Blog | Apr 27, 2022

What is Process Mining, and How Does it Accelerate Automation?

What is Process Mining, and How Does it Accelerate Automation?

Processes make businesses tick, and many organizations have turned to robotic process automation (RPA) and intelligent automation (IA) to digitize processes and transform operations. As a result, they’re saving significant time and costs, increasing job satisfaction and empowering people to focus on more strategic tasks.

Organizations are now ready to go beyond automating highly manual, repetitive processes and transform a wider range and breadth of systems across their organizations.

Prioritizing the processes to automate

This next step can present challenges in selecting and prioritizing which processes to automate, based on which will drive the most value and deliver strategic objectives. Typically, when an organization has challenges finding processes to automate, they use manual process discovery methods to create what’s known as a process definition document (PDD).

The PDD is effectively an instruction manual that must be accurate and detailed enough to train digital workers to perform a business process unaided by humans. It’s developed with the help of subject matter or domain experts who understand how a process works and could be improved through automation.

More recently, organizations have begun using process mining tools to automate this information-gathering activity. The dilemma is that both approaches — manual process and process mining —have challenges.

Manual process discovery relies on people explaining the process step by step, which can lead to missing information or workarounds. This results in automation that may omit key steps and organizations that don’t truly have a clear picture of process performance.

Manual process discovery takes a significant amount of time and resources, putting pressure on subject matter experts and potentially introducing bias and inaccurate assumptions about processes that are false.

Meanwhile, process-mining-only tools can be inadequate in today’s complex business environment, not always providing the insights businesses need to build into their processes.

In this article, we explore:

  • What is process mining ?
  • How does process intelligence add more capabilities to process mining?
  • How does process intelligence enhance intelligent automation?

What is process mining?

Process mining uses data from information systems to create a model that accurately reflects how a process executes. IDC defines it as: “Data-driven statistical analysis of how a business process performs to identify areas of variance and inefficiency.” The global market intelligence firm goes on to explain: “The purpose of process mining is to gain a fact-based understanding of process variance and inefficiency to systematically improve the process to maximize performance while aligning with the overall goals of a business.”

The data required for process mining is collected from the log data of applications and databases used to execute the process. The data is fed into an analytical engine that mines the data to produce a map of how the process operates in production, then compares it with a model of how the process is designed to operate.

Process mining is effective even when a single process relies on interactions with multiple systems and databases. It can follow logs and audit trails to build process models, which show the details of end-to-end processes based on real-life data. Organizations can then analyze models to discover whether the processes are operating as they should and identify root causes of deviations and bottlenecks that prevent them from working properly.

The advantages of process mining over manual discovery processes are many and varied, including the ability to leverage automation to build accurate representations of process performance faster, easier and more accurately than manual approaches.

However, process mining operating alone has its shortcomings. Some tools may not be able to connect with certain types of data sources or cannot mine highly complicated and variable processes.

And while process mining is great at looking at real-world logs and audit trails, these are necessarily based on work undertaken in the past, rather than in real time. This means processes can be analyzed retrospectively but do not enable organizations to monitor processes on an ongoing and granular basis.

How does process intelligence add more capabilities to process mining?

Blue Prism Process Intelligence powered by ABBYY Timeline combines process mining, task mining and business intelligence-like metrics to provide much deeper insights into business processes. Its numerical analysis approach works well on all types of processes, no matter how many data sources are involved or how complex a process may be. It’s a powerful system that can cope with large volumes of process logs, which can be aggregated and searched in great detail.

Blue Prism Process Intelligence is not confined to analyzing processes that have already taken place but can instead monitor processes in real time, so that process owners can be alerted to errors and deviations, helping to improve how the business operates across the board.

With process mining tools, users can look at outputs to find issues that could impact an organization’s regulatory compliance. Process Intelligence goes one step further by allowing organizations to define actual process rules that align with their compliance requirements.

It then trains digital workers to monitor for any deviation from those rules and to automatically inform process owners. Process rules relating to compliance can be set to fix problems as soon as alerts are made, avoiding the challenges associated with infringements.

How does process intelligence enhance intelligent automation?

Because Process Intelligence provides a single end-to-end view of process execution and potential side effects, it enables organizations to identify the most valuable automation opportunities. This includes the ability to calculate process variations, along with time and cost implications for automations. It is built around quantifiable, data-driven return on investment (ROI) calculations based on the number of process transactions and steps, process duration and cost per transaction. Organizations can create these insights while removing resource-hungry manual processes, which means a faster time-to-value and ROI.

One of the most valuable outputs from intelligent automation projects is that they provide an opportunity to address sub-standard processes. With Process Intelligence, organizations can review processes as they’re executed, allowing them to identify, analyze and correct issues before they’re integrated with RPA.

Continuing investment in intelligent automation depends on the success of RPA projects, which should be measured by the value they bring to a business. Process Intelligence helps to ensure that automations are operating as expected post-deployment, using its ability to monitor impacts upstream and downstream.

This extends further into automated process monitoring in mixed-mode scenarios where digital workers operate collaboratively with human assistance. By showing the value of mixed-mode automations, organizations can safeguard future ROI commitments. The system can be trained to provide specific data points to senior decision makers, who can view actual quantifiable data that are constantly monitored and updated.

One of the ambitions of leaders in intelligent automation is to scale their use of digital workers across the organization. This requires careful orchestration to ensure automation remains synchronized across every process and business system it touches. With Process Intelligence, organizations can monitor such enterprise-wide processes in near real time, ensuring that any problems can be fixed as quickly as possible.

Process Intelligence and Intelligent Automation

Analysts and center of excellence teams have historically been hindered by manual process discovery and definition, which is time-consuming, resource-hungry and often inaccurate. For many, process mining was the first step in bringing technology on board to help understand how processes worked.

Today, Process Intelligence provides a new approach that accelerates transformation and helps leaders truly understand their businesses. They no longer run the risk of wasting their investment in automation that fails to add value or that simply automates broken processes with little benefit.

The data-driven approach achieved by Process Intelligence makes it easier to identify areas that would truly benefit from automation, providing access to levels of detail that were simply not possible with process mining tools alone.

Process Intelligence offers an ongoing opportunity to monitor the efficacy of processes, identify problems, maintain regulatory compliance and alert the right people of problems at the earliest opportunity. Taken together, these benefits make it easier for automation teams to make a watertight business case for future investments.

Get started today with Process Intelligence. Current customers are eligible for a Starter Pack with Support or a 30-day evaluation license.

Want to Know More About Process Intelligence?

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