skip to main content
Close Icon

In order to deliver a personalized, responsive service and to improve the site, we remember and store information about how you use it. This is done using simple text files called cookies which sit on your computer. By continuing to use this site and access its features, you are consenting to our use of cookies. To find out more about the way Informa uses cookies please go to our Cookie Policy page.

Global Search Configuration

Ovum view


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.

It is time to develop a rational view of iBPM

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

Recommended Articles

  • Enterprise Decision Maker, Enterprise IT Strategy and Select...

    2017 Trends to Watch: Big Data

    By Tony Baer 21 Nov 2016

    The breakout use case for big data will be fast data. The Internet of Things (IoT) is increasing the urgency for enterprises to embrace real-time streaming analytics, as use cases from mobile devices and sensors become compelling to a wide range of industry sectors.

    Topics Big data and analytics IoT

  • Consumer & Entertainment Services, World Cellular Informatio...

    Mapping the Future of Enterprise Messaging: SMS, RCS, and Chat Bots

    By Pamela Clark-Dickson

    In this paper, we analyze the results of the Enterprise Messaging Survey 2017, placing the findings in the context of the rapidly evolving business-to-consumer communications market.

  • Consumer & Entertainment Services, Service Provider Technolo...

    FAANG to sink its teeth deeper into TV in 2018

    By Rob Gallagher 14 Dec 2017

    Few trends will be bigger in 2018 than the transformation of TV and video by OTT technology and services. Here we present five Ovum predictions related to the most influential players: Facebook, Amazon, Apple, Google, and Netflix – or FAANG, for short.


Have any questions? Speak to a Specialist

Europe, Middle East & Africa team - +44 (0) 207 017 7700

Asia-Pacific team - +61 (0)3 960 16700

US team - +1 646 957 8878

+44 (0) 207 551 9047 - Operational from 09.00 - 17.00 UK time

You can also contact your named/allocated Client Services Executive using their direct dial.
PR enquiries - Call us at +44 7770704398 or email us at

Contact marketing -

Already an Ovum client? Login to the Knowledge Center now