Process Mining – Definition, Importance, Benefits & Applications

05 Jun Process Mining – Definition, Importance, Benefits & Applications

Does data have the power to elevate the efficiency of your business processes? The answer lies in process mining. Effectively, process mining is a data-driven technique used to model and optimize any business process in an organization.  

Despite its significant potential, many business leaders are still unsure of what process mining truly entails and how it can transform their businesses. So, what is process mining? Let’s delve deeper into this concept, its benefits, and its applications in the business world.

What is Process Mining?

Let’s begin with the process mining definition. Gartner defines process mining as the “technique to discover, monitor, and improve real business processes by extracting readily available knowledge from event logs of information systems.”

Essentially, it is a technique used to track and analyze business processes – and extract relevant insights from their data. For instance, process mining can involve mining from the data logs of ERP and CRM applications to deliver an accurate representation of the business process. As compared to “traditional” methods, process mining works with existing business data from enterprise systems.

Now that we understand the process mining meaning, let us look at the history and evolution of process mining.

History and Evolution of Process Mining

As a technology, process mining possesses the potential to revitalize effective process management and improvement in any enterprise. Among the major challenges, organizations need a proper description of their “current” processes, or how they are being performed currently. Through business process reengineering, they can think of the “to be” process improvements.

Without understanding the current business process, organizations cannot determine if it’s worthwhile investing in process improvements. Most organizations end up spending too much time analyzing the “as is” process. Additionally, with process management, there is a lack of connection between business processes and information systems (for example, SAP ERP systems).

Process mining can efficiently address both of these challenges in the enterprise. For instance, process mining can capture information from enterprise systems and provide data-driven insights about the performance of critical business processes. 

Where should organizations enable process mining? For maximum value, process mining is best applied to digitalized processes supported by IT systems. Effectively, companies that use enterprise systems to support business processes must begin adopting process mining.

Why is process mining important in modern enterprises? Let’s explore that next.

Importance of Process Mining in the Digital World

Revenue augmentation for organizations is not solely dependent on boosting sales. Through methodologies like lean manufacturing, manufacturers can also cut operational costs, leading to enhanced revenue.

This is where the importance of process mining comes to the forefront. Leveraging data to uncover process inefficiencies and bottlenecks, the technology provides a roadmap for businesses to reduce operational expenditures and enhance overall processes. In doing so, it aids in fostering innovation and refining business decision-making capabilities, thereby underscoring its integral role in the digital era.

 

What are some of the industry applications or use cases of process mining? Let’s discuss them next.

Use of Process Mining

How is process mining being utilized across industries? Here are some industry-wise use cases or applications:

1.Banks and financial Services

Financial companies are leveraging process mining to automate manual processes such as purchase-to-pay and accounts receivables. Using process mining, finance companies can reduce the lead time caused by human errors and manual interventions. Additionally, banks employ process mining to improve their customer experience and risk management.

2.Automotive

In the automotive industry, process mining is used to improve the customer’s after-sales service. For instance, vehicle owners can directly report their buying experience or feedback to the automotive company. Besides, car manufacturers can use process mining to streamline and automate backend operations such as customer invoicing and bills of materials. Apart from improving after-sales service, process mining provides multiple benefits like improving operational efficiency, detecting production inefficiencies, and modifying logistics.

3.Healthcare

In the healthcare domain, process mining is enabling improvements in clinical pathways and administrative processes. For instance, it can be used to standardize the best practices in healthcare. With effective process mining, healthcare companies can identify problems leading to the wrong treatment or delays in patient care. Among the successful applications, process mining has improved patient care and discharge – along with accurate cancer diagnosis.

4.Insurance

Insurance companies regularly face the challenge of accurately estimating insurance claims. With process mining, insurance providers can improve the underwriting process through proper risk management. They can also reduce their quote-to-bind ratio, which is the ratio of converting quotes into binding policies. Other use cases include regulatory compliance, fraud detection, and back-office operations.

Process mining can be useful in many use cases across organizations and industries. Here are a few of them:

• Sales and marketing

For most companies, sales processes that encompass generating leads right up to customer order fulfillment can be a long and costly affair. Process mining can identify any sales-related bottlenecks and provide insights to reduce the overall sales cycle time. Besides that, process mining provides valuable insights into which marketing strategies are generating conversions (or not).

• Enterprise resource planning (ERP)

When integrated into ERP solutions, process mining can improve operational visibility into ERP processes and manufacturing operations. The technology is useful for pinpointing gaps or inefficiencies in ERP systems. Further, companies can delve into process delays in resolving customer tickets. 

• Finances

Finance-related operations like procurement, vendor payments, and accounts management are filled with manual or repetitive processes. Process mining can be effectively used to streamline and automate financial processes, thus eliminating “human” errors and reducing costs. For accounts receivables and payables, process mining can help companies find the root cause of delayed customer payments – or bottlenecks in the invoicing process. Further, process mining is effective for comparing any auditing-related process changes and improving response time.

• Manufacturing and industrial production

With growing challenges and competition, manufacturing companies are constantly looking to reduce warehousing costs and improve production efficiency. On its part, process mining can detect inefficiencies in warehouse management and production processes. Further, process mining can be used to identify logistical delays and optimize the geographical location of warehouses.

Next, let’s discuss some of the popular process mining software that is being used across industries.

Process Mining – Software & Tools

Process mining software & tools are designed to discover, monitor, and improve business processes by extracting information from event logs. According to Gartner, the global market for process mining software is expected to grow to $2.3 billion by 2025.

