Process mining is a technique that analyzes how a process performs based on its event log. It is a source of data, knowledge, and insights that considers each process step and variation.
Most organizations are interested in fixing things but spend little time learning how their current process works. Most teams use their intuition and use shortcuts to fix issues, which can be significant and costly mistakes.
Intuition and shortcuts rarely work well.
Using data to understand how processes work is essential to making the necessary changes to move the needle.
This is the essence of process mining. It focuses on the “as is” state to determine how the process performs in its current form to help redesign what fails to produce sustainable value for the enterprise.
How Does Process Mining Work?
Things can become complex in a cross-functional business process and tricky for business improvement teams who need to clarify where bottlenecks occur. Hence the need to gain insights from the EPR, EHR, and CRM systems to determine if things are functioning the way they should.
It is precisely what process mining reveals.
Process mining captures information from any IT environment. It focuses on transactions to provide detailed data from event logs that inform how key process steps perform compared to KPIs.
The algorithm used to run event logs offers numerical proof of how work is completed, and the process’s analytics of these inputs, throughputs and outputs help determine priorities.
In other words, which process steps need immediate attention, and which ones influence performance the most. It allows teams to understand their end-to-end process in detail, be more laser-focused, and enables managers and leaders to remain objective.
The Different Types of Process Mining
Three different process mining techniques allow teams to map processes and discover gaps and inefficiencies in workflows.
These techniques are:
- Process discovery – This technique extracts and visualizes process models from event logs.
- Conformance checking – This technique checks how existing patterns conform with a predefined model.
- Model Enhancement – This technique analyzes a data-driven process model for optimization potential.
Process mining reveals areas that need improvement to avoid automating nonsense. It also helps assess results, simulate workflows, and predict how changes can impact performance.
The Importance of the IT Environment
The IT environment is an essential part of the equation, and the company needs to have digital processes from an ERP, EHR, or CRM to run event logs.
It does not mean that the end-to-end process needs to be entirely digitized to successfully run a process mining project.
That said, things can be trickier if the company uses old disconnected legacy software or its process is not digitized. In these cases, data extraction may be fragmented and more complicated. But, not impossible.
Process mining plays a central role in improving digitized operations or helping companies with their digital transformation. It considers contextual relationships of processes and analyzes them to diagnose flaws based on facts and not intuition.
Through measuring event data and process models, process mining helps identify deviations, verify compliance, support sound factual decision-making, and helps in the re-design of processes. Connect with our team if you need more information.