Businesses have been using AI-based automation to improve efficiency and streamline operations. In order to improve their real processes as they pursue this, they require a method of looking beyond their presumptive procedures. They believe that process mining is a vital tactic for achieving this goal.
Automation can be as simple as robotic process automation (RPA), a field that has experienced phenomenal growth. Hyperautomation, which Gartner characterizes as a business-driven, rigorous way to quickly identify, analyze, and automate as many business and IT operations as possible, is another strategy that is now receiving prominence.
It might be challenging to decide which company procedures to automate. Cognitive biases, false assumptions, and a lack of in-depth understanding of ground operations are just a few examples of the factors that might impair decision-making and hinder innovation.
A thorough grasp of the performance and operation of current processes is required. This can be provided through process mining.
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Process Mining Is A Crucial Step Before Automation.
Process mining is a technique for obtaining important data and useful insights from event logs, which are digital recordings produced over time by information systems. It is possible to precisely record each step of the processes involved and identify any deviations from their planned trajectories by filtering, processing, and arranging this data.
This enables businesses to accurately depict business processes and their variations and to continuously monitor them. Organizations can dramatically improve workflow optimization through automated process discovery and mapping.
According to Marc Kerremans, VP analyst at Gartner, “Process mining plays a crucial role in generating visibility and understanding before you automate, and it creates the foundation for business operations resilience, which helps you adjust operations in the face of changing business conditions.
Process mining, he continued, is not just essential for building visibility and comprehension before automating. It also shows how various islands of automation are connected and how they might be improved through its monitoring capabilities.
Best Techniques For Automating Processes Effectively
According to Jaclyn Rice Nelson, cofounder and CEO of data and AI consulting business Tribe AI, in order for automation to be successful, fundamental organizational difficulties must be resolved. Effective change management is necessary for process automation, she noted.
More difficult than the technological work needed to automate the processes has proven to be change management. According to Nelson, the CEO’s dedication to automation makes the difference between businesses that succeed in this shift and those that suffer. The effectiveness of process mining and automation activities depends on leadership support and team incentives that are in line with automation. Process automation investments will fail without [buy-in and alignment].
What Is The Future Of Automated Process Mining?
According to Gartner’s Kerremans, process mining will eventually automate other crucial use cases in a company, such as process analysis, comparison, and discovery for compliance, auditing, sustainability, business design, and composability.
“Processes are interdependent; they never exist in isolation. So, it is crucial to step back from procedures and adopt a business operations viewpoint in order to link to a digital or business transformation. Hence, it is crucial for business operations to integrate the processes, interactions, and activities that produce goods, services, and information and, in the end, add value for clients and other stakeholders of the company, according to Kerremans. “Process mining without action is a daydream, and action without process mining is a nightmare,” says one expert. “Process mining and action/automation are extremely firmly intertwined.”
The next stage in process mining, according to Nelson of Tribe AI, is to make it possible for models to access APIs, get rid of tedious business procedures, and improve output quality through automation.
“The ultimate action-driven AI future is automation applied to the identification and even resolution of automation possibilities,” she continued.
Writer’s Alshikh, for his part, thinks that process mining will advance more as hyperautomation technology advances. Hyperautomation will enable businesses to become even more data-driven, since advancements in process mining will better guarantee the accuracy and completeness of the data gathered.
