ServiceNow this week revealed it plans to acquire UltimateSuite as part of an effort to unify task and process mining in a way that serves to make launching digital business transformation initiatives simpler.
The UltimateSuite platform is designed to enable organizations to discover all the applications that make up a task, while processing mining focuses more on identifying all the functions within a platform that are associated with an application, says Eric Schroeder, vice president of products for NowX, a ServiceNow platform for incubating emerging technologies.
The overall goal is to provide organizations with deeper insights into how tasks and processes are intertwined to help advance digital business transformation initiatives by embracing hyperautomation capabilities based on robotics process automation (RPA) and artificial intelligence (AI) technologies that ServiceNow has embedded into its core platform, notes Schroeder.
Far too many organizations have embarked on these initiatives without first really understanding how existing processes work. In the absence of that understanding, many of these initiatives are going to cause more disruption than necessary simply because there are exceptions to workflows that are either poorly understood or simply undocumented.
That’s critical because as organizations embrace RPA and AI, organizations need to identify and eliminate as many bottlenecks in existing processes as possible, says Schroeder. Otherwise, these technologies are only going to wind up automating an existing inefficient process, he adds. In fact, many organizations, to achieve that goal, have set up centers of automation excellence to create a central repository for vetted automations that can be reliably reused, notes Schroeder.
In addition, many organizations are also likely paying for applications that are today being used inefficiently, says Schroeder. “They may only be using 20% of the capabilities of an application,” notes Schroeder. Once that inefficiency is identified, it then becomes possible to either focus on invoking more capabilities or replacing it with another application that provides a similar set of capabilities at a lower total cost, notes Schroeder.
Of course, much of the focus on digital business transformation in the last year has shifted from driving new processes to optimizing existing ones as part of an effort to make organizations more profitable. The challenge is: The older the process the more likely to have a plethora of exceptions to rules that would need to be rationalized before they could be efficiently automated.
Hopefully, the combination of process and task mining with RPA and AI will make it easier to successfully launch a digital business transformation initiative. It should not require a large number of consultants to manually discover how various tasks and processes actually work before any of them can be transformed, noted Schroeder. In effect, the total cost of digital business transformation at scale should continue to steadily decline.
In the meantime, there is now a primordial soup of technologies that are all maturing at the same time. The challenge and the opportunity now is to find the catalyst that will ultimately transform those enabling technologies into a framework for driving innovation at rates that previously would have been thought to be unattainable.