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ServiceNow - From Operational Management to Operational Intelligence


Jitin Hirani

January 15, 2018

Organizations across the globe are under increased pressure to meet their accelerating business demands. The rise of digitization and adoption of technologies such as cloud, big data, virtualization, and IoT have been instrumental in driving innovation across organizational layers. Organizations are also leaning towards solutions that help them accommodate volatile business circumstances and identify potential business opportunities to improve competitiveness. ServiceNow has made its place in the enterprises as a go-to solution to improve business processes and workflows and act as a critical enabler of their digital transformation journeys.

Worldwide, organizations have successfully leveraged ServiceNow’s Operational Management capabilities to ensure greater availability of enterprise applications and infrastructure for uninterrupted business continuity. The ITOM offering from ServiceNow ensured that enterprises could manage processes, applications and enterprise infrastructure in a service-centric manner. With greater visibility into the IT landscape of an enterprise, the ITOM offering could help organizations increase their operational management capabilities, prevent outages and ensure business continuity.

However, with the rising volumes of data owing to digitization drives, mobility, and increased automation, it is becoming clear that in the near future organizations will have to employ some level of machine learning or Artificial Intelligence to manage these data volumes and filter through the data noise. Along with this, with the rise of the digital enterprise, IT has moved away from the static and monolithic infrastructure to the continuous delivery model by leveraging a mix of virtual and physical resources. Organizations are looking at IT to find innovative solutions to their business problems. For that, businesses are leveraging data analysis using data collected from business services to gain insights into customer behaviors and assess market dynamics.

As we move into the application economy, organizations also want to tap into the data generated by the IT and application infrastructure that is associated with business services. Logfile data, performance metrics, application transaction performance, etc. are a few things that are captured constantly. However, for this data to deliver value, organizations need to go beyond data filtering, normalization, and threshold crossing and basic correlation and show a direct impact on the company’s bottom line. This can be done by showing them opportunities to improve operational efficiencies and reduce the cost of service downtime owing to threats or infrastructure failures.

The need for operational intelligence

The technology stack that most organizations use has developed phenomenally over the past decade. Today, enterprise-class infrastructure consists of micro-services, cloud, containers, and mobility. This has also led to the growth of machine-generated data. However, given the rising volumes of data, most IT operations personnel find themselves drowning in innumerable alerts. They have to invest a lot of time in sifting through these alerts and identifying the false alerts from the real ones, impact analysis and then applying the corrective actions. As enterprises adopt the DevOps and Continuous Delivery models, the number of IT resources on the need of management also increase, thereby further increasing the burden on IT operations to manage a larger number of operational events and metrics and derive insights from them.

One of ServiceNow’s latest offerings brings a greater level of Operational Intelligence to your enterprise. The Operational Intelligence offering, an add-on to ServiceNow Event Management, gives the IT department the capability to proactively analyze the IT infrastructure of an organization to identify issues and prevent outages. This application leverages machine learning capabilities to analyze the IT infrastructure information of an organization, automatically determines dynamic thresholds and identifies anomalies before they become incidents. This application effectively highlights disruptions leveraging data and helps organization not only avoid outages but also helps them identify the root cause of the same.

With this application, ServiceNow helps organizations:

  • Employ operational metrics to detect outofband behavior of infrastructure items. It employs the use of raw operational metric data instead of processing events from monitoring tools, applies machinelearning algorithms to create thresholds for normal behavior and eliminates the need to manually manage numerous monitored thresholds.

  • With Operational Intelligence identifying anomalies, promoting them to alerts and initiating health action becomes faster, simpler, and convenient and IT can view trends and anomalies in real-time.

  • Using operational metrics, data IT can triage alerts, identify probable causes by using a service history view and correlate metrics to understand probable causes of issues.

ServiceNow’s Operational Intelligence, helps organizations further automate alerts processing and thereby allows IT operations greater insights and more flexibility. Along with identifying anomalies and reporting them as alerts, Service Now’s Operational Intelligence application also helps its users create custom views of the infrastructure metrics to investigate these issues.

In order to match the speed of business, organizations have to ensure that they move from a reactive IT management plan to a proactive management plan – a plan which helps avoid outages that negatively impact business continuity. ServiceNow’s Operational Intelligence helps in accomplishing exactly that.

Want to know how your IT teams can leverage ServiceNow to operate faster and in a scalable manner? Talk to our ServiceNow Certified experts today!

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