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Process Mining provides a new means to improve processes across all industries. It is an innovative analytical approach that analyzes data from IT systems to gain objective insights and uncover hidden problems.
When employees perform their tasks, or customers interact with a company, traces of their actions (e.g. what happened and when) remain in the information systems or in the machines that perform the operation. Records of individual actions taken, such as ‘approve loan’, or ‘request information’ are called ‘event data’. Process Mining software uses event data to automatically reconstruct a map of the entire process and its variants, in order to analyze the process and uncover inefficiencies, exceptions, unusual transactions, bottlenecks, deviations, weaknesses & risks.
Business owners know their processes well from a theoretical perspective: what is supposed to happen, when, who is supposed to do what, under which condition. However, they lack the insight into what is really happening throughout the process lifecycle. Traditional reporting, Business Intelligence (BI), and statistical tools are not able to detect deviations, bottlenecks, and waste, or investigate their causes.
Process Mining builds upon the traditional model-based process analysis such as simulation and other business process management techniques and enhances it with data-centric analysis techniques. It is a groundbreaking new tool to discover the real process, in order to control and improve it facilitating continuous process improvement and process compliance.
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HigherProcess Mining aims to provide actionable information – information related to the redesign and structural change of the process. Each Process Mining project is a collection of use cases with a set of goals and corresponding actions. The goals could be to improve KPIs – time, cost, quality or risk. For example, to minimize the mean flow time, waiting time, or response time, or to maximize the service levels – the percentage handled in the period.
The result of the analysis could be a recommendation to adjust process parameters such as temporarily add resources at peak times. Or to intervene at the level of individual cases or resources to handle a problem in an
By reconstructing the process from data already present in IT systems, Process Mining allows organizations to diagnose problems based on facts rather than assumptions. This approach eliminates subjectivity and human errors from the analysis and facilities more exact and systematic process improvement.
Process Mining is as universal as a spreadsheet. Where spreadsheets work with numbers, Process Mining uses event data from IT systems. It can be applied for all processes form purchase-to-pay, order-to-cash, hire-to-retire, customer care to IT management processes, and in every industry sector from finance, manufacturing, and retail to logistic services.
Using Process Mining software reduces the analysis time by weeks on end and minimizes the costs by reducing the number of analysts and consultants. The software is also able to analyze millions of events on the fly – impossible by traditional model-based methods.
Process Mining bridges the process knowledge gap that exists between various systems, departments, and functions and at the edges of processes. The same analysis can be repeated anytime with fresh data almost without additional costs. Thus, supporting improvement based on the continued assessment on the effects of changes can be repeated.