ABBYY Named A Leader In Gartner's Magic Quadrant For Process Mining

Dwayne Parkinson
Jun 26, 2024 10:32:42 AM
ABBYY Named A Leader In Gartner's Magic Quadrant For Process Mining
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Gartner has named ABBYY a leader in the technology space known as "Process Mining" in their Gartner 2024 Magic Quadrant.  Process Mining is not a new concept, and most organizations are already doing it to some degree, whether they know it or not.  However, as organizations become aware of Process Mining in terms of technology and solutions, they are able to leverage industry leading tools like ABBYY Timeline to analyze, optimize and improve processes much more effectively and efficiently than in the past.

What is Process Mining?  At a very high level, it's figuring out how an organization actually does business and figuring out ways to optimize those processes.  Process Mining does this through three phases: Discovery, Monitoring & Optimization.

Discovery is the act of trying to figure out what happens in a process.  It includes trying to find hidden costs, impediments and problems that are impacting the process and discover the undocumented real-world problems that people are managing within the organization.  In the world of 1990's process improvement, this would involve many hours of interviews with subject matter experts in the organization, volumes of documentation and hours of white board process flow sessions.

Modern Process Mining solutions take a slightly different approach.  Process Mining solutions use Task Mining to record and analyze log files, desktop keystrokes and mouse clicks, and data from ERP and other systems in the process to intelligently extract that data into a Process Model.   ABBYY has a Task Mining solution that discovers, analyzes, (and monitors) tasks to predict behavior by extracting and combining knowledge from desktop activities, event logs and case-based processes with a high degree of variability.  This information often contains data that has been extracted from ERP systems and documents via OCR.  The information is then used to create a picture of what actually happens within an organization in an updated Process Model.

Once the Process Model is in place, Monitoring can begin.  During this phase, organizations seek to understand the difference between what they believe they're doing vs. the reality of all the additional steps and problems that actually occur in the real-world process.  ABBYY Process Intelligence also incorporates a more effective methodology of monitoring than just looking at volumes of data periodically extracted from systems.  It allows raw data from process systems to be loaded for immediate analysis.  This eliminates much of the pain traditionally associated with "scrubbing" and preparing the data for monitoring and it allows organizations to quickly find root causes for deviations from the expected process. 

Once monitoring is in place the final step in Process Mining is Optimization.  During this phase ABBYY Timeline is used to perform Simulations within the Process Model to see how future outcomes from the process can be improved with predictive analytics.  The most optimal simulation can then be rolled back into a new Process Model which is then evaluated in the real world using the same Process Mining techniques.  The cycle begins again and the goal of "Continuous Improvement" that many organizations championed back in the 1990's can finally become a reality.

Organizations that are able to leverage Process Mining have a distinct advantage over their competition as they become more agile, responsive and able to adapt to change.  For organizations to effectively leverage Process Mining, they need a robust set of integrated Process Mining tools and the latest release of ABBYY Timeline is at the cutting edge of the Process Mining space.  

When was the last time you analyzed your order to cash process to fully understand what is going on?  What about your contract to build process?  Check out the latest from the ABBYY Process Intelligence solution and their great resources for understanding where to start with Process Mining.

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