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For years, organizations have relied on intelligent business process management to automate decisions and improve process management.
As the business world continues to embrace analytics to sharpen decision-making, using intelligent business process management suites is becoming even more attractive; particularly now, when a case is being made for connecting the front-end and back-end systems and using data to better serve customers.
As intelligent business process management -- or iBPM, as it's commonly called -- continues to mature, in part by adopting new standards and by making it easier for business people to use, experts caution against doing too much too soon -- or getting caught up in some of the newer technologies available with the suites.
Ease of use vs. sophistication
In the last few years, iBPM vendors have tried to simplify the user interface experience and democratize software for citizen developers, business analysts and line-of-business (LOB) users, according to Robert Dunie, research director at Gartner.
"Some of the platforms do get to the extent where it's easy enough for the LOB users to use," he said.
Robert Dunieresearch director, Gartner
However, the downside is that more user-friendly iBPM often lacks the higher intelligence capabilities of more complex tools, said Dunie.
To get the most out of iBPM, it may be necessary to use a more sophisticated platform that's harder to use, but that offers complex business rules, more advanced decision automation, predictive analytics or machine learning.
"Some of these highly intelligent products can do sophisticated things, but at the cost of ease of use," Dunie said.
Sales-boosting potential of intelligent business process management
Customer experience has become more critical in gaining a competitive edge. In turn, iBPM has focused on linking the front and back office, or used along with other application development tools to provide a customer-facing experience that connects to the rest of the enterprise, according to Dunie. Those scenarios enable iBPM to connect ERP systems and CRM systems, and to customize applications to create adaptive, contextually aware and personalized customer experiences, he added.
For example, up-selling and cross-selling are areas where iBPM shines, according to Dunie. It works alongside the system of record and provides automation to proactively suggest products or services based on previous interactions.
Strategic RPA use for intelligent business process management
Robotic process automation (RPA) is yet another hot area in iBPM, and it presents a big opportunity for companies to implement bots to move information around systems, according to Mathias Kirchmer, managing director and co-CEO of consulting firm BPM-D.
However, all too often, companies use RPA to fix a symptom of a problem, and not to move the organization forward. For example, a financial services organization may use RPA to move accounts into the next working steps, despite abnormalities in the accounts.
"But if the organization spent more time to figure out why those accounts are different and fix the underlying issue, it would take the organization forward," Kirchmer said.
This goes to show that, while RPA in iBPM is a great opportunity, it needs to be combined with strong processes before it can make sense for the organization.
DMN sparks intelligent business process management interest
Meanwhile, more vendors are adopting the decision model and notation (DMN) standard, according to James Taylor, CEO of consulting firm Decision Management Solutions. DMN has been out for a couple of years, but it's gaining traction as BPM and iBPM works to define complex processes straight through --and there is no simple way to describe logic in standard business process model and notation (BPMN).
Typically, in BPMN, users ignore the instructions of a gateway, twisting the modeling notation to a form that doesn't resemble logic or the intended use of the gateway, Taylor said. However, DMN enables the user to define the decisions in the process, as well as to execute them. The different ways people try to express logic potentially will be in DMN, he added.
DMN may also make it easier to use analytics, as the point of analytics is to improve decision-making.
"There is definitely a lot of interest to apply machine learning to improve business processes," Taylor said.
Intelligent business process management simplifies ERP data transfer
More organizations are also using BPM or decision rules capabilities on top of their ERP stacks, instead of customizing their ERP systems, Taylor said.
Part of this flexibility is that one tool can connect to both ERP and non-ERP systems, enabling all the actions to occur in one place. Additionally, ERP vendors, such as SAP, have encouraged this to some extent, with the objective to make the products easier to customize and require less work inside the actual ERP system.
"The problem with customizing the ERP system is that it makes it hard for customers to upgrade," Taylor said. "It's not good for customers or vendors."
Additionally, iBPM systems enable customers to spin up simple, temporary applications on top of the ERP system quickly -- such as transferring data from one ERP system to another -- say, after an acquisition. No one wants to code that directly into an ERP system, and iBPM simplifies that, Taylor said.
While ERP vendors are still trying to simplify systems to ensure that customizations don't hinder upgrades, layering iBPM on top of the systems may be the way forward for many companies. While the technology continues to advance and add further automation, companies may choose the less user-friendly tools to enable more complex process automation.
As iBPM continues to mature and sees greater adoption, it may spell good news for companies considering to link their back-end and front-end systems and eliminate manual processes.
Learn more about iBPM and other business tools
Know the difference between BPM and intelligent BPM platforms
A primer on embracing intelligence in BPM