Grant: Discovery Grants Program - Individual

The overall aim of this research program is to provide managers with efficient techniques to apply their expertise to organize and interpret large data sets. The program will address issues ranging from theory (representing preferences) through algorithms (organizing entities) to practice (understanding, manipulating, and utilizing data). It will extend to the design and development of decision support systems, which should result in improvements in environmental and infrastructure management and, more generally, in better informed and more responsive decisions. Multiple Criteria Classification and Analysis (MCCA) procedures are designed to help users classify entities described by multidimensional data. Classification organizes information, strengthens understanding, and facilitates the application of expert guidance, though it may or may not lead to an immediate decision. New MCCA tools will be developed, tested on real-world data, improved, and extended to handle uncertainties and missing data. For instance, a sorting procedure based on MCCA was recently used to classify 1,285 Canadian municipalities as high-risk, low-risk, or robust with respect to future water supply, providing useful information to water-supply managers at all levels. A related technique can be used to design an A-B-C system to streamline inventory management in manufacturing, warehousing, and service organizations such as hospitals. Data, which is now cheap to collect and easy to store and access, has mushroomed in the modern era. MCCA tools will lead to a democratization of expertise in understanding and acting upon this data, and will be of increasing importance in an age of scarcity and decentralization. .