Jun 28, 2004Many conversations about RFID inevitably end up touching on the presumed flood of data and resulting data management issues that are expected to arise from tagging individual products. Data management is a key issue for any organization deploying RFID technology, but the issues are broader than simply creating an infrastructure to manage the sheer volume of data.
Companies, for example, need to address a couple of questions: what data should be collected and stored? How is this data different from what is currently collected and stored? Who owns the data, and what elements are subject to privacy or security considerations? What is the best way to visualize this data and act upon key events? And most important, what business processes need to be changed to enable people to act upon this information?
Generally speaking, data management issues fall into several categories: data collection and storage, data integration, data ownership and privacy, data interpretation and analytics, and execution of end-user business processes to sense and respond to RFID data. Given this range of issues, here are five best practices to help companies develop and implement a data management strategy.
1. Lead with well-defined business processes. Let business requirements drive the collection of RFID data. It should be up to the business managers to define what constitutes a business event and how this translates into a read or write transaction on a tag. Adjust the frequency of read or write events to the needs of the business. For example, asset tracking within an Army maintenance and repair facility may require tracking items as they move from one maintenance and repair service area to another, as opposed to installing readers on shelves where parts are stored. In other words, the granularity of data collection should be driven by business requirements not by what is technically possible.
2. Determine business rules that govern data collection and storage. While RFID technologies have the ability to provide a massive amount of data, the first step in a successful data management strategy is to ensure that only meaningful information is passed on from the edge server-the server connected to the readers-to your back-end applications and data repositories. It's critical that business rules are well defined up front to help separate meaningful information from unwanted data as close to the readers as possible. This will help to reduce the burden on the network and on data storage systems.
Additionally, since RFID opens up the capability for unique item-level tracking as opposed to tracking at the part number or stock-keeping unit (SKU) level, changes may be necessary to both data repositories and to enterprise applications in order to accommodate this level of granularity. Determine changes to database schemas that will help ensure that events and attributes specific to unique items can be accurately captured. In addition to data about unique items, you will also want to prepare for data about your RFID infrastructure itself. Information about the physical location and settings of your RFID reader infrastructure must be carefully managed so that you can correlate events with physical locations.
3. Leverage existing architectures and frameworks for data integration. When integrating RFID data with enterprise applications, one of the challenges is to leverage the infrastructure already in place to minimize costs. This challenge can be addressed by using existing service-oriented architectures and vendor-neutral integration frameworks to help provide the appropriate IT and business services.
Be sure to delineate business services and IT services within your technical architecture. The IT services, such as routing and transformation, should provide a framework for integrating your data irrespective of your business scenarios. Your business services, such as specific business rules, can provide the layer of business functionality that uses the underlying technical service layer.
4. Consider the business dynamics related to data ownership and privacy and develop strategies that benefit your company and its supply chain partners. Over the next three to five years, RFID will force companies to redefine the rules of engagement for collaboration in terms of the how supply chain data is exchanged and protected. Today, many participants in the supply chain are able to benefit from process inefficiencies that are subsidized by their partners. For example, manufacturers don't penalize retailers for stocking too many items within a store. Many stores actually receive merchandise credit plus a service fee when they return expired items to the manufacturer.
Electronic tagging can help to smooth out the balance of power in the supply chain by increasing visibility into operations for all companies involved. Some will benefit; others may not. Be certain to understand the business dynamics across all entities that handle your goods or assets, and determine data ownership or privacy issues that may arise.
5. Make sure data interpretation and analytics provide information people can act on. Having all the data in the world will not help improve a company's profitability if the data is not interpreted correctly or if no one is able to act upon it. Determine business requirements, such as key performance indicators, that will help you understand and take action based on the data that's collected by RFID systems. In some cases, such as in supply chain performance management scenarios, you may need to be alerted in real time or near-real time when key events or exceptions have occurred or are about to occur.
In other cases, the response time may be less critical, and you can employ more asynchronous or batch-oriented techniques in order to process and interpret your data. A business intelligence dashboard can help to monitor key metrics and key processes and allow you to drill down into individual events and transactions for further detail. If you want to automate some of this sense-and-respond activity, consider emerging technologies, such as the Semantic Web standards, which can help computers better interpret data and take actions themselves. In essence, the Semantic Web standards allow computers to better understand the "meaning" of data; this is vital for improved search accuracy and for improved machine-to-machine automation of complex tasks.
RFID technologies can provide information that gives companies a greater visibility into their supply chain and a better understanding of their operations, but the decision as to how to respond to this information is ultimately a human one. Having a business strategy that determines what data is important-and business processes connected to RFID-enabled software applications to enable business managers to sense and respond to key events-should be a major item on your agenda.
Nicholas D. Evans is global lead, emerging technology, for BearingPoint's public services sector. He is the author of Military Gadgets: How Advanced Technology Is Transforming Today's Battlefield...and Tomorrow's and Business Innovation and Disruptive Technology. To comment on this article, click on the link below or send e-mail