What is process mining?
Process mining is a discipline that bridges data mining and process management, allowing organizations to visualize and analyze their processes based on factual data from the execution of a process – all to drive continuous optimization.
As part of a continuous optimization strategy, process mining enables organizations to:
- Understand their processes
- Identify and fix process inefficiencies
- Monitor and optimize processes on an ongoing basis
Why use process mining?
Process mining gives you insight into your business processes so you can make data-driven decisions about how to improve and optimize workflows.
Other common approaches to process discovery and visualization – such as interviews and observation – can be manual, time consuming, and costly. Additionally, they’re limited in their ability to produce useful and accurate data about how processes are running due to subjectivity, human error, and small sample sizes of focus groups.
Process mining uses event logs to look at all of your processes, providing you with a holistic, data-driven view of how your business is running. And once you have that view, you can use process mining’s analysis capabilities to identify the root causes of inefficient processes.
Benefits of process mining
- Increases efficiency. Process mining reduces the time and effort necessary to complete required tasks by removing obstacles to working quickly and efficiently in your workflows.
- Saves costs. Process mining offers multiple opportunities for across-the-board cost savings by reducing bottlenecks, reworks, and the need for manual labor, as well as improving the accuracy and quality of work.
- Reduces risk. Through ongoing monitoring of your processes, process mining allows for greater compliance with regulatory requirements by reducing the risk of human errors and fraud in your workflows.
- Improves customer experiences. With process mining, you can identify the areas of friction in your processes that frustrate customers and uncover inefficiencies in automated, customer-facing workflows.
How does process mining work?
Process mining uses event log data from the systems that support the process’ execution to generate visualizations and process maps that model the lifecycle of your processes – so you can make data-driven decisions about how and where to improve your processes.
What’s the difference between process mining and task mining?
- The practice of processing historical and near real-time event logs to understand and analyze your processes and identify inefficiencies and enhancement opportunities
- Carried out at the level of the systems that support an organization’s process execution
- Best used when you want to identify inefficiencies within a business process, such as slow transitions, reworks, and bottlenecks
- The practice of capturing process-related information through user actions and metadata to provide insights into the tasks and activities involved in executing a process
- Primarily carried out at the micro-level and is concerned with an individual user’s actions on the desktop
- Best used when you want to understand your employees’ behavior at the individual user level and look for opportunities to automate manual, repetitive tasks
Frequently Asked Questions about process mining
Process mining and business intelligence (BI) tools are both analytical tools that aim to depict reality using underlying data. Both usually have the ability to slice and dice data to help correlate information and drill down to specifics.
However, process mining differs in several fundamental ways: First, it analyzes process data rather than general business data. Process mining data requires information to be formatted as an “event,” which has three parts: a timestamp, a case ID, and an activity name. This allows process mining to perform activities like discovery, enhancement, and conformance, which BI doesn’t have the capability to do.
Additionally, process mining focuses on helping you visualize and understand why your process inefficiencies are occurring, while BI focuses on measuring KPIs and outcomes with dashboards and scorecards.
When combined with a workflow automation platform, process mining offers you the tools you need to identify inefficiencies in your processes and eliminate them through automation or other corrective actions. Then, you can use process mining to identify any new or lingering issues with your recently improved processes and continue to improve them through your workflow automation platform. Repeated on an ongoing basis, this cycle of identifying issues, resolving process problems, and monitoring and optimizing as you go supports the idea of continuous process optimization throughout your organization.
A process mining solution should be easy enough to use so that anyone in your organization – from business users to developers – can participate in the continuous optimization process. Additionally, it should have a big data architecture that can scale confidently and efficiently so you’re able to transform your processes in the present and future. And it should integrate well with your workflow automation platform, so you can easily turn your mined insights into action.
Process mining can identify processes that are unnecessarily slow, costly, and frustrating for customers. Once those processes are improved, organizations can benefit from reduced cost of doing business, the ability to free up resources to pursue innovation opportunities, and an improved customer experience through reduced friction in the customer journey.