In today's world, continuous optimization of operational methods and procedures is a major focus of all major businesses. However, performing enterprise operations often requires implementing multiple, discrete computer applications. As a result, capturing and understanding operations or business processes that are part of an enterprise's business information technology (IT) solution is critical for any organization's optimization initiative. Among the many challenges faced when trying to understand operations are heterogeneous applications throughout the organization with no uniform way to capture and/or extract information from these applications, business processes that age before the advent of business process management (BPM) tools that are currently used for designing them, a gap between designed processes and executable process, and a need for human investigation to identify problems and suggest improvements for business processes.
U.S. Pat. Nos. 5,734,837 and 6,073,109 disclose a typical workflow engine, that is, a programming tool for workflow. A process can be created based on the workflow. However, neither analysis nor optimization of the process is performed.
U.S. Patent Application Publication No. 2005/0289138 discloses a near real-time system and method that analyzes large amounts of data. While the system uses XML format, it analyzes only data, not processes, and merely reports results. No optimization is performed. Similarly, U.S. Patent Application Publication No. 2005/0154700 discloses an extraction, analysis and processing system for specialized data from service industries. This approach is somewhat like typical data mining systems but focuses on a specific type of data, that of services industries.
U.S. Patent Application Publication No. 2004/0187140 discloses an application framework that may contain business processes. However, no analysis or optimization of the processes is performed.
Among the problems of the aforementioned systems are the lack of a standard way to capture and/or extract information from heterogeneous business applications, and the lack of automated means to identify and interpret business process problems, and to suggest improvements to maximize process results.