BANFF SOFTWARE

This synopsis is for notification purposes only and does not constitute a solicitation for bids, quotes or proposals. ARS intends to award a one year purchase order on a sole source basis, for The National Agricultural Statistics Service (NASS) for Statistics Canada's Banff software. The Fellegi-Holt (F-H) principles of statistical data editing are internationally considered the gold standard upon which a statistical data editing system should be built, and NASS needs an F-H based system to integrate into its editing and imputation procedures for its sample survey program to reduce an increasing untenable manual, survey data review workload. The use of such a system will enable the agency to reduce the costs of its editing processes, while maintaining (or improving) the quality of the resulting survey data. Statistics Canada's Banff is the only comprehensive statistical data editing package that fully implements all of the F-H principles. In doing so, it contains modules for edit checking for consistency (prior to any data collection), error localization (that fully implements the F-H minimum change criteria), a wide array of imputation choices (all of which are fully integrated with the edit), and automated outlier detection (implementing the associated Hidiroglou-Berthelot algorithm). Banff is the only statistical data editing product on the market that is fully documented and provides both on-site and remote training and support. It is also the only statistical editing package that is written in SAS, which is essential to our implementation of it into our operational systems. This combination of package comprehensiveness, programming coherence with our operational systems, thorough testing, and full documentation and support makes Banff absolutely unique in the editing world, and it's the only package that will meet NASS' needs for statistical data editing -- a path the agency is committed to take. The associated North American Industrial Classification System (NAICS) code for this procurement is 921190. All interested parties may submit capability statements to Shelia Tucker at [email protected], which will be considered. Estimated award date is January 27, 2010.