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FBO DAILY ISSUE OF SEPTEMBER 05, 2009 FBO #2842
SOLICITATION NOTICE

B -- Private label weekly scanner data inches

Notice Date
9/3/2009
 
Notice Type
Combined Synopsis/Solicitation
 
NAICS
519190 — All Other Information Services
 
Contracting Office
Department of Health and Human Services, Food and Drug Administration, Office of Acquisitions and Grants Services, 5630 Fishers Lane, Room 2129, Rockville, Maryland, 20857-0001
 
ZIP Code
20857-0001
 
Solicitation Number
FDA-SOL-09-1062086
 
Archive Date
9/24/2009
 
Point of Contact
Matthew J. Erbe, Phone: 3018277169, Jose Bumbray,
 
E-Mail Address
matthew.erbe@fda.hhs.gov,
(matthew.erbe@fda.hhs.gov, /div)
 
Small Business Set-Aside
N/A
 
Description
The Food and Drug Administration (FDA) is seeking Full and Open Competition from vendors/resellers, that can provide quotations/proposals. (i) This is a combined synopsis/solicitation for commercial items prepared in accordance with the format in Subpart 12.6, as supplemented with additional information included in this notice. This announcement constitutes the only solicitation; proposals are being requested and a written solicitation will not be issued. (ii) The solicitation number is FDA-SOL-09-1062086. This solicitation is being issued as a BRAND NAME OR EQUAL to Request for Quotation (RFQ). (iii) This solicitation document and incorporated clauses are those in effect through Federal Acquisition Circular (FAC) 2005-36. (iv) The associated NAICS code is 519190 and the small business size standard in millions of dollars is $7.0 (v) Purchase of Nielsen Company Private Label Weekly scanner Data. (vi) The FDA requests responses from qualified sources capable of providing these services in accordance with the below: Background Private label goods are an increasingly important part of household food consumption. In order to better understand the impact of FDA regulations on consumer purchasing behavior and producer costs we need information on private label product attributes, prices and sales. FDA label regulations in particular influence consumer product choices and may place different costs on private label goods versus branded goods. The economic effects of labeling regulations that lead to label changes are estimated using an existing food labeling cost model. The model however, is increasingly out-of-date and uses aggregated data on private label goods. Accurately calculating regulatory costs requires comprehensive and up to date data on the products that are being sold. The existing data does not accurately portray the current extent of market penetration or range of private label products. Scanner data is the most complete, representative and accurate source for this information. We need recent, disaggregated private label scanner data to both estimate the impact of our upcoming regulations, guidance and initiatives generally, and to estimate labeling costs in particular. This purchase will be the first comprehensive dataset covering all FDA-regulated private label products: previous purchases had been limited to food products only. We require new data to be compatible with our existing Nielsen Company scanner data because our on-going projects benefit from time series analysis: especially our labeling cost model and various FDA directed surveys such as the Food Label and Package Survey (FLAPS). Time series analysis of continuous data provides more reliable insight about the impact of FDA regulations and the cost of safety for these products. Purchasing incompatible weekly scanner data will mean that our existing data models will not be able to accurately determine trends and changes in food labeling and purchasing and would diminish the value of both the new data and FDA’s existing investment in data. The Nielsen Company has provided the agency with annual scanner data for the Food Label and Package Survey (FLAPS) and nearly four years of weekly data. Scanner data from collecting companies are proprietary and unique: methods and scope of collection and definitions of terms differ in ways that make comparing results between data sets and integrating data sets potentially problematic, and any new data purchases need to be evaluated carefully to ensure maximum value from our existing data and new purchases. Objective The outcome of this contract shall be the purchase and delivery, in electronic, Excel format, of disaggregated, masked, private label scanner data as detailed below. This data shall be compatible with FDA’s existing weekly scanner data from The Nielsen Company so that time series analyses can use both new and existing data, and so that sales data, product characteristics and prices are compatible. Description of Item I. The contract awardee shall provide FDA weekly historical sales data in electronic, Excel format as detailed below. The data shall be for at least the 52 week period starting with the week ending 9/08/07. The data will be available for use by FDA employees and FDA’s designated contractors as needed for FDA research projects. The contract awardee shall provide disaggregated, masked, weekly historical sales data on individual private label products in electronic, Excel format for 52 weeks period starting with the week ending 9/08/07 for the following product categories in existing FDA data: i. (00)DRY GROCERY DEPARTMENT (inclusive of all subcategories) ii. (01)FROZEN FOODS DEPARTMENT (inclusive of all subcategories) iii. (02)DAIRY DEPARTMENT (inclusive of all subcategories) iv. (03) DELI DEPARTMENT (inclusive of all subcategories) v. (05)FRESH PRODUCE DEPARTMENT (inclusive of all subcategories) In addition, the contract awardee shall provide disaggregated, masked weekly historical sales data on individual private label products in electronic, Excel format for 52 weeks period starting with the week ending 9/08/07 for the following product categories: vi. NON-FOOD GROCERY DEPT. (ONLY subcategories: PERSONAL SOAP/BATH NEEDS PET CARE and TOBACCO & ACCESSORIES) vii. ALCOHOLIC BEVERAGES (inclusive of all subcategories) viii. HEALTH AND BEAUTY AIDS DEPT. (inclusive of all subcategories) Data shall be included at the UPC, category and subcategory level. For all departments listed, the following characteristics or their equivalent shall be provided: DEPARTMENT CATEGORY SUB-CATEGORY PRODUCT MODULE BRAND DESCRIPTION EQUIVALIZED BASE PRODUCT FORM SIZE TYPE CONTAINER PACKAGE GENERAL SHAP PACK TYPE/PACKAGE TYPE ****Salient Characteristics**** The required data shall be consistent and directly compatible with existing FDA weekly sales data so that trends in sales can be accurately analyzed and the value of the data be maximized. CCR: Vendors must be registered in the Central Contractor Registration (CCR) prior to the award of the contract. You may register by going to www.ccr.gov QUESTIONS DEADLINE: All questions are to be submitted via email to Matthew.Erbe@fda.hhs.gov, no later September 7, 2009, 11:00 am EDT. PROVISIONS and CLAUSES: The provision at FAR 52.212-1, Instructions to Offerors Commercial Items applies to this solicitation. The following agenda has been attached to this provision: None. The clause at FAR 52.212-4, Contract Terms and Conditions, Commercial Items applies to this acquisition. The following agenda has been attached to the clause: None. The clause at FAR 52.212-5 Contract Terms and Conditions Required to Implement Statues or Executive Orders, Commercial Items applies to this acquisition. The following FAR clauses cited are applicable: FAR 52.217-8, FAR 52.222-26, FAR 52.222-35, FAR 52.222-36, FAR 52.232-33, FAR 52.246-9 and FAR 52.246-18. Clauses and provisions are incorporated by reference and apply to this acquisition. Responses to this notice shall be sent via email to Matthew.Erbe@fda.hhs.gov
 
Web Link
FBO.gov Permalink
(https://www.fbo.gov/spg/HHS/FDA/DCASC/FDA-SOL-09-1062086/listing.html)
 
Place of Performance
Address: FDA/CFSAN/ORPSS (HFS-020), 5100 Paint Branch Parkway, College Park, Maryland, 20740, United States
Zip Code: 20740
 
Record
SN01940682-W 20090905/090904002505-c5105c233009c81a7c52ce3e18e9d57d (fbodaily.com)
 
Source
FedBizOpps Link to This Notice
(may not be valid after Archive Date)

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