Mastering Efficiency Through the Integration of Process Mining Techniques and Robotic Process Automation

Process mining and RPA: Achieving Process Excellence

Tamas Mahr

July 23, 2024

Organizations across industries, from manufacturing to healthcare, are looking to process mining and robotic process automation (RPA) to improve their operational efficiency. Process mining enables you to identify bottlenecks or inefficiencies in your current processes and optimize those workflows. In comparison, RPA automates repetitive tasks, freeing up employees to focus on strategic work. When used together, process mining will turbocharge your process optimization strategy, guiding you to implement RPA technology where it has the greatest potential for ROI.

In this article, we’ll explore both process mining and RPA, including how they work, their uses and the benefits of utilizing them together.

What is process mining?

Process mining is a data-driven technique used to understand, track and improve processes, by analyzing data from information systems.

Before the advent of process mining technology, businesses would manually review their data and interview stakeholders to gauge how their processes were performing. Now, advanced process mining platforms use automation to collect event logs from various information systems, showing how processes are performing. This data is used to generate process models that provide a detailed visualization of organizational processes.

Process mining is leveraged across various industries to model and present process flows, including:

Manufacturing. Process mining helps manufacturers analyze their workflows to reduce downtime, and improve overall equipment effectiveness (OEE). Up-to-date views of process performance help to align resource allocation with demand.
Financial services. Financial services firms use process mining to streamline their interorganizational processes, from onboarding to loan processing. Process models will highlight inefficiencies or bottlenecks in process flows that should be addressed, including handling times and error rates.
Healthcare. Healthcare organizations manage several, complex in-person and online systems. With process mining, you’ll get insight into the day-to-day details of process execution. Healthcare companies can use this data to make improvements such as optimizing patient flow and reallocating appointments, which will improve overall quality of patient care.

What is RPA?

RPA (Robotic Process Automation) is a technology that uses software robots, or “bots” to automate repetitive tasks that are typically performed by human workers. RPA equips businesses to perform rule-based tasks faster. Once you’ve trained your bots to perform a task, you can monitor their performance to ensure they continuously improve and adapt to process changes.

RPA is valuable across all industries, namely:

Financial services. Financial institutions are renowned for undertaking various rule-based activities, including data entry and account reconciliation. RPA bots can complete these tasks by gathering data from specified sources, validating it and updating the relevant systems.
Transportation and logistics. RPA is most often used for routine logistics tasks such as order management, invoice processing and data entry. Employing automation in these areas helps to relieve employees to focus on higher-value tasks.
Insurance. Similarly to financial services, insurance process flows are rife with data-heavy tasks. RPA is used to automate manual tasks such as form processing, claims processing, and policy administration.

How process mining improves RPA results

Process mining and RPA are both technologies businesses employ to optimize their processes. But they serve different, complementary purposes.

Process mining provides detailed insights into how existing processes are performing, by collecting real-time event data from information systems. Businesses use process mining to:

Uncover the root causes of process inefficiencies, bottlenecks and deviations.
Spot redundant processes they may be unaware of.
Discover inefficient human-digital worker hand-offs, or vice versa.
Gather quantifiable data on the financial benefit of employing digital workers, or “bots”, for each process.

Crucially, identifying process flaws highlights opportunities for automation, which is where RPA comes in.

Employing RPA enables you to offload your most routine tasks to bots, freeing employees up to focus on more strategic work. With the insights gathered from process mining, you can pinpoint the best opportunities for bot-enabled processes. In the long term, by monitoring the impact of automation efforts, you can compare the value of human labor compared to digital labor in your processes, in terms of cost, accuracy, efficiency, and duration.

Overall, process mining improves RPA results by establishing a data-driven foundation for process governance, and enabling more detailed lifecycle management.

Process mining, paired with RPA, allows businesses to:

Monitor and assess automated process performance regularly

An invaluable facet of process mining is the ability to monitor process improvements. You can specify scenarios or conditions that should trigger real-time alerts for process review. This ensures your processes follow ongoing business compliance.

Target processes with the greatest automation potential

Process mining provides a comprehensive, end-to-end view of actual process execution, spanning multiple applications. These insights will highlight high-value RPA opportunities, considering all process variations, times and cost implications.

Execute RPA at enterprise scale

Scaling from tens to hundreds, or thousands, of bots requires significant process control at a business-wide level. Process mining provides the aerial performance view you need to ensure automation is synchronized across every business system it touches.

Avoid automation of broken or poorly executed processes

Full process visibility allows teams to identify, analyze and correct process execution issues before investing resources into RPA. You’ll have detailed insights to effectively address inefficient tasks, bottlenecks or compliance risks.

Maintain post-RPA visibility for impacted processes

By employing process mining to monitor your automation’s upstream and downstream impact, you’ll gather daily, quantifiable data on post-implementation impact. You’ll also have a clear view on whether your automation investment is operating as expected.

Spot redundant processes

Pairing process mining and RPA helps businesses to accelerate their digital transformation, by spotlighting redundant processes. With a more streamlined operational landscape, you can expand the scope of RPA investments while reducing time to value.

Achieve process excellence by combining process mining and RPA

Accelerate your digital transformation with our end-to-end process intelligence platform, ABBYY Timeline .

Timeline is powered by advanced process mining, giving you access to market-leading process visualization tools – including digital twins – with 100 percent visibility, to identify inefficiencies, bottlenecks, and outliers. Our platform is built to provide an interactive view of your processes, complete with real-time data updates. You’ll get granular insights into your ‘as-is’ workflows, enabling you to make data-driven process optimization decisions.

But, ABBYY Timeline goes beyond process mining. It will improve your business performance and customer experience by highlighting internal process trends, and providing advanced solutions for them. Our cloud-first, low-code environment is equipped with over 25 pre-built tools, designed for you to start conducting deep-rooted analysis within minutes. Out of the box, you can use its process simulation feature to test potential process adjustments and assess their impact on your business.

To unlock unparalleled business efficiency and performance, speak to one of our experts.

Tamas Mahr

Head of ABBYY Timeline Development, Administrative Director of ABBYY Hungary

Connect with Tamas on LinkedIn .

Editorial note: This blog post was originally published October 8, 2019, and was updated on July 23 to include an FAQ section and an updated definition of how RPA and process mining work together.

Frequently asked questions

What is the difference between process mining and robotic process automation?

Process mining and robotic process automation (RPA) are different, but complementary, technologies designed to optimize business processes.

Process mining is a technique used to analyze and visualize how a business’ processes actually operate. Using data from IT systems, it builds precise process models, pinpointing bottlenecks, inefficiencies, and workflow deviations. On the other hand, RPA is a technology used to automate repetitive tasks. Software robots are deployed to carry out predefined processes, freeing up human workers for higher-value tasks. RPA aims to boost efficiency by minimizing the manual business effort needed for routine tasks, and making business processes more scalable.

Process mining provides insights for understanding and optimizing processes, while RPA offers tools for implementing automation opportunities. Combined, they form a powerful combination for organizations seeking to elevate their operational efficiency and process excellence.

How is process mining used in RPA?

Process mining is the pivotal first stage for organizations aiming to automate their key workflows. Process mining exposes the inner workings of any business process as it actually happened, based on real data. By spotlighting inefficiencies, bottlenecks, and deviations, process mining helps you to identify the most impactful opportunities for automation. Thanks to its diagnostic capabilities, process mining ensures all RPA implementations are targeted and effective, delivering a greater ROI from your automation efforts.

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Mastering Efficiency Through the Integration of Process Mining Techniques and Robotic Process Automation