people or objects. There are several methods of identification, but most common is to store a serial number that

identifies a person or object, and perhaps other information, on a microchip that is attached to an antenna (the chip and

antenna together are called an RFID transponder or an RFID tag. Visit http://www.bigsquid.org for more information on this).

The antenna enables chip to transmit identification information to a reader. The reader converts radio waves

reflected back from RFID tag into digital information that can then be passed on to computers that can make use of

it.

Objective The objective of any RFID system is to carry data in suitable transponders, generally known as tags, and to retrieve data, by

machine-readable means, at a suitable time and place to satisfy particular application needs. Data within a tag may provide

identification for an item in manufacture, goods in transit, a location, and identity of a vehicle, an animal or individual.

By including additional data prospect is provided for supporting applications through item specific information or

instructions immediately available on reading tag.

The system requires, in addition to tags, a means of reading or interrogating tags and some means of communicating

data to a host computer or information management system. A system will also include a facility for entering or programming

data into tags. Quite often an antenna is distinguished as if it were a separate part of an RFID system. While its

importance justifies attention it must be seen as a feature that is present in both readers and tags, essential for

communication between two. To understand and appreciate capabilities of RFID systems it is necessary to consider

their constituent parts. It is also necessary to consider data flow requirements that influence choice of systems and

the practicalities of communicating across air interface. By considering system components and their function within

the data flow chain it is possible to grasp most of important issues that influence effective application of RFID.

However, it is useful to begin by briefly considering manner in which wireless communication is achieved, as

techniques involved have an important bearing upon design of system components.

Components of RFID

RFID Reader : The Reader is a radio frequency device used to read data from microchip contained in RFID tag. RFID readers use a

variety of methods to communicate with tags. The most common method for reading passive tags at close range is called

inductive coupling. Simply put, coiled antenna of reader creates a magnetic field with coiled antenna of tag.

The tag draws energy from this field and uses it to send back waves to reader, which is turned into digital information -

the tag's electronic product code. A Reader comprises of a transmitter, receiver, control module and communication functions, sometimes called a transceiver in

radio terms for it to link to a controlling PC. Readers should have an attached antenna, which is used to transmit and

receive radio frequency signal. Each reader is accompanied with PC compatible software that allows user to read and

program tags. Win 2K, XP, ME are some of operating systems compatible with our Readers.

RFID Tag : An RFID tag or transponder is a wireless system composed of an electronic chip (semi-conductor device) with a memory where

data can be stored. The memory can be permanent or volatile. They are classified within two frequency ranges, namely 125 KHz

(low frequency) and 13.56 MHz (high frequency).

The competitive game is changing for retail. As industry continues to consolidate, retailers have begun to realize that using technology to better understand customer buying behavior, to drive sales and profitability, and to reduce operational costs is a necessity for long-term survival.

Retailers are now paying significant attention to BI software, specifically in areas of merchandise intelligence (including merchandise planning, assortment, size, space, price, promotion, and markdown optimization), customer intelligence (including marketing automation, marketing optimization, and market basket analysis), operational intelligence (including IT portfolio management, labor optimization, and real estate site selection), and competitive intelligence. There are many factors that have led retailers to adopt BI software: increased competition, need to squeeze more profitability out of less space, prevalent credit card usage, Internet's role as an alternative sales channel, popularity of loyalty cards, and soon, RFID (radio frequency identification). These milestones have created a wealth of data that retailers are now beginning to appreciate and use.

Within individual companies, we view history of BI in retail through a method that we devised to describe status of any company's evolution toward becoming an intelligent enterprise. We believe that organizations pass through five fundamental stages as they advance in their use of BI as a competitive differentiator:

Operate -- At this most basic level are companies rife with information mavericks: guys in basement offices hammering away on desktop spreadsheets. If they go, knowledge goes with them. There are no processes, and each request becomes an ad hoc data rebuild, resulting in multiple versions of truth, with likelihood of a different answer to any one question every time it is asked. Consolidate -- At this stage, a company has pulled together its data at departmental level. Here, a question gets same answer every time, at least within department. However, departmental interests and interdepartmental competition can skew integrity of output and result in multiple versions of truth. Integrate -- At this point in evolution, a company has adopted enterprise-wide data and bases its decisions on this more complete information. This company is beginning to have a true awareness of additional opportunities for use of BI to improve processes and profits. Optimize -- At this stage, company's knowledge workers are very focused on incremental process improvements and refining value-creation process. Everyone understands and uses analysis, trending, pattern analysis, and predictive results to increase efficiency and effectiveness. The extended value chain becomes increasingly critical to organization, including customers, suppliers, and partners who constitute intercompany communities. Innovate -- This level represents a major, quantum break with past. It exploits understanding of value-creation process acquired in optimize stage and replicates that efficiency with new products in new markets. Companies operating at this level understand what they do well and apply this expertise to new areas of opportunity, thus multiplying number of revenue streams flowing into enterprise. Armed with information and business process knowledge, organizations approaching innovate level will introduce truly innovative products and services that reflect their unique understanding of market, their internal strengths and weaknesses, and an unfailing flow of ideas from continuously engaged employees. We are finding that most large retailers have reached or are approaching integrate stage, with many making great strides toward optimize and innovate levels. There is an enormous opportunity for evolution to continue -- within every retail organization.

The Presence of BI in Retail IT Infrastructure

In typical retail IT infrastructure, there are two fundamental categories of systems: transactional/operational systems, such as POS and purchase order management systems; and analytic/BI systems.

Operational and transactional systems such as merchandise management, ERP (enterprise resource planning), and POS, are very good at what they do -- organizing huge amounts of operational data and transactions. These systems can tell retailers what has happened in their business and what their customers have done -- last week, last month, and last year.

It's critical, however, for retailers to understand what will happen: what demand will be for a select assortment of merchandise, what impact an incremental price change will have on demand, which floor plan will sell more designer shoes, which customers will respond to a direct mail or catalog offer.

Real value comes from systems that go beyond limitations of operational software alone, systems that can take operational data and create enterprise intelligence and predictive insights.

These BI systems must combine data management (consolidating, organizing, and cleansing huge amounts of disparate data from varying systems and platforms) with predictive analytics (data mining, forecasting, optimization). When they do, retailers can make sense of customer, product, supplier, and operational data and draw insights that will help them run their businesses better and more profitably.