Process Mining
Discover how you can reduce costs, increase efficiency, and optimize processes.
Discover
Understand how business operations are executed by discovering “as-is” process diagrams based on event data from an IT system.
Analyze
Analyze data to identify friction points in a business process and relate these friction points on key performance indicators.
Understand
Understand what makes the difference between desirable and undesirable process outcomes, for example between orders that are delivered on-time versus orders that are delivered late.
Identify
Identify non-compliant behavior, understand the root causes of deviations, and quantify the impact of these deviations on process performance.
Predict
Predict the future performance of a process under different scenarios to make better decisions and to prioritize their process automation and process improvement efforts.
Continuous optimization.
Custom metric thresholds and automated alerts help process owners be aware of new areas for improvement.
How Process Mining Can Ensure Successful ERP Migration
Process mining combines computational intelligence, data mining, process modelling and process analysis to discover, monitor and improve real processes. Event logs recorded in enterprise information systems form the basis for all process mining techniques to extract relevant knowledge regarding process activities and instances as well as additional information about resources that initiate an activity, timestamps and any other process-related data elements that have been recorded.
The Process Mining Manifesto defines three broad types of process mining techniques:
- Process discovery: Discovery techniques focus on extracting process models from event logs without requiring any additional information about the activity.
- Process conformance: Where discovery creates process models from event log data, conformance techniques are used to monitor process deviations by comparing event log data against an existing process model. Conformance techniques can also be used on-the-fly to provide real-time warnings, predictions, and recommendations based on comparing the existing process model with event data related to running process instances.
- Process enhancement: In this technique, the combination of an existing process model and actual process log data is leveraged not just to establish conformance but to actually reengineer, extend and update the existing process model.
PROCESS MINING KEY BENEFITS
Reduced costs
By revealing inefficiencies, bottlenecks, and tasks that can benefit from automation, organizations can significantly reduce their operating costs.
Increased transparency
Process mining helps stakeholders locate the right data and create actionable insights.
Improved performance management
Automating the collection of key performance indicators. Stakeholders can continually monitor processes in real-time.
Improved customer experiences
Organizations can get to the root causes of issues quicker, allowing them to react fast and provide better customer service.
Improved compliance
Auditing is costly and time-consuming. This technology can analyze data faster and stakeholders can identify compliance issues in real-time.
Reduce reaction time
Constant process monitoring via process mining tools enables companies to react faster. Thus, if a problem occurs, the software can identify its cause faster and the company can react accordingly.