Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or... – Electronic shopping
Reexamination Certificate
1999-03-26
2003-08-12
Nguyen, Cuong (Department: 3625)
Data processing: financial, business practice, management, or co
Automated electrical financial or business practice or...
Electronic shopping
C705S001100, C705S027200
Reexamination Certificate
active
06606603
ABSTRACT:
TECHNICAL FIELD
The present invention relates to e-commerce systems and, specifically, to a highly distributed system for large-scale content and e-commerce transactions over global computer networks, such as the internet.
BACKGROUND
The network economy is rapidly taking shape, and electronic commerce (eCommerce) is at the forefront of this emerging paradigm. The eCommerce opportunity is expected to explode to over
1.1 trillion dollars by the year 2002, according to several industry analysts. The business-to-business sector will capture the majority of the dollars transacted for eCommerce, an estimated
800 billion dollars.
A closer examination reveals the bulk of the spending activity associated with business-to-business eCommerce will originate from the acquisition of “operating resources”, the goods and services required to operate an enterprise.
Acquiring operating resources is ideal for eCommerce because traditionally they are acquired in a manual, paper-intensive manner—prone to error, mistakes and inefficiencies. The expected savings associated with reducing the costs of acquiring operating resources ranges from 5-15%. Considering the dollars spent by a typical manufacturing corporation, resulting savings can have a significant bottom line benefit.
Conventionally, though, each supplier is “on its own” to provide its own buying relationship with customers. This has the disadvantage the supplier's system is not linked into the buyer's processes (e.g., for approval and procurement). Thus, a system like OBI (Open Buying on the Internet, see http://openbuy.org) is desirable to “glue” the supplier's system to the buyer's system. Unfortunately, OBI still has the disadvantage that the end user doesn't necessarily know which supplier has the goods he wants. This is a fundamental failing of basic OBI, since a primary task an end-user must perform when purchasing something is to find what he wants.
In order to deliver the expected benefits associated with business-to-business eCommerce, it is desirable that a solution provide:
Enterprise Connection of Users, Processes and Systems
Scalable Connection of Buyers and Suppliers.
The Operating Resource Management System (ORMS), from Ariba Technologies, Inc. of Sunnyvale, Calif. is a customer-driven solution that enables buying organizations to achieve significant savings in acquiring operating resources. The Ariba ORMS is described in detail in referenced International Application No. PCT/US98/08407 filed Apr. 27, 1998 of which this application is a continuation-in-part and the contents of which are hereby incorporated herein by reference. An example of how the Ariba ORMS is used within an enterprise is provided in FIG.
1
. The Ariba ORMS can do the following:
Network Enabling Buyers;
Capturing Procurement Processes and Spending;
Network Enabling Enterprise Systems.
Conventionally, buying organizations use the Ariba ORMS to enable their corporate community of users, approvers and related departments to acquire all of their operating resources via a single, common networked infrastructure. The Ariba ORMS executes on a customer's corporate intranet. Ariba ORMS provides a user access to catalogs that are stored on the user's own intranet system, and the Ariba ORMS channels the users to products and services from preferred suppliers while simplifying the numerous processes (e.g., approval within the organization) of acquiring operating resources. In addition, users have cross-process visibility and are able to reference relevant information regarding the status of their requests.
The capture of all operating resources spending is important to achieving significant savings in acquiring these resources. Typically, different spending categories require unique procurement processes to request, approve and purchase the items of interest. The Ariba ORMS facilitates an easy to understand presentation of each process to the user, so complexity is minimized, while still allowing the enterprise to model sophisticated process scenarios. In addition, internal acquisition processes are available within the Ariba ORMS, such as I/T service requests or new employee kits. Complete operating resources spend and process capture drives maximum savings, as well as allowing for global collaborative buying across the enterprise.
A large number of large corporations require a heterogeneous enterprise resource planning systems environment. The seamless integration of these systems into the Ariba ORMS, as shown in
FIG. 2
, facilitates networked information flow and provides for complete leverage of important information such as financial, human resource, security, inventory, messaging and other related data.
The adoption rate of business-to-business eCommerce systems is rapidly growing. In particular, the Ariba ORMS is a leader among global 2000 and mid-size corporation.
Ariba's customer success and market leadership has created a critical mass of buying organizations that represent tens of billions of dollars of annual spending on operating resources. Each Ariba customer represents a network of people, systems and processes that govern the acquisition of operating resources for their enterprise.
The critical mass of buyers and the associated buying power has led to exponential supplier demand for participation. The supplier demand drives requirements for massive integration of product and service content. In addition, eCommerce transactions such as purchase orders, acknowledgements, change orders, order & ship status and invoices require massively scalable integration.
Existing solutions to large-scale integration of supplier content and eCommerce transaction integration include:
Peer-to-Peer Networks
Many-to-One-to-Many Networks
Single Standard Networks
Peer-to-Peer Networks, such as Electronic Data Interchange (EDI), connect individual buying and selling organizations in a one-to-one manner. Electronic commerce has traditionally based interoperability on these one-to-one connections and Peer-to-Peer Networks have been quite effective for acquiring production and manufacturing resources.
However, operating resources are non-manufacturing goods and services acquired from thousands of suppliers, each with widely varying technical capabilities. Therefore, while Peer-to-Peer networks facilitate connections between buyers and suppliers, they are difficult to scale across the thousands of organizations that supply operating resources. This is due to the complexity and cost of establishing each one-to-one communication scenario.
Many-to-One-to-Many Networks provide a central repository or location for all content and transaction activity All buying activities are channeled through the central hub while all supplier interactions flow from the central hub. These networks aggregate supplier content in order to provide an effective means to find products or services of interest across multiple selling organizations. Aggregation of supplier content relies on normalization of the content where multi-sourcing of items is required. A system that aggregates supplier content in a public computer system is disclosed in U.S. Pat. No. 5,319,542 to King, Jr. et al.
Data normalization is the process of defining common descriptions and attributes for the same or similar products offered by different suppliers. To perform this function effectively, domain expertise must exist in the industry or product area requiring normalization. Lack of domain expertise creates content aggregation challenges for Many-to-One-to-Many Networks.
While providing central control for the aggregation of supplier content, Many-to-One-to-Many Networks create bottlenecks that significantly limit the scalability of the network. These bottlenecks act as “choke points” for the network unless effective and efficient aggregation techniques based on relevant domain-based content expertise are used. Furthermore, at some point the amount of data to be aggregated simply becomes too large to be effectively and efficiently aggregated by any method. This type of system that aggregat
Joseph Joshy
Putanec Boris
Ariba, Inc.
Blakely , Sokoloff, Taylor & Zafman LLP
Nguyen Cuong
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