Process mining refers to an advanced method of leveraging and analyzing data. With the use of process mining, businesses can improve their methods of data collection and analysis, and gather real-time information about how their data is impacting their operational success.
Effective process mining enables organisations to optimise their daily processes for maximum success. It’s a strategy and approach that many new and well-established businesses are adopting, and for good reasons.
In this article, we’re going to explore process mining in more detail. We will start by defining at what process mining is and follow up with its key features and benefits.
What is Process Mining?
Process mining is an approach to data collection that is used in data science. It uses a log system, where a log is generated every time a user request or function request is created.
The log will detail when and where the log was generated, as well as why it was generated (such as the user’s problem or request). As an IT technician processes the logged request, they may update it on the system to keep written records of what they’ve done and when they’ve done it.
Process mining improves the visualisation and utilisation of the log system, enabling businesses to respond to logged requests more easily and improving problem resolution. It logs events in chronological order to provide accurate, real-time data that businesses can use to improve their operational processes and service for customers or clients.
There are three main types of process mining – discovery, conformance, and enhancement. Each one offers unique features and benefits, although they all work in similar ways and provide real-time data visualisation and improve data privacy for businesses.
Discovery extracts process models directly from a generated log. It provides key information on how various activities and updates on this log are interconnected, creating a well-rounded overview.
Conformance checks that a business’s processes are aligned with the standard guidelines or pre-determined rules. It highlights any deviations from these rules, bottlenecks, or outliers so the business can take the necessary actions to eliminate them.
Enhancement works to optimise existing processes within the system to improve efficiency and accuracy. It uses information from previously logged and resolved requests, and insights from mining.
What Are the Key Features of Process Mining?
The key features of process mining include:
- Log analysis – process mining starts with a generated log, which details when and where a request was created. These logs provide the foundations for understanding data and improving its processing.
- Discovery and visualisation – discovery processes can be used to analyse logs and data to identify patterns and relationships between them. These patterns enable easier visualisation of various business processes.
- Conformance checking – this element of process mining evaluates whether the actions following the generation of a log align with the pre-determined rules or standards. Conformance checking ensures the appropriate actions are taken to resolve queries and logs efficiently.
- Performance analysis – process mining enables businesses to analyse their chosen key performance indicators (KPIs). It provides easy visualisation of metrics during a given time period to measure operational success.