forecasting, Subsequent Complications, WPES 2004