E-BOOK
Agentic IT Operations,
Built for Action
How enterprises can turn ServiceNow and BigPanda into an engine for intelligent IT operations, without waiting for perfect data.
1
Introduction
2
Enterprises are drowning in noise
3
The real cost isn’t the alert, it’s everything it sets in motion
4
BigPanda makes ServiceNow more actionable
5
Autodesk transforms from reactive, manual operations to a more efficient, context-driven incident management model
6
A better operating model, not just better tickets
7
From reactive firefighting to agentic incident orchestration
Key takeaways from this e-book:
- Only 25% of alerts are actionable, and fragmented context slows triage as 50% or more of MTTR is wasted waiting for information.
- Agentic ITOps platforms can make sense of imperfect, noisy data, extract meaningful signals from it, connect them within your technology components, and operationalize them into action.
- Customers who integrate BigPanda with ServiceNow can save up to 15,000 hours of manual work, reduce tickets by 43%, and reduce bridge calls by up to 74%.
- The business impacts of the BigPanda and ServiceNow integration include 430% ROI, $2.85 million median annual benefits, and payback in less than a year.
Introduction
“This partnership is about helping customers get more from their ServiceNow investments. Whether an organization is early in its ITOM journey or operating a mature NOC, they can start seeing improvements in MTTR within weeks.”
As organizations grow, their systems and data become more complex, and IT operations become harder to manage.
At the same time, observability data is increasing rapidly, which makes it harder to understand system, infrastructure, and application performance. Teams are overwhelmed, trying to make sense of what’s happening and why. This slows their ability to take action and puts service continuity at risk. ServiceNow and BigPanda help complex enterprises turn overwhelming operational data into faster, more effective incident response actions, enabling a more scalable path to resilient, proactive service operations.
This is made possible by combining an agentic layer that filters noise, correlates signals, and enriches them with context, with an operational backbone that turns intelligence into governed action. Together, this helps enterprises reduce noise, improve incident quality, automate workflows, and significantly accelerate IT operations.
“This partnership is about helping customers get more from their ServiceNow investments. Whether an organization is early in its ITOM journey or operating a mature NOC, they can start seeing improvements in MTTR within weeks.”
Enterprises are drowning in noise
Modern enterprises are built on digital services. Every customer interaction, transaction, and internal process depends on systems that must always be available, responsive, and connected. Uptime is not just an IT metric. It’s a business requirement tied directly to revenue.
The reality behind these critical services is more complicated. Organizations have webs of legacy systems and modern architectures, distributed teams, and tightly interdependent workflows. Their monitoring and observability tools are generating streams of alerts and tickets. Data from their cloud platforms, infrastructure, applications, and services flow from everywhere.
The problem with this vast volume of data is not visibility, but clarity. Enterprise IT data comes from too many places, in too many formats, and at such a rapid pace that signals are noisy, context is fragmented, and ownership is unclear. Every handoff between teams introduces delay, ambiguity, and cost.
Why “perfect” data isn’t the answer
Enterprises often assume that their operations can only be fixed when their CMDB and observability data are structured, with fully mapped environments and topology. However, this expectation of perfection has created a barrier to progress: change feels disruptive, and it means a long path to value. Postponing action until conditions are “ideal” results in nothing happening.
The problem is how observability data is interpreted. Teams responsible for responding to incidents are often overwhelmed by telemetry that was designed for instrumentation, not action, making it harder to understand what’s happening and why.
This is where an agentic approach thrives, by actively interpreting signals, identifying relationships, and surfacing what is most relevant. To make sense of imperfect, noisy data, extract meaningful signals, connect them within your technology components, and operationalize them into action.
The real cost isn’t the alert, it’s everything it sets in motion
The issue isn’t only that incidents happen, it’s that reactive operations are expensive to run. Teams are stuck responding to what has already happened, spending time interpreting low-value signals instead of resolving issues. Too much effort is being used with monitoring, deduplicating, investigating, escalating, and re-routing. Support structures exist just to make sense of signals, adding delays before meaningful action can happen.
This means the cost to serve increases. Every handoff resets understanding. Manual triage, escalation, and noisy tickets keep skilled engineers and the IT operations team stuck in low-value work rather than focusing on the improvements that drive the business forward.
As environments grow in complexity, enterprises respond by adding more tools, people, and processes. But instead of creating clarity, it creates an operating model that scales efforts rather than outcomes.
