What Is Process Mining? Explore the Best Practices and Tools

As a business evolves, technology takes command of most processes. But with great processes come great inconsistencies. 

Given the dynamic nature of industries and the advancement of globalization, a business process that served you well yesterday might not be efficient today. As a result, every organization needs new ways of scrutinizing its operations to keep up with industry advances and gain a competitive edge. 

Creating flexible processes that can keep up with change is only possible by gaining insights into how a process works and identifying key challenges. The traditional process modeling methods are no longer effective as they bring high risks of manual errors.

So how do you ensure optimum outcomes when there are too many processes to track? That’s where process mining software comes into the picture. 

Process mining software performs by extracting event log data from a company's database or business management tools like customer relationship management software (CRM), enterprise resource planning software (ERP), and electronic health records software (EHR). These event logs help a business look closely at its "as-is" processes.

With a suitable process mining tool, enterprises create ideal work models or graphs by examining the end-to-end trail for discrepancies and bottlenecks. These specialized algorithms identify the root causes of deviations from the norm, provide resources to fix them, and build a more robust and efficient process.

What is a process?

It might go unnoticed for the most part, but processes surround us in our daily mundane lives. Be it cooking a meal, cleaning your room, creating a monthly budget, or any other #adulting chores. But how do we precisely define a process?

A process is a series of actions taken from start to finish to complete an activity. In process mining, this set of actions can be individual steps or tasks that define a business operation's start and end points. Processes can be one-time, recurring, or periodic, depending on the nature of the workflow.

How does process mining work?

Let's say a customer calls your helpline number. As a business owner operating on a big scale, you might have several questions about that particular interaction. For instance, when was the call received? Who attended to the customer? Was the problem understood correctly? Was a quick resolution given? How long did the entire process take?

Imagine having to keep track of thousands of such phone calls every day. Sounds impossible? Maybe not.

Standard business processes leave behind a trail of data which we refer to as event logs. They help process miners understand the operational model and optimize it for better results.

With the help of process mining algorithms, you can take this data from company records or in real time and convert it into solution-focused insights. You can explore how long it takes to complete a process, which employee is handling which step of the process, whether there are any misdirections from the standard model, or what is slowing down the operation. 

Once you have a clear picture of what works and what doesn't, you can take these data-backed solutions and apply them in the necessary spots to remodel your business functions from start to finish.

How does process mining complement RPA?

Process mining uses a technology called Robotic Process Automation (RPA) that helps workers focus on high-value tasks by eliminating tedious steps from a process. RPA software employs bots to automate repetitive duties that previously required manual effort. As a result, process automation enhances the overall efficiency of a business operation.  

Analysts can identify the current work model and locate multiple variations, discrepancies, and other inconsistencies before RPA can work on automating the process steps. Using bots to determine which steps are redundant and require manual efforts is much simpler when you have a process model outlining each action and interaction in a business process model.

Moreover, process mining makes it easy to compare the new automated process with the old model by generating a new process map at any time.

Hence, these techniques complement and support each other to deliver the best possible outcomes. When worked in tandem, process mining and RPA can empower a business to achieve higher results that are easily measurable.

History of process mining

This specialized algorithm for identifying data trends, patterns, and inefficiencies from event logs started to take form in the late 1990s. A Dutch computer scientist and professor, Wil van der Aalst, is the face behind the academic research that went into discovering the details of how a process unfolds.

Also known as the godfather of process mining, van der Aalst and his team of researchers encountered a resolution to utilize data in assortment with analytics and visualization tools.

However, the study remained limited to the academic world for quite some time. Eventually, businesses realized that merging process mapping with data analysis could deliver the most efficient results. Around this time, process mining’s economic prospects became known across industries.

Of course, modern process mining software solutions are much more advanced for competing in today's business world. They bring an amalgamation of data science, data mining, business intelligence, and analytics to deep dive into the workings of an organizational model.

As a result, the newer wave of process mining not only visualizes and optimizes processes but also measures KPIs, benchmark and compare operations, collaborate with your existing IT infrastructure, and solve problems with data-centric solutions.

Why is process mining important?

Think of process mining platforms as an X-ray machine that provides visibility into how different tasks work together by collecting necessary data from your information system. This data brings forward actionable insights that identify areas of process improvement and delivers concrete solutions. 

Process mining solutions enable professionals to visualize the practical layout of a process and identify real-time problems instead of working with solutions based on assumptions. Process mining software brings the best of both worlds with the perfect combination of business process management (BPM) techniques and data mining algorithms.

