Most automation initiatives have failed to live up to their expectations. Researchers believe the problem lies in the approach, especially when enterprises rush into automation projects, repeatedly picking the wrong process candidate or the wrong way to automate the fitting process.
To answer the questions mentioned above, enterprises need granular and broad intelligence-driven insights to make accurate decisions. In order to scale RPA success, businesses must understand two things: First, why they need Automation. Secondly, which process improvement projects should be taken as the first candidates.
A combination of both Process Discovery and Mining can offer just that – helping conceptualize, execute, and scale automation and process improvement needs.
Process Discovery is tasked with recording primary data from user keystrokes for delivering accurate process execution representation. On the other hand, Process Mining reduces the gap between this extracted data and actionable insights using insights encapsulating a broader view of processes concerning enterprise strategy.
A combination of both addresses the varying levels of granularity existing in enterprise processes. Further, Process Mining focuses on L1-L3 levels of granularity to analyze event commits and application logs to power discovery, monitoring, and process improvement based on current organizational information. Analytics derived from the data help enterprises review organization-wide process maps supported by a comprehensive understanding of process structure.
By tracking human-system interactions at the keystroke level, Process Discovery adds on-ground intelligence, eliminating any subjectivity from the automation planning process.
Both Process Discovery and Mining have proved effective in ensuring automation success. A combination of both helps enterprises with the following capabilities, such as:
Process Discovery and Process Mining address automation requirements in critical areas, such as:
The first step to scaling processes’ real efficiency is detecting bottlenecks and their reasons. It is done by evaluating the number of variations and exceptions, the time spent on non-essential activities, and the nature of application delays and inefficiencies. With the help of Process Mining, enterprises conduct root cause analyses to estimate the cost impact of process inefficiencies accurately. Then by applying Process Discovery tools, enterprises can drill deep into understanding process execution at a granular level.
With both strategies, enterprises understand their performance baseline, underpinning automation initiatives and setting the foundation for sustained and continuous improvement.
Process intelligence requires a two-fold intervention:
However, Automation success is much more than choosing the proper process candidates. It requires diligence in the approach to Automation and accurate forecasting of the initiatives’ potential impact.
Enterprises work in an increasingly complex regulatory environment, mostly fraught with challenges. Hence, compliance often becomes a hurdle.
Process Mining addresses the challenge by flagging cases and causes of non-compliance. Once the flagged instances are identified, Process Discovery takes over to capture non-compliant variations, application accesses, and resources expended on non-compliant activities. The result isn’t just a more compliant organization, but millions of dollars saved in potential fines.
The insights generated from Process Discovery and Mining develop functional responsibilities for employee roles’ clarity and specific process maps needed as training material for staff.
On the one hand, Process Mining identifies candidates for training alongside the training steps required. At the same time, Process Discovery generates BPMN-compatible business process maps and optimized process definition documents for enhancing process analysis. A combination of process overview and execution analysis compares employee performance data across regions, departments, and teams.
Intelligent Automation is a layered exercise, and cost reduction is one of its many benefits. Growth is the North Star, and Automation is essential to this end.
Automation initiatives can be impactful when they align with the business strategy and are backed by leadership buy-in to drive enterprise-wide transformation. But rushed pilots will translate into automation project failure and loss.
In order to drive progress in the face of a uniquely challenging environment, enterprises should prioritize Process Discovery and Mining to scale the growth and success of automation projects. These stages are critical in driving enterprises on the road to successful Intelligent Automation.