Analytics dashboard not updating after workflow completion

We’re experiencing a frustrating issue with our process analytics dashboard in Appian 22.4. After workflows complete successfully, the dashboard doesn’t reflect the updated data for anywhere from 15-45 minutes. We’ve checked the dashboard refresh interval settings, which are configured to refresh every 5 minutes, but this doesn’t seem to be working as expected.

The delay is particularly problematic for our operations team who rely on real-time visibility into process completion rates. We suspect it might be related to cache invalidation not triggering properly when process instances complete, or perhaps the event-driven data sync mechanism isn’t firing correctly.

Has anyone encountered similar dashboard refresh delays? Are there specific cache settings or event configurations we should be reviewing to ensure the analytics layer syncs properly with completed workflow data?

Be careful with reducing that sync interval too aggressively. We tried setting it to every 2 minutes and it caused significant database load during peak hours. The Process Analytics engine runs complex aggregation queries that can be resource-intensive. You need to balance real-time needs with system performance. Consider whether you actually need real-time analytics or if a 5-10 minute delay is acceptable for most use cases.

Thanks for the pointer. I checked the Admin Console and found the Process Analytics sync job is scheduled to run every 30 minutes, which explains the delay. Is there a way to trigger this sync based on process completion events rather than a fixed schedule? Our business needs near real-time visibility.

Another option is to implement a hybrid approach using record types with real-time sync. Create a custom record that captures key workflow metrics and updates immediately when processes complete. You can then build reports and dashboards off this record data instead of relying solely on Process Analytics. This gives you real-time visibility for operational metrics while still using Process Analytics for deeper historical analysis.