What is Process Mining and how does it work?

65% of companies are either currently using, or beginning to adopt, process mining to improve operational efficiency. But, what exactly is process mining and why is it helpful?

Process mining is one of the practical business applications of discovery, extracting data from your systems to help you understand, monitor and improve real processes. It uses event log data to accurately create process models showing how specific processes are executed and comparing that to how they should run. These insights can help decision-makers uncover efficiencies and opportunities for better business processes.

The power of process mining is that it doesn’t just show you how your processes run; it highlights variations, inefficiencies and other areas for improvement. Process mining can also help you assess how eligible new processes are for automation, so you can keep scaling your intelligent automation (IA).

Process mining is a key tool in the process science field. Taking a data-driven approach to analyzing, improving and monitoring business processes, it fits within several other business disciplines. It’s often used to select and optimize processes for robotic process automation (RPA) and can play a key role in business process management (BPM). Plus, it can be combined with RPA and advanced technologies like artificial intelligence (AI) and machine learning (ML) to create our full intelligent automation solution.

There’s a lot to be said about using process mining to benefit your IA platform by increasing it's efficiency and value. It requires strategic planning and understanding and is wholly worth the dedication for the value achieved in ROI and customer and employee satisfaction.

True end-to-end understanding of processes

Process mining lets you capture an accurate image of how your processes are performing. You get process-visualizations of the flow of your work through each of the process stages, identifying all delays, bottlenecks and outliers.

Without these process mining techniques, your business process improvement goals are based on guesswork or are super complex and time-consuming. To properly analyze process performance, you’d have to perform manual data reviews and interviews with your users. This isn’t just a slow process, but one with a high margin of error.

Speed up and improve your processes

By removing bottlenecks, you can improve processing time for tasks, allowing for easier scalability. Understanding and tackling issues within your workflows will help you increase accuracy and streamline the flow of processes.

Compliance risk management

Process mining makes compliance easier by using audit trails to create a model of your processes. You can monitor processes in real time and be alerted immediately of any issues. Process mining used to rely on subject matter experts (SMEs); but now, decision-makers are given facts on real-time event log data to back their decisions.

Reduce costs

Eliminating inefficiencies and discovering more tasks for automation will also help you significantly cut operating costs by driving down the cost of process evaluation. Plus, with human workers not needing to perform manual analysis, they can focus on higher-value, more interesting work.

Improve customer satisfaction

Using process mining on customer service journeys leads to better customer experiences. You can reduce the time it takes to serve customers, reduce frustrating mistakes and free up staff to devote more time to client care.

Continuous improvements

Process mining is not a one-and-done technique. You can use it to provide continuous improvement to processes across your organization.

Process mining tools extract data from information systems’ event logs. These might be Enterprise Resource Planning (ERP) or CRM systems, or any system of record. Using this data, process mining software creates an accurate process model.

Business process modeling shows how the process is executed end-to-end. It also reveals any variations. Users can then analyze the models, revealing whether processes are working as expected. If not, the models may reveal what’s going wrong and where.

We recommend following these five valuable steps to increase the productivity and efficacy of your process discovery tool usage. 

Process Discovery | Process Analysis | Process Optimization | Process Automation | Process Monitoring and Prediction

Process discovery

Process discovery is now a simple and speedy part of rapid workflows, used to analyze desktop user interaction data and link it with process details mined from system event data. Using these timestamps, the software can then create visual models to help identify the variations and bottlenecks impacting efficiency or customer experience.

Process analysis

Process analysis is where you develop an understanding of process performance based on actual data. Insights gained from process analytics may include optimal process paths, paths for the greatest return on investment (ROI) and causes of variations.

This is also the stage where you can better understand your processes by visualizing them through process mapping. Some platforms include process simulations, and with these, you can also visualize target business outcomes.

While process mining gives you insight into how your processes actually run, BPM gives you a map of your business’s ideal processes. You can use them together to improve processes for better workflow management and business outcomes.

Understanding how processes currently work is invaluable for BPM. Process mining helps across almost every step of the BPM lifecycle.

