Automation makes our lives easier – a controversial ideology, but ultimately and universally true.
No matter how much we resist the digital transformation that has occurred in the past 10 years, automation has now become an integral part of our personal and corporate lives.
Focusing on the corporate world, there are a multitude of tools that grease the wheels for an enterprise’ journey towards complete automation. In the midst of many other tools and tech, ‘Process Mining’ is often highly underrated since people do not realize its complete potential. Leading vendors of process mining solutions believe that when evaluated alone, it has a few barriers – it cannot function as a comprehensive automation solution. Hence, it must be integrated with other automation technology to survive. They also emphasize that when treated as a support system, process mining has the capability to do away with opaque workflows and data silos, which are major problems for most organizations.
In accordance, process mining, when used in collaboration with other automation and data management technology, is capable of revealing information to enhance business performance, operation management, employee productivity and work ethics.
In Recent Times, Process Mining Is Widely Being Recognized as The Hidden Backbone Of All Branches Of Intelligent Process Automation, With An Emphasis On Its Contribution To Robotic Process Automation.
Robotic Process Automation highly benefits from process mining. But before exploring this relationship between the two, lets understand what Process Mining is.
In our overview of process mining, we defined it as “the utilization of specialized data mining algorithms to analyze processes, isolate trends and patterns, and highlight factors that can be modified, in the form of process maps, to improve business process understanding and management as a whole.” To simplify, it is a method that presents a detailed view of the workings of an organization.
In essence, it is the precursor to process automation. The commonality between the two is the “process”- the basic unit of business operations. In order to understand the scope of automation in a particular business, it is most important to first know every detailed aspect of the functioning of the business.
Process mining helps create a visual representation of digitally performed processes on various levels of an organization and identify specific parts of operation that require improvement. In this manner, it helps organizations determine nominees for process automation, analyze business operations, restructure processes, and redesign business models.
Additionally, when setting out towards digitalization, organizations must remember that robotic process automation (RPA) is a huge task to undertake. Having an elaborate plan BEFORE adopting process automation is essential. Process mining ensures organization wide transparency and aids organizations create plans based on detailed information.
While it is becoming more important to adopt RPA, many businesses are worried about the transformation failing. It is widely understood that RPA/ IPA implementation needs to be planned, phased, and carefully monitored. Operational transparency and centralized analysis make it easier to identify how and when an organization should roll-out their transformation efforts.
But what has this got to do with process mining? How exactly does it support the implementation of RPA?
Creation of a visual map
It charts out end-to-end processes, giving an overview of bottlenecks, process gaps, high impact areas and areas with potential of increase in ROI. It also helps eliminate redundancies and highlight problem areas. This in turn, facilitates automation related decision making.
To elaborate, if a certain process is taking longer to perform than anticipated, is causing delays in further processes, is vital to the workflow, and has the potential to be automated, then a process map visually indicates that it is an area that should be prioritized while considering RPA. On the contrary, if a certain task is taking long to execute, but is not vital to the workflow, process mining will spotlight this redundancy, saving the organization the effort of automating said process.
Analysis of human-bot relationships
In organizations where partial automation is in place, the interaction between human employees and the digital workforce can provide insight into how to progress from that point.
In many instances, human-bot interaction is awkward or complicates the process more than necessary. This becomes visible in the form of delays, errors, and repetitions. When such issues are highlighted, the organization has the option to introduce more advanced technology or retract to traditional functions.
Performance Comparison
Even though process mining cannot record and evaluate manual functions, performance metrics can generate a comparative value for pre- and post- automation. It acts as a measurement of improvement.
For instance, many smaller organizations cannot afford to adopt complete digital transformation. For this reason, they implement RPA only for specific repetitive tasks. Process mining helps measure the increase/decrease in productivity, efficiency, accuracy, and timeliness of these processes and allows managers to make decisions regarding expansion of automation.
RPA Lifecycle Support
Process Mining and robotic process automation are co-dependent automation technologies. Process mining plays a crucial role in every stage – pre/mid/post deployment – of RPA implementation. It also helps in creating foundations or process maps that outline the functioning of bots to create the preset templates for bots to follow.
To Conclude,
The most important aspect of process mining is that it highlights efficiency – processes that are being performed with excellence can be made even better with automation. At the same time, it also highlights weaker sections of operations so they can be diminished by application of RPA. Besides this, it is also beneficial in keeping track of the day-to-day performance of a business, identifying deviations or malpractice, and promoting compliance.
Process mining identifies areas of improvement, helps control automation efforts and measures process optimization. When placed beside RPA, it emerges as the ultimate supportive tool for enterprises that set out on the route of digital transformation.