This means IT teams are continually responding to customer issues, rather than identifying proactive steps through intelligent monitoring. The result? Delays to issue identification and resolution, inconsistent service quality, risks to SLAs, and negative impacts on customer experience, CSAT, and trust. Operational drag, uncontrolled, quickly becomes commercial drag.
BigPanda makes ServiceNow more actionable
CIOs aren’t only looking to fix incidents faster or see fewer tickets on a dashboard. They want to lower the day-to-day costs of running IT operations and move their organization away from reactive firefighting to a more predictive, preventive service model.
ServiceNow already sits at the center of this ambition, where work is governed, routed, and resolved. But its effectiveness depends on the quality of what flows into it. BigPanda sits upstream of ServiceNow, making sense of high-volume, noisy signals, correlating related events, enriching them with context, and identifying what is most likely happening. Before that information becomes work inside ServiceNow and teams complete tasks within the ServiceNow platform.
Together, this helps complex enterprises build a better operating model for IT operations. It reduces low-value tickets, speeds up triage, and creates clearer ownership. It also turns noisy, fragmented operations into faster, more coordinated action in the real-world conditions enterprises already manage.
Complementary roles that enhance value
BigPanda delivers agentic automation for ITOps, reducing the human effort required to understand what matters by correlating signals, enriching incidents, and helping determine the right action earlier. This is possible even without a mature or fully accurate CMBD.
By pushing actionable, context-rich incidents into ServiceNow ITSM, this transforms passive ticketing systems into a backbone for operationalizing intelligence consistently across incident workflows. Not only does this help lower the cost of reactive operations and enable greater returns from ServiceNow, it creates more capacity for growth and change and empowers organizations to act before issues are felt by their customers.
Autodesk transforms from reactive, manual operations to a more efficient, context-driven incident management model
“With the help of BigPanda, we reduced incidents by 69% and significantly improved IT operational efficiency.”
Global software company Autodesk struggled with an average of 100,000 monthly application alerts across 25 fragmented monitoring tools, with low-quality tickets lacking context and ownership. By integrating BigPanda with ServiceNow, Autodesk was able to:
- Correlate and fewer tickets into actionable incidents
- Automate ticket creation with full context
- Streamline workflows across teams
“With the help of BigPanda, we reduced incidents by 69% and significantly improved IT operational efficiency.”
A better operating model, not just better tickets
“BigPanda supercharges ServiceNow for complex enterprises, consolidating thousands of alerts into actionable, context-rich incidents that enable earlier intervention and faster response times. By enriching workflows with AI-powered root cause analysis, BigPanda helps IT teams shift from reactive firefighting to proactive operations.”
Enterprises don’t have to wait for perfect data conditions to move from fragmented IT operations to fast, effective action. BigPanda empowers even those organizations that have CMDB gaps, incomplete CI mappings, missing ownership or outdated relationships. BigPanda transforms the way businesses run, automatically surfacing configuration items in live alerts to rapidly improve data quality and continually enhance the quality of ServiceNow data over the long term.
“BigPanda supercharges ServiceNow for complex enterprises, consolidating thousands of alerts into actionable, context-rich incidents that enable earlier intervention and faster response times. By enriching workflows with AI-powered root cause analysis, BigPanda helps IT teams shift from reactive firefighting to proactive operations.”
From reactive firefighting to agentic incident orchestration
““We use ServiceNow daily for incident, problem, and change management. Integrating BigPanda’s incident and change capabilities into ServiceNow has reduced manual ticket creation and improved correlation between incidents and changes. Overall, the integration has been highly effective.”
Together, BigPanda and ServiceNow are redefining how complex enterprises run IT operations. By combining signal processing with a proven workflow backbone, this bridges the gap between overwhelming data and effective action.
By shifting to agentic-supported operations, systems not only detect issues but also actively shape how they are understood and resolved. The result is not just better incident management, but increased operational capacity and enhanced efficiency. One that reduces noise, removes operational and commercial drag, and enables a shift from a reactive to a proactive service management model.
““We use ServiceNow daily for incident, problem, and change management. Integrating BigPanda’s incident and change capabilities into ServiceNow has reduced manual ticket creation and improved correlation between incidents and changes. Overall, the integration has been highly effective.”
DEMO
See BigPanda and ServiceNow in action
Save up to 15,000 hours of manual work and improve MTTR by up to 50%.