While BPM employs manual efforts when collecting data, process mining operates with data-driven understandings to deliver a quantitative stance. 

Moreover, process mining is not a one-time solution. It equips businesses with what they need to continuously monitor and optimize their operational models by following a fact-based approach, assisting them in reaching process excellence while providing complete transparency.

Process mining techniques

With data mining and machine learning integration, process mining techniques benefit companies of any size and workflow. Process mining solutions can focus on various elements like the flow of a process, the organizational structure, or time management.

Automated business process discovery 

During discovery, process mining software traces the entire business workflow from end to end and provides an ideal blueprint to its users. As the name suggests, automated business process discovery (ABPD) automates this process discovery stage by incorporating artificial intelligence (AI), computer vision, and computational logic.

These automated solutions use a discovery algorithm to extract data based on user interactions from IT systems, event logs, and databases. Then, it analyzes the accumulated data to identify patterns and process models. Finally, ABPD draws out the organization's collective operational processes with real-time monitoring and highlights any significant process deviations. 

Conformance checking business processes

Once the operational model is evident from the discovery algorithm, it’s possible to find that the process execution deviates from the ideal process model. That’s why you need conformance checking in organizational mining to help determine a process' compliance rate. 

This method systematically evaluates the current process flow and compares event logs with the reference or target models. Conformance check assists in discovering and correcting any inefficiencies that might occur in the execution of the ongoing processes by measuring their performance against the ideal performance requirements. 

Model analysis and enhancement

Once you have the necessary information on the current process’ deficiencies from process discovery and conformance checks like bottlenecks, process loops, and unwanted deviations, you can narrow down the steps that have the potential to be optimized to the highest standard. 

Therefore, the objective behind the model analysis and enhancement is to determine how to optimize the target process model to its optimum potential. The enhanced model minimizes the risk of existing bottlenecks, making the overall process more efficient with automated workflow.

Process mining benefits

With process mining technology, businesses can improve their process intelligence to create ideal workflows and operations. As a result, more and more companies are leaning toward adopting this software to reach their maximum efficiency potential because process mining: 

• Identifies process bottlenecks. Process mining tools empower businesses to identify process bottlenecks by discovering the causes of existing discrepancies. This holistic view of the processes ultimately results in improved efficiency and the ability to fix accidents before they happen.
• Enhances process intelligence. With the help of process mining software, organization stakeholders better understand processes, evaluate suggested fixes, and make smarter unified decisions based on data-backed insights. 
• Improves business process management. Process mining is an integral part of BPM. Process mining work means owners can view processes in visual flows and automate tasks for higher efficiency. It also creates opportunities to align operations with business goals and strategies to generate the best outcomes.
• Increases transparency. Process mining serves as a guide to internal processes, allowing full disclosure about how functions carry out in a business workflow. This increased transparency makes it possible for decision-makers to comprehend the reality of their operations and find opportunities to improve and fix them.
• Reduces expenses. Organizations can reduce operating costs drastically by identifying opportunities to automate tasks and fixing problem areas beforehand. Process mining lets businesses analyze event log data and minimizes wasted time and resources.
• Offers superior customer service. Users can track process performance in real time by leveraging data procurement to identify bottlenecks and reach solutions much faster. As a result, businesses can improve their decision-making skills and deliver excellent support to their clients.

Process mining challenges

While several enterprises have recognized the necessity of process mining, implementing an effective mining strategy is complex. Business owners must evaluate their current IT landscape, set the right goals, and fulfill infrastructural requirements at every step. Prepare yourself by checking out some of the most common process mining challenges.

• Lack of digitization: Many organizations are still heavily dependent on paper-based documentation, which creates hurdles for business process mining software. Digital transformation is necessary for implementing a process mining strategy because, without digitized event logs, process mining software can’t extract the required data for enhancing process models. Therefore, it’s vital to incorporate business management software like ERP and CRM to record activities.
• Inadequate data integration: Some traditional process mining tools might restrict the types of data sources they can connect to, limiting their value to a company's operations. For instance, process mining is known for optimizing processes within one organization. Still, gathering data from other organizations and creating the best target model in some cases is helpful. It gives you a complete understanding of the end-to-end process workflow, so you gain a competitive edge.
• Poor quality data for mining: Process mining results rely directly on the quality of data extracted from information systems or databases. Unaware of this fact, many organizations encounter data quality issues, event ambiguity, trouble with timestamps, and missing data. As a result, businesses do not have data of an appropriate value for process mining and optimizing operations.
• Faulty Integration: When businesses are looking to deploy process mining software on top of processes to automate their functions, it’s essential to identify a compatible software with which process mining tools can seamlessly integrate. If the procedure you want to automate is incompatible with the chosen software, these faulty integrations won’t bring any results. 
• Insufficient staffing: Even though process mining software is all about automation, you need people to run those tools and gain context from the discovered bottlenecks. Besides, advanced process mining software requires hiring specialists like business analysts, data scientists, and engineers, which might strain a company's budget.

