As businesses undergo digital transformation and adopt new technologies and platforms, the complexities and expectations increase, challenging IT teams. Cloud services, SaaS apps, distributed and interconnected business services, and the explosion of data and resources that need to be managed are some of the challenges that IT teams face. To make IT teams more productive in managing IT operations, ServiceNow AIOps was introduced. ServiceNow AIOps empowers IT teams to not only keep up with the challenges but also be proactive.
How ServiceNow AIOps Improves IT Operations Efficiency
Uncover Data Silos to Identify Cause and Impact of Failures
Traditionally, IT teams have manual processes and work with data silos and disintegrated systems or tools, resulting in operational inefficiency. Often IT teams already burdened with a stream of infrastructure events are not acutely aware of the severity of events, their root cause, and how they impact the business.
ServiceNow is a single record system and AIOps cuts through the noise bringing out actionable insights at a centralized location in dashboards. Without having to go through data silos, data is correlated to understand the impact and root cause of failures. Having actionable alerts and impacted services displayed on a single dashboard saves time for the IT staff. The ServiceNow centralized system ensures transparency in communication and monitors IT infrastructure efficiently.
Reduce Issue Resolution Time with Automation and Self Service
Another advantage of AIOps in ServiceNow ITOM is that historical and real-time data can be used to identify and resolve the issues proactively. With historical data, it becomes easier for IT to find out how a similar issue was resolved in the past and use the same solution to automatically resolve the issue at hand.
To facilitate the resolution of repetitive issues, ServiceNow Knowledge base provides self-service options in the form of knowledge articles that specify solutions for various recurring problems. This way, IT teams can reduce the “Mean Time To Repair” (MTTR) and improve overall operational efficiency. The same self-service capabilities can also be used to solve real-time issues. Using predictive intelligence capabilities, an issue can be automatically detected proactively and can alert IT teams or be solved automatically. It can also optimize organizational processes and scale to meet increasing data volume and complexities.
Improve Operational Efficiency
ServiceNow AIOps can increase operational efficiency tremendously by applying machine learning to automatically analyze large quantities of events and data and process them for accurate correlation and identification of root-causes. AIOps can prevent service outages and other problems in the future significantly. According to ServiceNow, it observed: “a 67% reduction in P1 and P2 incidents, saving hundreds of hours of employee productivity.”
AIOps also increases agility in business to accommodate easy adoption of new tools and processes effortlessly, which is a critical need of most businesses. It is for these reasons that ReportBuyer's projects that the AIOps global market share will reach $20.1 billion by 2027.
Conclusion
Implementing ServiceNow AIOps does not demand as much as most large-scale AI initiatives do. Since the platform is based on existing IT operations knowledge, it doesn't require dedicated experts. It can be adopted without requiring major changes in processes or reskilling IT staff. Adopting AIOps can be the starting point of introducing AI culture within the organization and understand the viability of implementing AI on a much larger scale.
