Minit is now part of Microsoft. Learn why Microsoft has acquired Minit.

5 Ways Process Mining and Robotic Process Automation Complement Each Other

  • 06. 05. 2021

Share on social media


Download article as *pdf

Just give us your email where we will
send you pdf file article.


Some misunderstandings are floating around cyberspace regarding Process Mining and another emerging technology, Robotic Process Automation (RPA).

Table of Contents

    Let's clear things up, and learn about some of the ways these two technologies act in tandem to bring you better ROI.

    To kick things off, here is a basic definition of Process Mining and RPA:

    • Process Mining is about gaining insights into your business processes through the data in your IT systems. Output? A complete picture that accurately depicts the “as-is” state of your business processes.
    • RPA refers to the use of so-called “bots,” to automate process steps in your company that previously required human action.
      These technologies and techniques differ in five ways, highlighted by how they work together to further your business goals.

    1. Process Mining Gives You the As-Is State of Your Business Processes

    ...then RPA takes the complete picture of these processes, and turns it into actionable automation.

    Process Mining software sits on top of your existing IT infrastructure, and sifts through the event logs left there by other systems. These logs contain the what, who, and when needed to produce an interactive depiction of your processes.

    Then the RPA team can take the process map and deploy the bots to complete these exact steps. Over and over again, either endlessly or on a set schedule.

    2. Process Mining Highlights the Best Candidates for Robotic Process Automation

    Analysts in your company can then take transparent process map from Process Mining tool to determine which processes are ready for automation. They can also use it to identify steps that have multiple variations, discrepancies, or other inconsistencies, that will require further investigation.

    By starting with such analysis, you can bypass one of the most frequent failure points of RPA: automating faulty processes. Since RPA needs standardized, data-centered, and easily repeated tasks in order to be most effective, this step is crucial to a successful deployment.

    It doesn’t pay to automate a bad process--all you’ll get is the same bad output, just faster and more consistently.

    3. Process Mining Locates Deviations Before RPA Automates Them

    In cases where you find that a process has too many variations or deviations, you'll get the chance to harmonize these steps to ready them for automation.

    If a process has been using a workaround for so long that nobody even realizes, employees won’t know to tell you about it.

    However, Process Mining doesn’t rely on anyone’s memory to collect its data.

    Say you’re working with a process that has 45 variations. Ten of these represent single-digit percentages of total cases. By finding this out via Process Mining, you have the ability to streamline the process. Maybe you can combine those ten process variations into one.

    Now you can go ahead with the automation using RPA, knowing that you aren’t automating a mess.

    4. RPA Uses the Process Map as a Guide for Bots

    The process of deploying bots is made much simpler if you have a process map outlining the steps conducted by human employees.

    For a simplified example, say you uncover a process that consists of ten steps, all of which are performed by a single employee working at their regular workstations. The process steps consist mainly of mouse clicks on certain menus and keyboard input to copy and paste data into a particular spreadsheet. The analyst can simply perform those same tasks in order and use that as a template for the bots.

    Process Mining provides the template, RPA takes that template and automates the process. This allows future compliance checking and monitoring to be run much faster, and the cycle can continue being improved.

    5. RPA Gives Results, Process Mining Measures Them

    Okay, you have some processes automated, you're generating statistics and new numbers to compare to your KPIs.

    Now, it’s time for Process Mining to step in and provide a way to compile those numbers for comparison. Since Process Mining can be run at any time, it can generate a new process map of the automated process to compare to the old results from pre-automation.

    That holds true for generating a new baseline for use going forward as well.

    Thus, the improvements provided by your RPA bots can be quantified by Process Mining, allowing you to measure up to your KPIs, as well as providing you the basis for a Proof-Of-Concept.

    3 Key Aspects of the Relationship Between Process Mining and RPA to Remember:

    • They are complementary: one reads event logs in IT systems to learn about business processes, while the other automates those processes.
    • One supports the other: Process Mining allows the deployment of bots to be done more efficiently and for the results to be more effective.
    • Higher chances of success: RPA projects are more likely to succeed with the addition of Process Mining.

    As you're now on board with Process Mining and RPA, are you aware of the processes in your company that can be automated right away? Are there some that need adjustments first? Let us know in the comments.

    If you still need to clarify how your company can benefit both from Process Mining and RPA, schedule a quick call with our representative to discuss all your questions.

    Picture of Jana Gregusova

    Written by Jana Gregusova Jana Gregusova is the Process Consulting Leader here at Minit. Check out her articles!