ManageEngine, a division of Zoho Corporation and a leading provider of enterprise IT management solutions, today announced a significant upgrade to its flagship IT analytics solution, Analytics Plus. Version 6.0 introduces Spotlight, a contextual recommendations engine powered by AI, designed to identify key inefficiencies in IT operations and suggest corrective strategies.
The 2023 State of Analytics Engineering report found that time to business insight is the biggest challenge for nearly 50% of surveyed directors. Spotlight dramatically reduces the time IT managers and CIOs spend analyzing various IT metrics and coming up with remedies to fix structural fault lines in operations. By incorporating decision-intelligence capabilities, Analytics Plus now facilitates contextual decision-making, addressing a crucial gap in traditional analytics software.
For instance, Analytics Plus can analyze correlations between the age of IT assets, their frequency of failure, and the meantime to repair. Based on these parameters, it suggests the optimal time frame for asset replacement. This approach ensures that organizations neither dispose of assets prematurely, losing usable value, nor retain them for too long, negatively impacting employee productivity. With the introduction of Spotlight, ManageEngine reinforces its commitment to enhancing IT operations through intelligent, data-driven solutions.
“While traditional analytics tools excel at providing a platform for analyzing any type of data, they often lack the necessary context of the data they are analyzing. Deriving meaningful and context-specific insights is becoming increasingly challenging due to a significant disconnect: the people performing the analysis are skilled at mining data but often lack the IT context, making it difficult to translate findings into actionable business decisions,” said Samantha Hall, Service Delivery Manager, Leathams Ltd., a UK-based food supplying company.
Analytics Plus’ built-in AI engine is programmed to study common IT processes and identify solutions to achieve desired results more quickly. Spotlight acts like an assistant, constantly monitoring for bottlenecks or operational inefficiencies and offering tips for corrective action. By bringing in IT context and leveraging AI capabilities, Analytics Plus ensures that organizations can address issues more effectively and efficiently.
“Organizations no longer want to spend hours mining data for actionable insights. They require ready-made strategies that they can implement immediately to see rapid results,” said Rakesh Jayaprakash, product manager and chief analytics evangelist at ManageEngine. He added, “There are sufficient tools in the market that promise automation and remediation for day-to-day network and application failures, but there’s a lack of focus on strategic decision-making. This is the gap Spotlight aims to bridge.”
Root Cause Analysis
Quick decision-making is only half the journey; IT managers and CIOs also need a way to backtest their decisions to ensure a new strategy or model will achieve the desired results. In addition to decision intelligence capabilities, ManageEngine is introducing the Root Cause Analysis feature, which automatically identifies the top factors contributing to a particular trend. This feature allows IT managers and CIOs to verify whether their changes or decisions are having a positive impact.
For instance, if tools are implemented for auto-remediation of L1 network issues, Root Cause Analysis can look at the increased uptime and highlight the reduction in L1 network issues as the major contributor to better network uptime.
No-Code Auto-ML for Deep Analysis
The new version of Analytics Plus empowers IT teams to create custom machine learning (ML) models without writing a single line of code. Traditionally, developing and deploying ML models was restricted to experts. However, Analytics Plus’ no-code ML platform democratizes this process, allowing IT managers to develop ML models directly on the data they are familiar with.
With this capability, IT managers can build ML models for prediction and classification, such as a predictive model to derive the probability of ticket escalations based on various factors or related events. This approach ensures the development of highly specific and accurate models because they are built on the organization’s unique data and validated by the very people who use it daily.
Unified IT Metrics Library
Analytics Plus serves as a command center and decision hub for IT by contextually analyzing all IT data, enabling organizations to cross-correlate metrics and identify interdependencies. Analytics Plus version 6.0 introduces the Unified IT Metrics Library, listing all KPIs from an IT environment in a single view, effectively acting as a comprehensive directory of metrics. This makes searchability and reusability easier, breaking down silos created by various IT tools and serving as a single source of truth for any metric that IT teams need to track.
“Traditional IT data analysis is often confined within individual tools. For instance, resolution time of incidents is limited to ITSM while mean time to repair a device is restricted to IT operations management. This inhibits cross-correlation and prevents organizations from obtaining a complete picture of their IT infrastructure. By analyzing all these metrics together in a centralized platform, organizations can unlock significant value,” said Jayaprakash.
The Unified IT Metrics Library democratizes data by making a catalog of KPIs readily available for technicians to conduct their analyses, which can also be consumed by other IT applications for contextual integration. This comprehensive approach enhances governance and ensures that all relevant metrics are easily accessible and managed effectively, driving quick decision-making.
In addition to these key features, Analytics Plus version 6.0 includes a range of productive enhancements such as multivariate forecasting, workflow charts, support for distributed processing (on-premises) and more than 10 new integrations with popular IT tools, detailed here.
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