Conformance checking — checking compliance

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[*]The actual course of activity is compared with the standard prescribed in a specific organization. At the initial stage, the real process is reconstructed in accordance with the following algorithm:

identifying the actual sequence of actions;

formation of the "process word";

detection of repetitive and standard operations;

identifying the percentage of processes that correspond to the reference path;

finding "happy paths";

search for behavior patterns.

Enhancement - improvement
The goal of this stage is to jordan email list optimize the process according to the findings of the previous stage. Based on the results of the analysis, algorithms are redesigned and the proposed modifications are pre-tested.

Process Mining tools help in drawing conclusions:

graphical presentation of analysis results, creation of information panels;

development of professional advice and proposals;

predictive assessment of the results of implementing improvements;

streamlining and improving the efficiency of business operations.

Then redesign and modeling takes place:

putting forward initiatives to improve processes;

testing of the proposed modifications using quantitative modeling methods.

Monitoring — tracking
The task of the final phase is to monitor the correct functioning of the modified process, as well as to control the compliance of the actual results with the original intentions. At the final stage, systematic monitoring of the algorithms is organized, including the provision of information on the accuracy of the procedures to the relevant stakeholders:

regular assessment of key process performance indicators;

verification of the algorithm's compliance with internal standards and rules;

monitoring and signaling of non-standard transitions, including errors, process defects and fraudulent activities;

identification of stages with high resource consumption;

informing responsible persons about identified deviations through various communication channels.

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Data sources for Process Mining technology
A high level of process automation is a key factor for using PM technologies. Data sources can come from various systems. The most effective are those whose architecture was initially designed to support processes and manage workflows.

These include Process Mining systems of the ERP/EAM, CRM, BPMS, ITSM class. These platforms store historical data on changes in the state of objects, be it assets, work orders or user requests.

Data sources for Process Mining technology

Source: shutterstock.com

In fact, information for process analysis can be extracted from any transactional system. Process Mining tools can work with data from the following classes of systems:

data warehouses;

OLAP repositories;

enterprise resource planning (ERP) systems;

customer relationship management (CRM);

processing of applications;

Application Performance Monitoring (APM);

error tracking;

management: product data (PDM);

documents (DMS);

IT services (ITSM);

software configuration (SCM);

projects.

The main condition is the presence of multiple event logs and traces in the system - the actual process is reconstructed using them.

The key parameter for assessing the suitability of a source system for the application of the PM methodology is the answer to the question: "Is it possible to reconstruct a picture of the process execution based on the collected information?"

The effects of the implementation of process analysis tools, it becomes obvious that this technology is rapidly evolving. This is due to its practical use in real conditions of commercial organizations.

It is safe to say that as automation of current business operations increases, the number of adherents to Process Mining methods will steadily increase, since optimization of operational activities is a key trend in modern entrepreneurship.

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