ABBYY’s Intelligent Automation Month
Process intelligence is an approach to process improvement that’s driven by advanced data analytics. It combines advanced process mining and task mining technologies with the latest artificial intelligence (AI) to provide detailed data about business processes, illustrating where they are working well and where resources are being wasted. This insight enables businesses to perfect process performance and optimize the use of time and money. Predictive analytics and process simulation capabilities provide a clear picture of your operations to make decision-making about technology investments easy.
Process intelligence enables businesses to automatically build an interactive digital twin of their processes, analyze them in real time to identify bottlenecks, and predict future outcomes to facilitate decision-making of technology investments.
Visualize the flow of your work through the process stages and see the delays, bottlenecks, and outliers. Gain insight into your “as-is” customer processes to understand challenges.
Simplify compliance by using audit trails to build a model of your process and reason against it. Receive alerts when rules set in place are broken and follow up immediately to ensure that it won’t happen again.
Drive down the cost of process evaluation and make it easy to identify high-value improvement opportunities. Discover the most valuable opportunities to implement RPA or automatically monitor the performance of your existing RPA processes.
Previously, process mining relied on subject matter experts. Now, process mining software gives decision-makers facts and figures from real-time event log data to back up their decisions by serving as an irrefutable source of truth.
Forrester Research provides guidance on optimal use of process intelligence
We asked guest speaker Bernhard Schaffrik, Principal Analyst at Forrester Research, to share some insight with us about what the “automation fabric” is and how process intelligence can support it. In this Q&A, Schaffrik explains how businesses can utilize process optimization tools to enhance the stability of the automation fabric, including best practices for doing so.