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Process mining

Process mining (PM) is a technology for creating interactive business processes (BP) based on digital traces and their in-depth analysis.
Process mining (PM) is a technology for creating interactive business processes (BP) based on digital traces and their in-depth analysis. As result BP model provides an opportunity to evaluate the specific BP effectiveness, analyze the main deviations and formulate steps for improvement and optimization.

Examples of PM programs are: Celonis, Fluxicon, Disco, ProM, PM4PY.

What exactly do these programs allow to carry out:
1. Analysis of the entire chain of BP events, not individual steps
2. Analysis of all cases, not a limited sample
3. Automatic control of deviations from regulations in accordance with standards
4. Predict the choice of scenario or time of completion for not yet completed processes
5. Continuous collection and processing (updating) of data
6. Simulation of future processes with assessment and preliminary optimization
According to a 2018 Gartner study, process analysis technology can play a key role in digital business transformation.

Requirements for Process Mining Deployment:
1. A high level of process automation, high digitalization of systems
2. Availability of event logs (activity logs), which record user actions in the system
3. High level of systematization and development of processes
Where PM can be particularly helpful:
1. Supply-chain management
2. Product speed launch
3. Cost management of back-office operations - automation and robotization of processes
4. Service quality (NPS indicators)
5. Setting and tracking KPI teams

Basic steps in PM:
1. Understanding the regulated process
2. Collection and preparation of activities in the system (logs)
3. Analysis of the process «as is»
4. Search for "bottlenecks" and deviations from the regulated process
5. Recommendations development for optimization and improvement

Examples of BP optimization effects on the payment process case:
1. Decrease in the reversal transactions share
2. Reducing the share of alternative process scenarios
3. Reduction of errors in the payment items
4. Reducing the volume of re-editing positions
5. Prioritizing RPA Automation and Implementation Initiatives

Basic steps in implementation:
1. Choice of technology
2. Search for a customer and a contractor
3. Launching a pilot project
4. Creation of a center of excellence and a center of analysis
5. Change management and success story

As we can see from the above, with proper implementation and an appropriate level of organization development, Process Mining can be a competitive advantage that allows you quickly and efficiently adapt your business to a rapidly changing external environment.


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