Process mining vs. task mining 

Process mining and task mining are complementary elements that share the same purpose: to help organizations get the most out of their operations on multiple levels and achieve better results. However, there is a slight difference in how each of these techniques works.

While process mining revolves around discovering, analyzing, and optimizing end-to-end processes, task mining focuses on smaller tasks that define said processes. These include sub-processes that employees perform manually, like uploading files or copying data.

Hence, task mining describes how companies run their tasks, and process mining identifies user interactions to determine the accuracy of those tasks.

Process mining vs. process modeling vs. process mapping

Business processes can be a complex interconnected web of activities that drive a particular goal or company objective. While process mining targets these activities to optimize them for faster and improved results, process modeling and process mapping focus on the visual representation of business processes.

Process modeling uses quantitative data mining techniques and algorithms to represent a business process. It acts as a sub-component of process mining, precisely the stage where machine learning algorithms use event logs to create a workflow model. A process model includes workflow data like user interactions, success rates, actions taken, and a timeline of each cycle.

Similar to process modeling, a process map is also a visual representation of a workflow. But these techniques are not interchangeable as they highlight different aspects of a business process. While a process model is quantitative and data-driven, a process map is more qualitative and subjective. Process mapping is more people-focused and outlines how employees get involved with the process at various stages.

Process mining use cases

The potential of process mining is not limited to any specific industry or business model. Any enterprise that follows processes can use this technology to reach maximum efficiency. And as long as they meet the fundamental requirement of event logs, there is no limit to how much they can explore processes in depth. 

However, despite this algorithm's universal nature, a few industries are already leveraging the benefits of process mining in their day-to-day work.

• Supply chain management: Process mining software analyzes logistical functions to pinpoint any weak links in a supply chain. Adopting an optimized model makes the supply chain more resilient to unexpected disorders.
• Finance: Automation and process enhancement significantly benefits the finance sector. Process mining can optimize audit controls, find root causes for incorrect invoices, mitigate risk, and enhance loan processes. 
• Sales: Since complex sales processes depend on external factors, process mining allows business leaders to envision discrepancies and resolve them to meet fixed targets. Companies can increase conversion rates, enhance strategies, and improve sales performance across the board.
• IT & software: IT professionals benefit from sorting out disorganized engineering processes by gaining clarity and managing the complexity of ERP migrations and implementation. They can also monitor systems in real-time to ensure everything is running smoothly.
• Customer experience: With process mining technology, businesses can identify which customer processes are taking longer to resolve and pinpoint their root causes while providing solutions to fix the delay. 
• E-commerce: Organization leaders in the e-commerce sector can boost their conversion rates by getting exclusive insights into buyer behavior, market trends, and growing customer base.
• Healthcare: The healthcare industry has a surplus of data, from health records to appointment booking procedures. Professionals can reconstruct this data digitally with process mining software for seamless integration. In addition, automation opportunities can eliminate redundant manual tasks and decrease the risk of error.
• Education: Educational process mining (EPM) allows administrators to analyze and visualize students’ learning behavior by applying specialized algorithms. The student activity logs provide insights into tracking and monitoring their academic performance. 

Process mining best practices

Over the past decade, operational excellence has become a buzzword for industries across all sectors. Process mining plays a substantial role in achieving this level of optimized efficiency. 

• Identify your business systems. Before taking process mining initiatives for your business functions, it's fundamental to identify your business sector and current systems. Process mining software will bring efficiency to your business work model by integrating with existing systems applications and products (SAP), CRM, and supply chain management. 
• Pick a tool that suits your business functions. Business owners must oversee their enterprise functions, what it takes to process them, and if they are well-equipped to meet those requirements. Once you have a clear vision of which functions to optimize, choose a process mining tool that best fits you. 
• Finalize the end goal. Once you understand your business systems and KPIs, take a moment to identify the end goal that you wish to achieve with process mining. Each process mining tool helps with conformance checks, process discovery, model analysis, and enhancement. However, there might be a better-suited tool for you that meets distinct specifications appealing to your bottom line. 
• Apply solutions to all use cases. Business leaders often choose specific places to optimize using process mining techniques, like processes when employees might lack the required skill set or departments have alarming deficiencies. However, when an organization gains transparency into its business processes, it’s profitable to apply those insights across the board. 

