ABBYY Timeline 5 Adds Task Mining

ABBYY has expanded the capabilities of its Process Discovery platform, Timeline 5, to include Task Mining (also known as Process Discovery).

Process mining centres on performance metrics and the order of process steps to determine how a process is treated. With the help of log files, it allows companies to see the actual stages of completion of a process and pinpoint bottlenecks using business data such as key performance indicators (KPIs) for process improvement or the discovery of automation opportunities.

Moreover, task mining looks at how companies manage a specific step of the process through recordings and snapshots. Here, it helps companies identify what employees actually do when they perform a particular task and identify the common actions through user interactions. This data is then used to improve processes.

Task mining demonstrates how companies run their tasks more accurately, and process mining allows them to use user interaction data to understand how accurately they are executing their processes.

(ABBYY has published an explainer blog post at “Task Mining Extends ABBYY Process Intelligence with Desktop Analytics.”)

ABBYY says Timeline 5 analyzes desktop user interaction data and seamlessly links it with process details mined from system event data enabling organizations to enhance operational efficiency, improve customer experience and accelerate impactful digital transformation initiatives.

During the COVID-19 pandemic two-thirds (66.7%) of organizations encountered broken processes, according to a global Forrester study conducted in Q1 20201. Companies are struggling to fully realize the potential of digital transformation initiatives because they don’t have visibility into their business processes. The primary cause of these challenges is that their Business Process Management (BPM), Robotic Process Automation (RPA) and process mining tools lack the ability to understand the details of variable processes all the way down to the steps users take.

“With our new task mining capabilities, we continue to set the bar for Process Intelligence tools enabling our customers to realize the alignment of their people, processes and data critical to the success of their digital transformation efforts,” commented Scott Opitz, Chief Marketing Officer at ABBYY.

“The addition of these new capabilities to ABBYY’s Digital Intelligence platform will allow organizations to better identify, design, implement and monitor their RPA, Analytic Process Automation and Intelligent Document Processing initiatives so they can realize the greatest returns on those investments.”

ABBYY Timeline allows for visibility into business processes with insights from unstructured and semi-structured content delivered by ABBYY’s Content Intelligence suite. According to Gartner, the platform is positioned to “uniquely address content/case-based digital transformation initiatives, providing end-to-end visibility into highly variable content-centric processes and how they are performing to identify challenges, improve efficiencies and enhance customer experiences.”

The task mining capabilities of Timeline 5.0 are designed to:

  • Identify time-consuming repetitive tasks and recommend possible candidates for automation, thereby freeing up knowledge workers to focus on higher value activities and enabling leaders to make data-driven decisions for automation initiatives;
  • Uncover variabilities in task execution to enable automation safeguards that mitigate the risk of compliance violations;
  • Combine task-level details with Timeline’s intuitive point-and-click process analysis tools to provide a unified end-to-end and top-to-bottom operational understanding and ensure that digital transformation initiatives deliver predictable results and do not cause unintended consequences;
  • Easily scale to large numbers of desktop users to discover the full set of variations in user actions while strictly protecting sensitive information through a multi-faceted set of data security services.

https://www.abbyy.com/timeline/

 

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