BigPanda and ServiceNow: Improve incident outcomes

Focus on actionable tickets, deliver insights for faster incident resolution, and improve service quality with less effort.

Benefits

  • Move faster: Provide service desk teams with context-rich incident data upfront, and consistently to minimize escalations, reduce effort, and speed up response.
  • Elevate and automate reporting: Combine historical ITSM and real-time incident data to gain new insights. Improve incident-management workflows for better team efficiency, workloads, and ROI impact.
  • Increase ITSM value and impact: Operationalize configuration management to keep your CMBD accurate and increase the value of existing ITSM platform investments.
  • Leverage cost-effective GenAI: Automate complex incident tasks without costly disruptions to support expensive ITSM license upgrades.

Improving service quality and optimizing the efforts of your IT teams can reduce costs and increase customer satisfaction. But it’s usually easier said than done.

Legacy event-management systems with manual rules and workflows are part of the problem. They make it harder to sort through the noise, find the important alerts from all your monitoring tools, and transform them into actionable tickets that speed up incident identification and logging processes.

Meanwhile, the absence of critical diagnostic information creates significant barriers to scaling incident management. Without the ability to quickly identify impact, urgency, and root cause, you’re stuck reacting to incidents instead of doing proactive problem resolution.

The BigPanda platform overcomes these challenges, reducing ticket volume and giving IT teams the necessary insights to identify and respond to important incidents. Platform benefits include:

  • Intelligent alerting Generate actionable ServiceNow tickets from telemetry data and update them as the incident evolves to prioritize and route issues based on their impact.
  • AI-powered incident investigation Resolve incidents faster with insights into impact, urgency, and root-cause analysis, even for dynamic infrastructures.
  • Access to previous incident data Compare live incidents with historical data to access details of previous actions, get ahead of P-0s, and act faster.
  • Continuous improvement Identify repetitive incidents, uncover the root cause, and utilize data-driven methods from incident response data to minimize impact and cost.

How BigPanda works with ServiceNow

BigPanda uses multisource infrastructure enrichment combined with historical ITSM ticket data to give incident-management teams the context to identify, respond to, and remediate incidents early on.

The BigPanda bidirectional integration with ServiceNow ITSM focuses on creating smart tickets with alerts and context populated in the correct fields. It improves the ITSM platform’s value by identifying gaps in the configuration management database (CMDB) and operationalizing accurate configuration management.

  • Automate the service ticket lifecycle: BigPanda generates ServiceNow tickets from correlated alerts in seconds, updating them as incidents evolve for accurate categorization, prioritization, and routing to the right teams.
  • Speed triage and reduce escalations: Improve and accelerate incident-management workflows. Benefit from highly informed, real-time AI-powered insights, including incident impact, root cause, and similar historical incidents within ServiceNow.
  • Reduce blind spots: Automate configuration item (CI) discovery to Identify missing items from alerts and update the CMDB. Adding operational characteristics from BigPanda enhances incident management and maximizes the value of the ITSM platform.
“With the help of BigPanda, we reduced incidents by 69% and significantly improved IT operations management efficiency.”

Samy Senthivel
Director of Observability Services, Autodesk

Intelligent Alerting

Incident Intelligence

Automated CI Discovery

Challenge

Manual event-correlation rules and the need for CMDB accuracy make it difficult to reduce ticket volume and identify important tickets.
Siloed teams, tools, and incident-related data prevent teams from getting the information to take proactive steps and stay ahead of incidents.
The cost of maintaining CMDB accuracy, combined with licensing new generative technologies to automate tasks, makes it difficult to justify additional investment.

Business value

Free teams from performing manual tasks and improve processes to enhance organizational impact across IT.
Provide responders with immediate access to data to enable quick remediation. Reduce the resources needed to resolve incidents faster with less impact.
Maximize the value of existing core ITSM investments that improve long-standing service-operation processes and adoption.

Intelligent Alerting

Challenge

Manual event-correlation rules and the need for CMDB accuracy make it difficult to reduce ticket volume and identify important tickets.

Business value

Free teams from performing manual tasks and improve processes to enhance organizational impact across IT.

Incident Intelligence

Challenge

Siloed teams, tools, and incident-related data prevent teams from getting the information to take proactive steps and stay ahead of incidents.

Business value

Provide responders with immediate access to data to enable quick remediation. Reduce the resources needed to resolve incidents faster with less impact.

Automated CI Discovery

Challenge

The cost of maintaining CMDB accuracy, combined with licensing new generative technologies to automate tasks, makes it difficult to justify additional investment.

Business value

Maximize the value of existing core ITSM investments that improve long-standing service-operation processes and adoption.
“Effective collaboration between IT service and IT operations makes sense to the frontline professionals whose work lives improve with friction-free cooperation and problem-solving. AI-curated information and automated workflows deliver practical advances that make work more productive and enjoyable.”

Valerie O’Connell
Research Director, EMA Research