Keplercode - Blog , Process MiningKeplercode - Blog , Process Mininghttps://keplercode.com/blog/process-miningFri, 27 Mar 2026 03:53:48 +0100http://zoho.com/sites/<![CDATA[Common Use Cases for Process Mining]]>https://keplercode.com/blog/post/common-use-cases-for-process-miningFive Common Use Cases for Process Mining according to the leading analysts company Gartner: Discovery and Analysis, Auditing and Compliance, Automation, Digital Transformation, IT Processes]]>

Common Use Cases for Process Mining

The term Process Mining describes a set of methods and an analytical discipline of detecting, monitoring, and improving real business processes by extracting knowledge from the event logs available in modern information systems. The main goal of Process Mining is to analyze how the processes actually work, how they deviate from the ideal model, what problems arise, what optimization measures should be taken, and how to improve the process. 

Five Common Use Cases for Process Mining according to the leading analysts company Gartner:

  • Discovery and Analysis

  • Auditing and Compliance 

  • Automation

  • Digital Transformation

  • IT Processes

Discovery and Analysis

Process mining complements the traditional area of business process analysis, allowing business process analysts to document, analyze, optimize and redesign complex processes at the conceptual and logical level.

So, it is a promising direction in applying Process mining methods to products, services, resources, channels, and customers. It helps organizations identify how they can actively influence customer experience and sustain them through internal operational improvements. Combining all these business model components, a new area of «business-mining» or «organizational mining» appears.

Auditing and Compliance

Process mining helps validate or audit whether actual operations meet internally defined standards such as ERP and CRM. More accurate assessments of process deviations and compliance issues help manage risks and describe the findings in the audit report. It also helps to ensure the reliability of external financial reporting and compliance with external laws and regulations.

Another option is to compare and analyze the same processes in different business units, subsidiaries, or countries.

Automation

Process mining helps business analysts identify and evaluate process automation capabilities. It effectively creates a business case for automation that some customers often find challenging to make on their own.

Process mining will help in two ways: first, it opens up opportunities to automate tasks in a more holistic process context, and second, by connecting automated tasks to the process context, it is possible to predict changes in business processes and reflect them in these tasks.

Digital Transformation

Shifting the scope of process mining to the operational and organizational level provides visibility, analysis, and understanding of business operations models that represent the way of doing business, providing real-time information to end-users on how they work and what can be improved. In some cases, it has been reported that this even helps end-users think about digital opportunities.

IT processes

Identifying, analyzing, and optimizing IT operations and processes is a new use case that can benefit IT organizations and common practices such as DevOps.

Although this use case has emerged recently, this option is expected to be widely used, especially by vendors and system integrators with strong IT experience.
So, with the growth of globalization, businesses worldwide are faced with the challenge of fully understanding what’s going on in their business processes. Therefore, when technologies take the lead, it is necessary to study and apply leading methods to work as a «well-oiled machine».
]]>Tue, 12 Sep 2023 19:29:57 +0000<![CDATA[Main factors contributing to the implementation of Process Mining]]>https://keplercode.com/blog/post/Main-factors-contributing-to-the-implementation-of-Process-MiningDeep tech offers fundamental ways of solving actual problems, and often they are new and unpredictable. They drive us forward and allow us to take the next step higher.]]>

Main factors contributing to the implementation of Process Mining

Recently, Gartner has analyzed the process mining market. Process mining is a vital automation tool that helps organizations find ways to improve their business processes by analyzing corporate data. Process analytics is also underlying effective digital transformation.

Gartner sees five main factors contributing to the implementation of process mining:

  • Digital transformation

  • Artificial intelligence

  • Task automation

  • Hyperautomation

  • Operational resilience

Digital Transformation

Digital transformation is the process of integrating digital technologies into all aspects of a business intended to meet the market and changing business needs. It aims to improve the effectiveness of business operations and customer relations. Organizations need to update their systems, processes, and culture to achieve these goals.

In enterprise-wide digital transformation initiatives, it’s essential to align and adapt WELL-DEFINED BUSINESS processes with client interactions to attain the targeted business outcomes.

Artificial Intelligence

Artificial intelligence is the ability of a computer or robot to perform tasks commonly associated with intelligent beings, such as learning from experience. The systems powered by artificial intelligence use various algorithms to organize and understand vast amounts of data in the process of making  optimal decisions.

Data and analytics leaders must focus more precisely on those instances in which algorithms provide insight and have become pivotal to competitive differentiation.

Task Automation (RPA)

Robotic Process Automation (RPA) offers an approach for automating manual tasks that provides a way to get many tasks performed fast and without errors. The focus of RPA is to carry out these tasks automatically on the existing software front-end.

Process mining can complement RPA perfectly to offer a broader context and help implement this task automation. This results in long-term sustainable business value and prevents the defects of a short-term perspective focused on large, one-off cost savings.

Hyperautomation

Hyperautomation applies advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans. Additionally, it’s important to emphasize that it is not about technologies (products or services). Instead, it is a design pattern.

Process mining is a part of creating visibility and understanding before you automate. It also visualizes how different islands of automation are connected and how continuously implemented and connected automation can be improved through its monitoring capabilities.

Operational Resilience

Operational resilience is a set of methods that enable people, processes, and information systems to adapt to changing patterns. It is the ability to change operations in the face of a changing business environment.

The fundamental purpose of process mining is understanding operations at all levels and providing regular feedback to improve these processes when new challenges arise. Process mining can quickly identify pain points when a crisis happens, so your business can quickly find a solution to ensure a quick and smooth back to the right track.

Therefore, using at least 1 of the 5 factors, Process Mining will not only provide a valuable business result in improving process performance but may also push the organization to move to a new, more advanced level.

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