Here are some of the essential features of any process mining software:

1.Easy installation and deployment

Process mining software tools are easy to install, deploy, and maintain for optimum efficiency. These tools are also available as SaaS products fit for deployment in private and public cloud environments.

2.Scalability

An efficient process mining software is also designed to scale depending on the business requirements. For the best results, organizations must have a scalable process mining tool that adopts a structured approach to evaluate a business growth opportunity.

3.Pre-programmed features

Process mining software with pre-programmed features are effective at mapping business processes and improving performance management. Moreover, they empower businesses with actionable insights, enhancing strategic decision-making and driving innovation.

4.Data visualization

Effective process mining tools also provide data visualization for professionals to easily extract business insights from the available data patterns. Data visualization presents a graphical representation of how business processes are currently operated in any organization.

Some of the additional features of SaaS-based process mining tools include:

• AI and machine learning capabilities to extract and analyze data from disparate data sources.
• Intelligent analytics to extract insights and unlock potential business opportunities.

Next, let’s discuss process mining with a real-world example.

Process Mining in Practice

Process mining is a practical methodology used to analyze business processes, with the aim of improving their efficiency and effectiveness. Leveraging event data recorded by information systems, it provides visual insights into the actual functioning of business operations. This allows organizations to identify bottlenecks, inefficiencies, or deviations from the intended process. In practice, process mining proves instrumental in optimizing various processes like procure-to-pay, order-to-cash, and service desk operations, thus leading to improved productivity and cost savings.

Benefits of Process Mining

Here are the top 10 benefits of process mining for any process-oriented enterprise:

1.Enables data-driven decision making

Process mining can efficiently provide data insights, which can improve business decision-making. For instance, a process mining tool with data visualization features enables business leaders to easily visualize and analyze the presented data, thus improving their decision-making skills.

2.Standardized business processes

Through the detection of non-standard business procedures and deviations, process mining can help standardize business processes across the organization. For example, collected system logs can depict the difference between conceptualized and actual processes.

3.Improves employee performance

Process mining can automate data collection from business processes, thus helping in monitoring employee performance. Further, continuous monitoring of employee KPIs like time required for resolutions and SLA can lead to enhanced employee performance.

4.Enables process automation

Process mining can define the automation of human-centric (or manual) processes. For instance, chatbots can help in automating customer service and marketing.

5.Eliminating unnecessary practices

Process mining can identify redundant or unnecessary steps (or practices) in business processes, which can cause delays and inefficiencies. This can also save the company unnecessary costs of executing these steps.

6.Identifying process bottlenecks

Process mining can effectively detect any bottlenecks that are slowing down the business process. After a complete analysis, these bottlenecks can be eliminated by assigning more resources or by automating the process step.

7.Enabling faster responses

With constant process monitoring, process mining can help in responding faster to any business-related problem. For instance, companies can identify the cause of any customer issue and move to resolve the issue faster.

8.Optimizing business processes

Process mining tools can help companies optimize their various processes for improved efficiency and productivity. For example, companies can improve customer experience by reducing the lead time in customer-facing functions.

9.Reducing costs

By eliminating bottlenecks and process-related inefficiencies, process mining can reduce operational costs through automation. For instance, the use of automated bots can improve the quality of customer interactions by reducing the average time taken for solving their problems.

10.Increasing transparency

Process mining can provide complete visibility over business operations and processes, thus increasing transparency. For example, customer support can be improved with full transparency over the service desk function.

How does process mining differ from data mining process? Let’s discuss that in the following section.

Process Mining vs Data Mining – How Are They Different but Critical to Business Automation?

Be it process or data mining, organizations need both to improve their business decision-making processes. Data mining is all about analyzing large volumes of data (or big data) to detect any hidden patterns and trends. It essentially searches for “if-then” data patterns. For example, if the inventory stock goes below this threshold value, then the organization needs to restock the items.

Similarly, sales organizations can leverage data mining to find answers to questions like:

• Which are our most loyal customers?
• Where should we place products on the store shelves?
• Which are our most unsatisfied customers?

While data mining explores relationships in large datasets, process mining connects data mining with business process management. Essentially, process mining analyzes data in the organization’s enterprise systems (for example, ERP) to understand how efficiently the process is working – and how to improve the same.

Here are the main differences between process and data mining:

Process Mining	Data Mining
Provides an end-to-end view of the business process.	Analyzes big data for any patterns and trends.
Enables organizations to find answers or solutions to predefined business questions.	Enables organizations to find hidden data patterns – but does not address specific questions.
Includes exceptions as an early indicator of process inefficiencies and areas of improvement.	Does not include data that falls outside the defined patterns.
Concerns with the Why aspect.	Concerns with the What aspect.

Despite their differences, process mining and data mining are essential for effective business intelligence and automation.

Conclusion

Using NuMantra Technologies, your go-to hyperautomation platform, businesses can leverage process mining to improve their business processes. With our data and cloud expertise, modern businesses can maximize the value of their untapped process-related data and identify areas for process improvement.

By partnering with NuMantra, companies can utilize process mining tools to:

• Unlock the power of hyperautomation and improve response times.
• React faster to social media events and analyze popular sentiments about their brand.
• Improve overall process performance and reduce costs.
• Optimize their existing resources for AI and machine learning models.
• Analyze system logs to improve process insights.

The NuMantra process mining application can identify business trends and data patterns using pre-built algorithms. Our cloud-based hyperautomation platform offers a cost-effective solution that is suited for any business need. Using process mining and intelligence, NuMantra offers a complete one-stop solution with its low-code development tools.

Are you looking to maximize the benefits of process mining for your business processes? Request a product demo.