Main factors contributing to the implementation of Process Mining

Main factors contributing to the implementation of Process Mining

12.09.23 07:13 PM By Keplercode Team

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 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.

Keplercode Team