Marketing hype has resulted in a myriad of descriptions for intelligent business process management suites (iBPMS). While the role of analytics in driving improvements in business processes and operations should not be downplayed, it is also important to understand that iBPM does not simply equate to "BPM + analytics" or more specifically, a combination of specific IT capabilities added to traditional BPM suites.
While the marketing hype around iBPM is unlikely to die down soon, it is clear that the iBPMS market in its current state comprises several bloated BPM suites that have retrofitted architecturally disjointed and loosely integrated analytics and social and mobile capabilities onto traditional BPM suites. This combination will not necessarily enable intelligent process management. There is also a view that projects iBPMS as a subsegment of the BPMS market, with a key focus on a content-driven approach to process management and the use of process intelligence and analytics to drive process efficiency.
Some industry pundits and vendor marketers do not give due importance to the practical connotations of "intelligence" in iBPM and instead focus only on the IT capabilities that may deliver the desired positive outcomes that would be difficult to achieve with a traditional BPM solution. Ovum espouses a simpler specification where an iBPMS constitutes the essential IT capabilities "enabling intelligent management of processes" and "management of intelligent processes" (intelligence at both process and process management levels). It is therefore difficult to develop a specific equation for the capabilities that should be put in place to enable iBPM (e.g. iBPM ≠x+y+traditional BPM), and this equation would vary as per the requirements of various use cases.
For example, BPM users cannot iterate faster and be agile in responding to changes in business requirements or new business requirements by following the same, traditional heavy-handed process methods. While integration with enterprise content management (ECM) platforms and access to relevant data sources (to add/push content and metadata into/out from a process, for example) is important for content-driven process applications, in certain use cases, rich analytics delivering the "context of content" is a more critical requirement. Key capabilities enabling iBPM include but are not limited to:
graphical process modeling and rapid prototyping
support for low-code development
multichannel support for human interaction and collaboration
software-based rules processing
real-time process analytics and continuous monitoring/feedback, and predictive analytics
easy integration with enterprise middleware platforms, applications, content management platforms, and databases/data stores
availability as a BPM platform-as-a-service (bpmPaaS) offering.
A closer look at adoption trends reveals that key iBPM use cases include:
dynamic case management
continuous process improvement and process digitalization
business process re-engineering
rapid process-centric application development/composition.
In the same context, it is important that digital-enablement capabilities are not added as mere Band-Aids, but are instead embedded at the architectural and design levels. iBPM extends well beyond operational intelligence or analytics-led BPM modernization. It lowers the barriers to experimentation and supports digitalization without "big bang" implementations, such as following a "start small, grow big" approach.
Saurabh Sharma, Senior Analyst, Infrastructure Solutions
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