Process mining is a way of discovering and improving business processes. It is projected that the market will grow by up to 40-50%, turning into a billion-dollar market in 2022. It is being applied to various industries such as transport and logistics, healthcare, banking, etc. Recent case studies show that retailers, finance companies, or telco organizations are prime beneficiaries of this new technology.
A major problem in process automation is the poor understanding of the underlying business processes. By analyzing and visualizing processes, process mining helps companies discover the areas that need automation. If in 2019, organizations were interested in process mining to improve business processes, in 2022, they are using the technology to drive digital transformation across the entire company.
Digital twins of organizations technology combine digital twin technology and process mining. Its main goal is to discover, optimize and stimulate a company’s internal processes. With DTO, companies can run numerous “what if” scenarios to make the best decisions.
Machine learning and Artificial Intelligence allow process mining to be automated and make it easier to model and predict. Machine learning algorithms enable users to model, discover, and forecast business processes in Python, R, Java, and other programming languages.
A further application of AI technologies to process discovery is to identify human interactions using computer vision, resulting in the discovery and modeling of workflows, which can be used to speed up the implementation of process mining solutions. These use cases are more effective than manual process discovery. Some vendors and academics refer to AI-powered process discovery as automated process discovery.
Machine learning will play a more significant role in process mining when organizations have more accurate process data. Process mining tools can pull data from all enterprise systems through integrations. In 2022, the traditional process mining methods, such as manual process discovery and conformance-checking, will still be used.
Although vendors and businesses may be interested in AI capabilities for process mining tools, the role of human intelligence in this field will not change anytime soon. New data-driven technologies can help to link human and artificial intelligence for more precise results. Human intelligence (HI) is a crucial component of process mining. HI is evident in process mining developments such as object-centric (OCPM) and action-oriented process mining (AOPM).
OCPM aims to eliminate the assumption that there is only one object in process mining tools. The belief is that one case identifier is the basis of process mining tools. In reality, however, one event could refer to multiple objects (e.g., a customer or multiple items and a place).
AOPM assists in turning observed events into management actions that guide the operational system and automates the correction of processes that have been identified by process mining. AOPM requires human intervention to resolve unusual situations.
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