Move the needle on the KPIs that matter most with Process and Task Mining

[Martin Barclay]

We usually associate KPIs with conventional analytics, for example, ServiceNow Platform Analytics which provides insights into past performance, where things are at right now, and forecasts the path forward to hitting targets.

What has often been overlooked in the past but is now clearly understood to be critical to the success of AI agents and workflows in general is Process Intelligence, anchored by Process and Task Mining.

Without Process and Task Mining and the critical data feedback loop they provide, AI Agents and workflow stakeholders are not grounded in the reality of verified workflow execution data, resulting in hallucinations, missed opportunities for improvement, repeating and scaling bad processes, and automating the wrong things. In short, they are flying blind.

Process and Task Mining complements Platform Analytics with another layer of intelligence by revealing “the why behind the KPI”, the reasons why a KPI is trending in one direction or another. It also surfaces solutions (in the form of insights and improvement opportunities) that can be put in place to solve process bottlenecks/slowdowns, inefficiencies, and compliance or conformance gaps that impact the KPIs you see on a Platform Analytics dashboard.

But insights and improvement opportunities aren’t enough. They must be put into action to make an impact. This is where native Process and Task Mining on the same platform where AI agents and workflows run is such an advantage because the mean time to improvement (MTTI) is so much faster than with external process mining tools. Processes and tasks can be mined in minutes instead of weeks and put into action right away through ServiceNow AI Platform automation and data tools like AI Agent Studio, App Engine, and Workflow Data Fabric.  Turning insights into action on a single AI platform for fast MTTI is what we call closed-loop process intelligence.

The demo shows closed-loop process intelligence in action through the experience of a business process owner who sees a KPI in Platform Analytics that’s not hitting the target, and needs to do something about it quickly,  without relying on a process analyst, to help move a C-level initiative forward.

We hope this shows how an expanding scope of ServiceNow workflow stakeholders, from process analysts to process owners, front-line managers, AI CoE, and LOB leaders - can reap the benefits of closed-loop process intelligence on the ServiceNow AI Platform.