What's Missing From RFID Tests 2What's Missing From RFID Tests 2

Therefore, let's review the amount of bar-code-based data that is captured today to determine how RFID may or may not influence the volume of data captured and retained.

For example, 20 cases of item X identified at a case level by bar codes will still be 20 cases with RFID. The only difference is that those 20 cases are uniquely identified at the case level with a product-level identifier that is accompanied by a serial number to identify which one of the 20 cases a single case is. (We refer to this concept as serialization.) Therefore, in this example, 20 cases (or pallets) with bar codes will still be 20 with RFID tags, and there is no change in the number of items added to the data warehouse.

The next area to consider is the number of captures made while products move through the enterprise. If an business simply replaces its bar-code readers with RFID readers at the same capture points, there still will be no increase in data for case and pallet movement unless more captures are made due to increases in product throughput volume (e.g., 10 cases per minute becomes 20 cases per minute).

However, the real increase in data volume is the addition of more capture points (e.g., shelf readers) and companies' desire for improvements in product availability, visibility, and market reaction capabilities.

To illustrate this, one simple capture point that is added to an RFID project at a store level and distribution-center level is the placement of an RFID gate for capturing trash that can contain empty or broken case or pallet tags.

This addition of the trash gate is done to improve visibility into shrinkage numbers (e.g., damaged cases) and to record the disposal of any empty cases or pallets. This tracking is enabled by capturing the inbound receipt of a case or pallet and the outbound ship of the same case or pallet in a distribution center. If the case or pallet goes into the trash when it is supposed to go onto another truck, the RFID trash gate will capture that case or pallet as disposed or damaged and deduct it from the shipped quantity. Therefore, if five cases or pallets are inbound to a distribution center, five will be accounted as outbound shipped or some mixture of shipped, shelved, and disposed or damaged. Correspondingly, it is the number of additional captures that will increase the space requirements for a data warehouse, not RFID itself.

The analysis of the capture points should be part of an RFID pilot, and the data-warehouse team should contribute to this process. We believe data-warehousing team members working with the applications team should determine the proper capture points required for product movement and analysis. Moreover, this combined team will also determine if the data captured at these points is needed for an extremely short time or if it should be retained by the data warehouse because that data is valuable to the analytical capabilities of the business.

For example, a read to determine routing of the product to its next step in the journey through the supply chain (e.g., place case/pallet X1234 on truck Y1234) may not be retained, while a read done to provide real-time inventory counts (e.g., 20 cases) for the next forecast cycle may be retained for trend analysis.

Bottom line: We believe that RFID pilots that don't include an impact assessment to the data warehouse and don't have data-warehousing team members will severely reduce the long-term success of a company's RFID initiatives.

Gene Alvarez is VP of technology research services at the Meta Group. He has 20 years of IT experience in business-impact assessment, vendor management, project management, software development, and delivery of complex business applications. He also has held positions with Nine West Group, KPMG Peat Marwick, New York Power Authority, and AT&T Communications.