Use Case: Data-Driven Process Insights

Use Case: Data-Driven Process Insights

This example demonstrates how a process owner or analyst can leverage CIB ins7ght to gain actionable insights from process data and make informed, data-driven decisions.
It combines the Global Overview and Process Analysis – Bottleneck pages to illustrate a full analysis workflow.

Step 1: Global Overview: High-Level Insights

Start on the Global Overview page:

  • Review the main KPIs for all processes, such as:

    • Started Instances
    • Finalized Instances
    • Successful Instances
    • Average Process Duration
    • Incidents
    • Completed User Tasks
    • Average User Task Duration

  • Look for anomalies or trends:

    • Are there spikes in process duration?
    • Are incidents concentrated in a specific period?
    • Are user tasks taking longer than expected?

Screenshot placeholder: Global Overview page

Interpretation Example:
If the number of Incidents for a process has gradually increased over the past month, this indicates a potential efficiency issue that requires deeper investigation.

Step 2: Drill Down with Bottleneck Analysis

Select the process and version to analyze on the Process Analysis – Bottleneck page:

  1. Examine the BPMN overview to understand the structure and sequence of activities.
  2. Use the Activity Heatmap to identify:
    • Activities with unusually high durations.
    • Frequently executed activities that may contribute to delays.
  3. Select two activities in the heatmap to measure the average waiting time between them, highlighting potential slow transitions.
  4. Explore the Bottleneck Graph:
    • Identify process instance outliers (max/min durations).
    • Use the matching table to see details for these outlier instances.

Screenshot placeholder: Bottleneck page with heatmap and graph

Interpretation Example:
If a particular activity consistently has longer durations than expected, this could be a potential point of improvement. Outlier instances can reveal rare but critical process failures that need corrective action. You will also be able to get more in-depth information about the instances that are outliers, so you can better analyze them. If a particular instance takes more time then what you consider to be accepable, you can see more information on it.

Step 3: Version Comparison

  • Use the Version Comparison Graph to see how different versions of a process perform over time.
  • Compare average durations across versions to assess whether process improvements or changes have been effective.

Interpretation Example:
If a newer process version shows reduced average duration, this confirms that optimization efforts were successful. Conversely, longer durations indicate areas for review before further deployment.

Step 4: Make Data-Driven Decisions

By combining insights from KPIs, activity-level analysis, and version comparisons, users can:

  • Pinpoint inefficiencies and bottlenecks.
  • Identify processes that are prone to incidents.
  • Prioritize process improvements based on impact.
  • Make decisions supported by objective, quantitative evidence instead of assumptions.

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