Key features of Process Mining

  • Release version: Xanadu
  • Updated August 1, 2024
  • 2 minutes to read
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    Summary of Key features of Process Mining

    Process Mining in the Xanadu release offers ServiceNow customers a comprehensive set of tools to automatically discover, analyze, and optimize business processes. It enables organizations to gain detailed insights into process performance, identify bottlenecks, and collaborate effectively to drive continual improvement.

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    Key Features

    • Automated Process Discovery: Define projects by selecting relevant process tables, activities, and breakdowns to mine business processes. Activities represent process steps, while breakdowns act as filters for detailed volume, velocity, and conformance insights.
    • Summary and Insights Page: Provides a quick overview of process performance through key performance indicators (KPIs), improvement opportunities, and their status.
    • Analyst Workbench: Offers an interactive visual workflow analysis with process maps, filters, bottleneck identification, and machine learning (ML)-driven insights. It also removes duplicate audits and self-loops for clearer process views.
    • Collaboration and Sharing: Facilitates project sharing with stakeholders, including options to add notes and screenshots within projects to enhance communication.
    • Integrated Continual Optimization: Allows creation and tracking of improvement initiatives, integrated with ServiceNow’s Continual Improvement Management capabilities.
    • Integration with Performance Analytics and Benchmarks: Enables root cause analysis by linking Process Mining data with Performance Analytics indicators, accelerating insights into low-performing areas.
    • Predefined ITSM Content Pack: Provides ready-to-use IT Service Management process mining projects and initiatives for faster implementation and time to value.
    • Process Comparison: Supports comparing multiple processes to explore performance differences and deviations.
    • Multi-dimensional Processes: Mines hierarchical or multi-table process data for a comprehensive view of process dependencies.
    • Bottleneck Analysis: Visualizes activity transitions to identify bottlenecks impacting process flow.
    • ML-Based Clustering: Groups similar records using machine learning to uncover patterns and clusters within processes.
    • Performance Indicator Analysis: Enables quick analysis of processes behind performance indicators (e.g., SLA breaches, customer satisfaction scores) directly from platform lists or reports.

    What to Expect

    With Process Mining, ServiceNow customers can expect automated discovery of detailed process flows, actionable insights into bottlenecks and inefficiencies, and tools to collaborate on and track continuous improvements. Integration with Performance Analytics and predefined content accelerates root cause analysis and implementation. The solution supports complex, multi-dimensional process analysis and leverages ML to enhance understanding of process variations.

    Some key features of Process Mining are listed in this topic.

    Automated process discovery

    Define a project by selecting a process table, and the activities and breakdowns that you want to mine. You can choose to edit a project in the Project Builder too.

    Configure at least one activity definition for your business process. An activity defines the different steps that can occur as part of your business process.

    You must configure a breakdown that acts as a filter and provides insights into the categorical volume, velocity, and conformance.

    Summary and Insights page
    Quickly understand process performance. From the Summary and Insights page, view key performance indicators, improvement opportunities overview, and list of improvement opportunities. For more information, see Summary and Insights page.
    Analyst Workbench

    Analyze business workflows visually with the interactive process map, explorative filter panel, and prebuilt performance metrics. You can see process variation, breakdowns, bottleneck analysis, and ML and smart rule-based insights. Also, all duplicate audits are removed, and that removes all self-loops in the graph. For more information, see Analyst Workbench.

    Easy collaboration and sharing

    Share projects with stakeholders and collaborate with notes and screenshots within a project. For more information on sharing projects, see Share a Process Mining project. For more information on creating notes, see Adding notes to a project.

    Integrated continual optimization

    Create and view statuses of improvement initiatives. For more information, see Integration with Continual Improvement Management.

    Integration with Performance Analytics and Benchmarks
    Compare processes

    Compare processes to investigate performance differences or deviations. For more information, see Comparing projects.

    Multi-dimensional processes

    Multi-dimensional processes refer to mining a hierarchy of tables. It’s a multi-table mining. It’s used for a more comprehensive view into process dependencies. For more information, Configure multi-dimensional mining.

    Bottleneck analysis
    View activity transitions you’ve defined with the bottleneck analysis feature. For more information, see Viewing business insights.
    Analyze processes using ML-based clustering
    Group similar records into machine learning pattern-identified clusters. For more information, see Cluster analysis.
    Quickly analyze the processes behind performance indicators and record lists
    Easy-to-see process behind scenarios such as bad service level agreements or CSAT scores. Run the analysis from any platform list or report.