Process optimization

Using the data you’ve gathered in the discovery and analysis phases, you can now make changes to your processes to prepare them for automation. This is also where you select the most important processes on which to place your focus.

Process automation

At this stage, your process data can be exported for RPA. With insights gained in previous steps, you can choose the ‘happy path’ with the least resistance and highest ROI for automation.

Process monitoring & prediction

Some process mining solutions will monitor every process instance. This is usually only available with full process intelligence. The platform will issue alerts or automatically act when unusual process behavior occurs. Some platforms can even offer predictive analytics to further enhance your process planning strategy.

Robotic process automation (RPA) uses software robots, or ‘digital workers’, to automate the processes usually run by humans.

Process mining and RPA are perfect collaborators when implementing transformative intelligent automation (IA) in your organization. RPA can only really get going with a good stock of processes ready to automate. And how do you know which processes are ripe for automation? That’s what process mining is for.

By giving insights about processes and where they can be improved, process mining highlights automation opportunities. It also allows you to finetune processes before you automate them.

For example, process intelligence from SS&C Blue Prism allows you to:

• Choose processes to automate and run them at peak performance
• Accelerate process transformation from days to months
• Achieve an 80% reduction in process discovery time
• Gain full visibility of existing systems, processes and workloads to optimize enterprise-wide

Business process management (BPM) does exactly what it says on the tin; it helps you strategically manage your processes by modeling, analyzing and optimizing them from end to end.

While process mining gives you insight into how your processes actually run, BPM gives you a map of your business’s ideal processes. You can use them together to improve processes for better workflow management and business outcomes.

Understanding how processes currently work is invaluable for BPM. Process mining helps across almost every step of the BPM lifecycle.

Discover
Process mining helps you discover undocumented or poorly understood processes, giving you a complete view of each process on a visual dashboard.

Analyze
Process mining insights and analysis help you identify areas for improvement such as bottlenecks and inefficiencies.

Design
Once you’ve analyzed your processes, you can decide which processes to automate, keeping in mind which require human intervention. It’s not necessary to automate everything—but you have to choose wisely. Keep in mind that after implementation, the redesigned process becomes the new ‘as is’ version.

Implement
Integrate your changes into your organization with deliverables, timelines and staff training.

Monitor
Process mining tools help you monitor processes in real-time to identify issues and anomalies and fix them. As your automation is running, you’ll be able to check for issues and address them quickly. Continuously monitor outcomes and work through the five stages, adjusting, refining and improving as you go.

Process mining can be used across all industries. Here are some key process mining use cases:

Process mining for insurance companies

Example of process mining techniques in action for an insurance company:

• Mapping the claims management process, from a customer getting in touch through to pay out.
• Showing how many sub-processes in the wider claims process are still managed manually, and how many can be automated. This also shows which sub-processes could run simultaneously rather than within a chain.
• Improving customer service by dealing with cases quicker thanks to streamlined customer care processes. With faster processes, staff can spend more time on customers.

Process mining in the healthcare sector

Process mining aids the healthcare sector by:

• Visualizing processes such as initial evaluations and diagnoses, patient check-in, billing, medication management, treatment and ongoing care.
• Identifying bottlenecks in healthcare processes and creating improvements.
• Identifying why some processes take longer than others.
• Analyzing the processes for two similar care events, helping you compare regions, departments or staff.
• Highlighting to cost management the incidents and tasks that slow down and/or add extra expense to care processes.

Process mining for financial services and banking

Process mining also helps financial services and banking by:

• Reducing compliance and regulatory risks. By better understanding your processes, you can reduce opportunities for human error and improve the accuracy and speed of sanctions checks, for example.
• Improving transparency, speed and accuracy of checks. By managing processes through process mining and automation, you also create audit trails to ease future investigations.
• Speeding up loan processing. By streamlining your loan decision and granting processes, you can better keep up with modern FinTechs.