Best process mining software 

The goal of acquiring process mining software is to incorporate it with the existing software in a company's IT infrastructure. A process mining software must be able to do the following to be included on G2’s list:

• Read, analyze, and monitor event logs from information systems and databases to understand the current business process.
• Conduct conformance checks to recognize deviations and bottlenecks in the ongoing model.
• Deliver data-driven insights into which methods are not meeting the set standards, down to individual employees deviating from the business model. 

*Below are the top five leading process mining software solutions from G2’s Summer 2022 Grid® Report. Some reviews may be edited for clarity.*

1. IBM Process Mining

IBM Process Mining delivers an objective outlook to examine operational processes, pinpoint weak areas, and develop strategies to optimize automation projects.

What users like:

“IBM Process Mining is a robust tool powered by AI. I like most of its features, like the advanced AI/ML technology to discover processes and automatically generate process models, which allows us to have a higher level of detail of the processes and get an RPA tool that IBM offers.”

- IBM Process Mining Review, Heather C.

What users dislike:

"The lack of mobile applications is a pain for someone like me, and the cost is something I wish they would reduce one day. Also, the documentation wasn't very effective or helpful; even those with good data skills came to us for training because it wasn't enough for them."

- IBM Process Mining Review, Abeer M.

2. UiPath RPA 

With the combined power of AI and machine learning, UiPath Robotic Process Automation (RPA) is pioneering the world of robotic process automation. The software provides digital skills to millions of people and automates repetitive, mind-numbing tasks for businesses and government organizations worldwide.

What users like:

"UiPath is an exciting and great tool to do automation more easily. I like how it flows in our company because of the current task automation and offers great flexibility. And the most important thing about UiPath is the support from the UiPath community."

- UiPath RPA Review, Avinash S.

What users dislike:

“Sometimes, compatibility with third-party software and workflows malfunction, and we have to reconfigure the whole coding.” 

- UiPath RPA Review, Muhammad Asim I.

3. Celonis Process Mining

Powered by its market-leading process mining core, Celonis identifies and troubleshoots bottlenecks that businesses can't locate, qualifying them to perform at the most optimal level. The software enables companies to eliminate operational inefficiencies and deliver a superior customer experience while decreasing carbon emissions.

What users like:

"Celonis is very easy to use, and you can get trained by using detailed courses from Celonis Academy free of cost, which I think is a very great thing which Celonis team did."

- Celonis Review, Poonam C.

What users dislike:

“The UI needs improvement, and the visual loading in dashboards is taking a long time which is a bit disappointing.”

- Celonis Review, Antonio G.

4. mysmartautomation

mysmartautomation identifies, optimizes, and drives efficiency across end-to-end business processes with real-time visualization and automated recurring tasks. It is ideal for saving time and making strategic decisions with the highest efficiency by predicting business outcomes through data-driven insights.

What users like:

"Information is a key factor to make decisions. mysmartautomation gives us information in real time to do it and has been more than helpful with our management."

- mysmartautomation Review, Ibitssam A.

What users dislike:

"They can improve the support. Sometimes I work on Saturdays, and I need someone that can help."

- mysmartautomation Review, Margot B.

5. Apromore

Backed by world-leading research, Apromore authorizes users to identify the full potential of their business processes while aiming to achieve operational excellence. This leading-edge software supports a full spectrum of process mining functionality. It provides data that helps improve process efficiency and serves customers better while reducing business risk.

What users like:

“Apromore is a highly intuitive platform that is easy to learn to use. The platform offers many functionalities, making it possible to do extensive process mining analysis. In addition, the tool has dashboard functionalities that help visualize issues and process data.”

- Apromore Review, Maria H.

What users dislike:

“I wish it were easier to apply filters on the performance dashboard when you want to compare different event logs. Workarounds are available, such as filtering each log, saving, and then comparing. However, it takes you away from the performance dashboard screen.”

- Apromore Review, Brandon A.

The road ahead

As we head into the future, data-based analytics methods like process mining will continue to automate business operations, paving the way for digital transformation across many industries like healthcare, e-commerce, and more.

This mass adoption of digitization strategies via process mining uses will fundamentally remake the way enterprises work.