What is Process Mining?
Process mining is a technique designed to discover, monitor, and improve real business processes by extracting readily available knowledge from the event logs of information systems.
Process mining helps organizations gain a full understanding of the processes that support their customers through the examination of the actual processes, which often differ from the documented processes that they currently use.
Process mining discovers, monitors, and improves real processes based on information from business event logs. Process mining includes:
- Automated process discovery and extraction
- Conformance monitoring
- Social network mining
- Automated construction of simulation models
- Model extension and repair
- history-based recommendations
- And more!
To discover and optimize business processes, process mining usually follows a series of steps:
- Select any business process
- Collect event logs from all systems (usually done automatically)
- Reconstruct and visualize the process from transactional data
- Identify and implement improvements using artificial intelligence (AI), machine learning (ML), and analytics models
- Continuously monitor and make improvements based on that information
Process mining enables customers to identify business process issues and build a prioritized list where the most costly inefficiencies are in their businesses. Additional benefits include:
- Increased efficiency by removing bottlenecks, improving cycle times, and streamlining processes
- Cost reduction associated with duplication, rework, and manual processes
- Improved compliance by detecting non-compliant processes or fraud
- Continuous business optimization by improving processes and monitoring them in real-time
- Enhanced customer service and satisfaction via improved customer-centric processes
To achieve significant, new, and sustainable cost savings and continuous improvement without hampering your ability to deliver, you need greater transparency and insights into your business. With intelligence-driven process mining, key stakeholders can quickly visualize, identify, and quantify bottlenecks and inefficiencies across their business. Thus, they can identify a prioritized list of changes with the evidence to deliver cost-saving improvements.
Business users and key stakeholders can drill down into as much detail as needed to see how efficiently processes are running,and if there are issues, what and where they are occurring. This capability works across all systems and lines of business:
- Acquisition of new customers and customer service
- Claims processing, investigations, and settlements
- Policy administration and mid-term adjustments
- Third-party loss adjusters, repairers, and so forth
- Underwriting
- Procurement, HR, finance, and more
With process mining, organizations can identify previously unknown cost-reduction opportunities and show evidence and metrics of issues.
Why Process Mining?
You have standard processes for every part of your business. There is a clearly laid out route map for each process in your business. For instance new policy acquisition, claims processing, and shipping products are all examples of business processes. But, do you know how often these processes go off track? Or how much things get held up when they do? Or do you know where in your processes these variations from the norm happen? These variations in processes can number in the hundreds or even the thousands. A majority of businesses today experience issues in their organizations due to misunderstood business processes.
Traditionally, this type of analysis was done manually with employee interviews. However, this was very error prone as two individuals can often have very different views of the same process with incomplete information. This is a very long process that is error-prone.
Now, with process mining, you can tap into your most precious resource: your operational data and log files. All transactions and user interactions are recorded in your systems (Policy, Claims, CRM, for example) as a digital footprint. This digital footprint can be analyzed to reconstruct how business processes are actually running, instead of just what the process owner’s flow chart shows. This is a very fast process and gives organizations an easy way to identify bottlenecks.
Process mining, using AI and ML, can tell a company where bottlenecks are and help them to improve processes. The results of the AI analysis are presented in a very simple visualization to create boardroom visibility but also supports drill down into specific detail for process owners and key stakeholders of all core processes.
Process mining efforts allow you to drill down into any part of your business and get the specifics on any process such as time, cost, or resources. Process mining is like putting your business through an MRI scanner. It uncovers details that were, until now, invisible. Process mining allows organizations to see clearly what is working and what is not working throughout the business and why. Process mining gives organizations metrics and the root cause of issues so they can take the necessary steps to get processes running smoothly. Process mining can lead to transformational cost savings for any organization.
Benefits of Process Mining
Including more insight into your business processes, the benefits of process mining are many:
Discover
Discover what’s actually happening in your business processes from live application data. You can see how your business processes operate from real operational data.
Analyze
Analyze your processes and find the root cause of inefficiencies. Understand where you spend time in what activities, and identify where bottlenecks are located. Find patterns and behaviors by looking at how resources perform process activities.
Check
Check planned performance versus actual so countermeasures can be taken where necessary to make the largest impact. Score your processes against reference models for optimum performance.
Predict
Use insights from historical cases to predict the path, cost, complexity, and duration of your in-flight cases. Build predictive analytics models that can be applied to your organization to improve the identification of issues.
How Does Process Mining Work?
First, process mining discovers how business processes perform based on real data taken from an organization’s operational systems. This discovery is performed automatically using advanced descriptive analytics to discover the “real process.” With this data, process mining discovers bottlenecks, determines the most time-consuming activities, and identifies areas of improvement within your processes. Then, using AI and analytic models, process mining scores your business processes against reference models and addresses compliance issues.
Process mining identifies business processes that are good candidates for automating and measuring before and after performance. Then, the process mining administrators work with the business owners to determine improvement areas based on KPIs and industry benchmarks—making suggestions to rebalance resources based on that performance. Finally, using historical case insights, process mining can predict the paths, costs, complexity, and duration of your in-flight cases.
As you can see in the image above, business processes usually involve moving a project from position “a” to “d.” However, there are many routes to get there. You can have several variants in your model. Process mining is able to automatically extract all the possible variants. Anytime you come across a specific variant, a case is generated. A case is a collection of activities executed over time, usually by a person or systems. When you drill down into all of the data and visualizations generated by process mining, you can start to discover which processes follow typical routes and those that have a lot of variants. From there, you can make improvements.
The more technical capabilities of process mining include:
- Connectivity and extraction of event log data
- Data preparation and data virtualization to unify data and make it useable
- Computation of process mining algorithm
- Storage of variants, cases, and metrics into tables
- Visualization and exploration of processes and data
- Combine with AI and ML models
- Case management for raising, tracking, and automating
Process Mining Case Study
Organizations that have implemented process mining have experienced as much as a 25 percent time savings by uncovering and fixing bottlenecks. In fact, Invitalia, the national agency for inward investment and economic development of Italy, needed a way to manage a large amount of applications and optimize processes to review them. Its old business processes created an incomplete, outdated view of performance for the organization. Invitalia wanted to reassess and improve its end-to-end business processes to save time and increase scalability for better decision-making. The organization worked alongside TIBCO LABS to create a process mining solution and visual analytics to improve the execution of enterprise-wide business processes. The results were reduced time and cost by identifying and removing bottlenecks. Invitalia achieved 100 percent operations compliance with segregation of duties in accordance with company policy and saw 35 percent faster funding approval.