BPM is business-driven. It’s about optimizing and improving business performance at the end-to-end process level, innovating the business, making it more efficient, faster, more agile, more compliant with policies and best practices, and more measurable. It’s top-down because it begins with the end-to-end process. SOA is IT-driven. It’s about transforming IT infrastructure, leveraging existing investment and breaking it into reusable parts.

BPM suites represent the fastest-growing discipline in enterprise software. So it’s not surprising that, increasingly, operational data will become process data–-data that’s captured, managed, and organized by a BPM execution engine. There are two major categories of operational data for predictive data mining: process data mining and mining aggregate data, data marts, and data warehouses. Data mining and, especially, predictive modeling, techniques can be used to detect business rule patterns in the process data and now captured rules automates the decision logic.

BPM and SOA techniques hold out the promise of creating agile enterprises, which operate efficiently and respond rapidly to changing business needs. Open standards for service definition and their orchestration into business processes are a key element to achieving this promise.

From a technical perspective BPEL is now the defacto standard, however business analyst definitely prefers a graph based notation such as BPMN. This article provides guidance in understanding the discrepancy between the technical point of view (pro-BPEL) and analyst's (pro-BPMN).

Last time, I challenged organizations and managers to change the way that they collectively think about business processes. Now let's take a closer look at the evolution of this revolution.
Before the Industrial Revolution
Clearly, work with an intended result has been performed since the beginning of mankind. You can call this a process, so what's really new?