Reported impact
Business outcome
ServiceNow cut change-management processes by 84%, discovered 74% of HR cases that needed recategorization, and uses one optimization product across about 900 processes.
- Productivity Improvement
- Speed to Market
IT Operations Automation · Real-time Analytics
ServiceNow had hundreds of complex internal processes where bottlenecks and rework were hard to spot with traditional reporting alone.
Reported impact
ServiceNow cut change-management processes by 84%, discovered 74% of HR cases that needed recategorization, and uses one optimization product across about 900 processes.
ServiceNow had hundreds of complex internal processes where bottlenecks and rework were hard to spot with traditional reporting alone. ServiceNow implemented a ServiceNow-centered stack built around Process Mining, Workflow Data Fabric, RaptorDB, and Now Assist. Key components included Process Mining finds bottlenecks and rework in process data; Workflow Data Fabric connects operational data and automation context; RaptorDB accelerates workflow analytics; Now Assist adds generative search, summarization, and drafting. Work enters as cases, requests, or automations, is classified or summarized by Process Mining and Now Assist, and uses context from RaptorDB before Workflow Data Fabric routes or fulfills the work. The same record of work is then exposed back to agents and end users through the platform. Running process analytics and continuous improvement on one data model reduced manual handoffs and made expansion easier.
Work enters as cases, requests, or automations, is classified or summarized by Process Mining and Now Assist, and uses context from RaptorDB before Workflow Data Fabric routes or fulfills the work. The same record of work is then exposed back to agents and end users through the platform.
But before we went all in on using Process Optimization throughout the enterprise, we had to see if it added measurable value
Incident management: Any time an incident is generated across ServiceNow IT services, whether it’s user created (reactive) or created through monitoring (proactive) 2
It was difficult to know where to start and what to fix to drive more productivity and enable better employee and customer experiences
Using process mining to uncover and repair inefficiencies 84% Faster change management processes 74% Of HR cases discovered for recategorization 1 Product to optimize 900 processes Discovering process inefficiencies We rely on process mining to find friction points that slow down daily ServiceNow processes, then we systematically fix these issues to be more productive
Vijay Kotu SVP, Analytics These were our results using ServiceNow Process Optimization for two weeks: Incident management Inefficiencies: - High CPU alerts consuming IT operations team bandwidth (automation opportunity) IT operations team manually triaging the micro-segmentation heartbeat failure INC Too many escalations from L1/L2 to L3 teams Potential impact if improved: 28% faster 5% more productive Asset management Inefficacies: 22% of requests taking additional step, adding an average of three days to the resolution 30% of requests waiting for four days for approval; Only 2% of requests getting rejected by managers 22% of requests took 10 days for license allocation after approval 31% faster 12% more productive Problem management Delay in problem assessment by the problem coordinator Delay in closing the root cause analysis task by the task assignee Delay in starting the remediation task by the task assignee 40% faster 22% more productive Request management Delay in server access request fulfillment, requiring considerable manual effort High volume for active directory group lifecycle management Manual intervention required to fulfill server reboot request 25% faster 10% more productive HR case management 74% of HR cases are recategorized 60% of the HR cases take longer than six days to resolve Case resolution is delayed, resulting in a lower employee NPS score 46% faster 34% more productive Our in-platform Process Optimization product identified very specific opportunities for improvement within each workflow
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
Related