Process mining in manufacturing and the supply chain

Process mining, including process intelligence, improves manufacturing and supply chains by:

• Quickly identifying and removing bottlenecks in the supply chain process by building a comprehensive view of supply processes. This helps organizations be better prepared for the unexpected, such as shipment delays.
• Optimizing the supply chain by analyzing a real-time view of how goods and components move between different parts of the supply chain. This helps manufacturers operate a lean, just-in-time inventory model to reduce costs and stay agile.
• Pinpointing deviations from agreed KPIs with alerts warning manufacturers so they can communicate with relevant parties and keep them informed on progress.
• Forecasting when machinery will need repairs or replacements by monitoring data from SCADA, IoT and maintenance systems to build a more accurate cost analysis and keep storage of spare parts to a minimum.
• Tracking deliveries in real-time by monitoring the goods at every stage, from shipment to delivery, and keeping customers in the loop on progress.

Process intelligence is a newer approach to process analytics solutions that improve process mining. It’s designed to work with all processes, gathering detailed insight into complex processes from end to end. And unlike traditional process mining, process intelligence shows real-time overviews of processes and analyzes the patterns leading to disruptions and siloes.

It doesn’t matter how complex the process is or how many data sources it involves. Business process intelligence helps ensure continuous process improvement with far deeper insights than process mining can manage on its own.

Process mining and task mining are essential to any intelligent automation project, and each serves a different but complementary purpose.

Both process mining and task mining are about discovery. However, process mining examines how well a system flows between people and machines. It’s a broader look at overall processes. Process mining visualizes data from system event logs to give you an end-to-end view of your process performance.

Meanwhile, task mining uncovers how efficiently the individual parts of a process are managed. Task mining, for example, analyzes a desktop user’s interaction to give insight into an employee’s performance.

Task mining can be used alongside process mining as part of a process intelligence platform. Process intelligence blends the metrics of both to provide detailed insights into processes and tasks across the organization.

Together, process mining and task mining enables organizations to see where repetitive and inefficient tasks are slowing down processes so they can allocate resources in the right places to resolve them.

How process intelligence adds capabilities to process mining

Process intelligence adds new features to – and improves – process mining capabilities. For example, it may include task mining tools. Task mining works on data at the front end, giving insight into how human workers manually use their devices. It also helps clarify all the steps needed in a task and how these vary between users. By examining manual as well as automated processes, process intelligence adds more opportunities to improve RPA results.

Process intelligence can also include predictive analytics. For instance, predicting specific outcomes or even warning that a deadline or SLA might be missed.

Examples of opportunities process intelligence can help uncover:

• Hand-offs between digital workers and staff
• Optimal ways to free up work cycles and increase productivity
• Redundancies and bottlenecks
• Manual tasks and their suitability for automation
• The steps in a manual task to create a template for an RPA bot to work on
• Data showing the financial and time-saving impact of digital workers in each process
• Human and digital labor comparisons of costs and efficiencies

Before starting your process mining project, decide what you want to tackle first. You might want to try a small test project to help you create your business case. But if you can, it’s smart to focus on the processes needing the most improvement. You should also think about which processes are likely to have the biggest impact.

Finally, make sure you involve the right people. Different skills will be needed to make process mining a success. Make sure your team includes at least these roles: a process leader, an analyst and a strategy manager. You should also at least consult with process owners and key IT personnel.

Set your goals and decide on initial key performance indicators. Without these defined, you may struggle to assess process mining’s results.

When you’re ready to dive in, make sure to find the right solution for your business. You might want to search for a platform designed with ease of use. You’ll also want to look into whether full process intelligence is the better investment.

Get your processes running up to 30% faster with SS&C | Blue Prism® Process Intelligence. Improve efficiency, get the right processes in production and accelerate your automation success.

If you want to know more about how process intelligence levels up process mining and accelerates your automation journey, download our process mining guide.

• Process mining is a way to find, analyze and optimize business processes.
• It works by extracting data from system event logs to create a process model.
• The power of process mining is chiefly its ability to uncover opportunities and improve business processes.
• Process intelligence improves process mining by adding new capabilities and delivering deeper insights.