Process mining definition
Process mining is a methodology by which organizations collect data from existing systems to objectively visualize how business processes operate and how they can be improved. Analytical insights derived from process mining can help optimize digital transformation initiatives across the organization.
In the past, process mining was most widely used in manufacturing to reduce errors and physical labor. Today, as companies increasingly adopt emerging automation and AI technologies, process mining has become a priority for organizations across every industry. Process mining is an important tool for organizations that are committed to continuously improving IT and business processes.
How does process mining work?
Process mining begins by evaluating established IT or business processes to find repetitive tasks that can by automated using technologies such as robotic process automation (RPA), artificial intelligence and machine learning. By automating repetitive or mundane tasks, organizations can increase efficiency and productivity — and free up workers to spend more time on creative or complex projects. Automation also helps reduce inconsistencies and errors in process outcomes by minimizing variances. Once an IT or business process is developed, it’s important to consistently check back to ensure the process is delivering appropriate outcomes — and that’s where process mining comes in.
For example, an IT department might decide to automate its help desk ticketing system. Previously, an employee would take time to review a ticket, determine the correct category and assign it to the right employee. IT departments can create automated processes to categorize and assign tickets as they come in — freeing up workers to spend more time addressing customer issues. Once these automated processes are in place, however, it’s equally important to ensure the process regularly delivers the intended outcome. As new technologies are implemented, process mining can help the company retool the process to accommodate new ticket categories, staffing changes and varying industry trends.
Process mining techniques
Process mining enables organizations to ensure automated processes are efficient, consistent and reliable. With process mining, companies can enable automated decision making, simulate processes to predict future outcomes, identify gaps in organizational leadership and ensure implemented processes are continuously improved. There are three classes of process mining techniques, each of which reflects a specific use case or focus for process mining:
- Discovery: In the discovery class of process mining, there are no past models to work from so your organization must start from scratch. A new model is created based off gathered information and requirements, and then an algorithm is developed to analyze data that will establish a model for your process.
- Conformance checking: Conformance checking happens when there is a process model already established and running. During this phase, companies compare data from the process event log step-by-step with the process or model to find discrepancies or deviations. Any determined variances are analyzed to see which data elements influence process outcomes. In some cases, improvements may be made, or it might confirm that the business or IT process is running as expected.
- Performance mining: Performance mining is also used when there is already a process in place, but it is intended to make space for new process performance. For example, a process might be expanded to accommodate cost adjustments, budgets, technology changes and processing times. Process mining can help organizations make process adjustments and then ensure they deliver the best outcomes.
Plenty of third-party services are available to help companies tackle the job of process mining. These software tools help companies collect the relevant data they need and deliver insightful analytics based on the data they pull.
Process mining software can help simplify process documentation and enable companies to make quick changes if new compliance regulations are introduced. It’s important to continuously monitor processes to ensure the best possible outcomes. While you can’t always control the outcome due to variations, it is possible to control, fix or improve the process to create better products, services and tools.
Process mining tools can automatically create visual maps for organizations to see step-by-step how a process works, where it works best or breaks down so companies can make incremental improvements over time to create better outputs. There are plenty to choose from, some popular process mining tools and software include:
- UiPath RPA
- ARIS Process Mining
- Kofax Insight
- Icaro Tech EverFlow