Process mining is an invaluable technique that can help managers and leaders better understand, monitor, and improve business processes.
Yet in today’s business world, process improvement is often tied to other business initiatives, such as automation and business change initiatives.
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In this post, will learn the details of process mining, how it works, and how it fuels automation-driven business change.
What Is Process Mining and Why Does It Matter?
Process mining is designed to analyze existing business processes in order to improve them.
Just as data mining collects and analyzes data, process mining collects and analyzes data related to business processes.
Here are a few steps that are commonly included in process mining models:
- Using data science techniques to prepare and analyze data related to business processes
- Using advanced analytics, such as predictive analytics, to apply those techniques in the real world
- Understanding that data through dashboards and platforms that track metrics and KPI’s
- Monitoring tasks through UI logs
- Developing a business operating model
- Analyzing and modeling employee interactions
- Analyzing customer interactions and developing journey maps
There are several reasons why businesses pay such close attention to business processes and process improvement.
A few of these include:
- The need to improve business efficiency and process efficiency. One of the main reasons to invest in process mining is to find more efficient ways of performing existing processes. This can reduce operational costs, shrink process timelines, and ultimately improve process efficiency.
- Enhancing the customer experience, the employee experience, the workplace, products, and services. Process mining can be used to analyze the process is that contribute to the development of employee and customers experiences, and improve upon those. The end aim of this use case would be to enhance, for example, customer lifetime value, products and services, and bottom-line profits.
- Staying relevant during fast-paced and disruptive times. Organizational change has become very common in recent times. Process mining is an essential step in the successful transformation of business processes, which goes hand-in-hand with many organizational change initiatives. Process mining can also be used as part of ongoing business improvement efforts, such as those implemented as part of process improvement methodologies.
- Improving the organization’s digital maturity. One use case of process mining, as we’ll see below, is to increase the use of automation tools. The effective use of these types of tools, in turn, complements the overall digital maturity of the organization.
- Increasing organizational agility and resilience. An organization that can adopt new processes and adapt existing ones through process mining and business process improvement tools will be more resilient against disruptions and external changes.
- Lowering operational costs. Another common sense benefit of process mining and process improvement is decreased costs. Automation, for example, can significantly improve in organizations productivity, while simultaneously decreasing overhead.
- Integrating automation Into the organization. Finally, business process automation is one of the key use cases for process mining. In today’s digital-first era, the use of automation is not only advantageous, it will soon become foundational to the way that organizations operate. Process mining, as a result, will also become an essential business function.
Process mining is a technique designed for organizations that want to not only improve business processes but continually improve upon the areas mentioned above and increase their business process maturity levels.
The Relationship Between Automation and Process Mining
Process mining plays a crucial role in the adoption of automation-driven processes, such as RPA, BPA, cognitive automation, and hyper automation.
While some organizations may view automation as a one-time initiative, others recognize that automation is becoming central to the way organizations operate.
As a consequence, process mining is becoming essential to the way many organizations operate – after all, to implement automation-driven processes, it is essential to mine data from existing processes.
Here are a few automation trends that are converging with process mining to help drive these types of transformations:
- RPA. Robotic process automation, or RPA, is one of the key trends that can be used with process mining to improve business efficiency. Task automation platforms operate at the level of the day-to-day workflow, and can significantly enhance employee productivity, output, performance, and even job satisfaction.
- BPA. Enterprises today or investing heavily in customized automation processes that affect high-level business processes. These types of automation approaches include AI, cognitive automation, and many other high-level, data-driven approaches that can transform the way a business operates.
- Hyper automation. Hyperautomation is a term that refers to the transformative impact of AI just mentioned. While RPA refers to low level task automation, hyperautomation refers to automation that can be applied across the organization, down to its “DNA.”
These three examples offer a top-down overview of one path that organizations are taking towards the automated enterprise:
- First, businesses automate tasks through technologies such as RPA platforms
- Second, they automate processes and workflows
- Third, they operate business operations through advanced automation tools such as cognitive automation and intelligent automation
The above journey certainly isn’t the only one businesses can take when adopting automation, but it is one of them – and its success will depend a great deal on how effectively the organization can learn from its business processes.