Are you enabling insight-driven IT operations–or just reporting the past?
In the world of rapid innovation and disruption, a mature analytics strategy is no longer a competitive advantage–it's a business imperative. This interactive assessment is designed for IT teams who want to benchmark and elevate their analytics capabilities. Measure your maturity across 7 strategic pillars–and gain a clear roadmap to drive efficiency, optimize operations, and deliver transformative outcomes.
1. Which industry does your organization belong to?
2. Do you currently use any analytics solution for your IT?
Your approach to collecting, centralizing, and integrating IT operational data.
1. What is the current state of your IT data quality and consistency?
2. How easily can you access and query cross-functional IT data ?
The sophistication of your analytics platforms, tools, and technologies (including AI and ML) employed for analysis.
1. What analytics tools does your team primarily use for monitoring and reporting IT KPIs and events?
2. How integrated is your IT analytics tool with your IT applications?
Your IT's expertise, organizational commitment, and importance to data-driven insights, data governance, and security.
1. How would you describe your company's culture toward IT decision making?
2. How do you handle sensitive or confidential IT data (e.g., passwords, PII, incidents)?
How analytics insights are shared across your teams and used to support IT decision-making.
1. How well do cross-functional IT teams collaborate around analytics?
2. How accessible are analytics and insights to non-technical stakeholders such as technicians, managers, and leadership?
The incorporation of automation, AI, and ML within your IT analytics workflows.
1. How sophisticated are your analytical techniques across IT domains?
2. To what extent do you use automated RCA in ITOps and ITSM?
The maturity of your IT monitoring, alert enrichment, and incident correlation processes, with a focus on analytics usage to reduce noise, detect anomalies, and accelerate resolution.
1. How centralized is your incident monitoring and alerting across infrastructure, applications, and endpoints?
2. How do you currently track IT health across domains?
How your IT analytics align with business goals and deliver data-driven insights to guide strategic decisions, optimize operations, and improve IT outcomes.
1. What role does IT analytics play in shaping your organization's strategic planning and decision-making?
2. Is there a centralized dashboard for CXOs to track business-impacting incidents?
2.5/5 Overall analytics maturity
For analytics beginners, IT insights are unstructured and reactive, with decisions largely based on intuition. Data is manually collected, siloed, and poorly organized, with minimal access or collaboration across teams. Reporting is ad hoc, using basic in-product tools or spreadsheets, and data-driven decision-making is rare. While there's awareness of analytics, no formal strategy or governance is in place.
Reactive analysts have begun to recognize the value of IT analytics and are taking early steps towards a structured analysis process. Dashboards and visual reports are used within departments for general intelligence, and efforts are underway to break data silos through creation of central data lakes or repositories. Basic automation support for data collection exists, but integration gaps, RCA inefficiencies, and limited analytics skills still hinder broader adoption.
Emerging proactive analysts recognize the value of proactive analytics and intend to make advancements in that direction, moving beyond "what happened" to an in-depth exploration of "why it happened". Self-service analytics is emerging, empowering more users with data-driven insights. Systematic diagnostic analysis, cross-functional correlations, and scenario analysis is performed to understand the root cause behind IT events and issues.
Predictive and AI-enhanced organizations are highly data-driven, leveraging advanced analytics platforms and widespread AI adoption. Predictive models, AIOps, and MLOps are actively used to forecast trends, detect anomalies, and drive proactive decision-making. Analytics plays a central role in anticipating issues and optimizing both IT and business outcomes.
IT analytics champions represent the pinnacle of IT analytics maturity. Analytics is viewed as a strategic asset and deeply embedded across all IT and business functions. AI is leveraged to its full potential through automated root cause analysis, no-code ML models, and advanced decision intelligence. The focus shifts from predicting outcomes to prescribing optimal actions–enabling continuous optimization, innovation, and autonomous IT operations.
Begin by identifying a centralized analytics platform to unify reporting across IT functions.
Encourage cross-functional collaboration and leadership buy-in for a shared analytics strategy.
Connect core systems like ITOps, ITSM, and endpoint management into a common repository to enable basic visibility and insight.
Refine your existing data pipelines and management to ensure IT data is more easily accessible to wider users across teams.
Shift from reactive static reports to embedded, proactive diagnostic analytics that help uncover patterns, bottlenecks, and causes.
Simplify and democratize the analytics process by adopting an intuitive analytics platform that enables all IT stakeholders, including technicians, service owners, and managers, to query and explore data with minimal training.
Automate analysis of common IT metrics, such as SLA compliance, alert volumes, utilization trends, and patching success rate, across departments for consistent visibility.
Implement enterprise-wide data quality practices, centralized governance, and standardized access controls to prepare for predictive and automated analytics workflows.
Introduce frameworks to automate data movement, enhance infrastructure observability, and ensure secure, scalable access for analytics and ML processes.
Begin exploring NLP-based narrative summaries, automate RCA and anomaly detection, and introduce custom predictive modeling to minimize manual analysis and enable faster, more accurate decisions.
Leverage AutoML tools to develop tailored models for forecasting, risk scoring, performance prediction, and more, without needing dedicated data science teams.
Foster a culture where AI-driven insights guide actions at every level–from leadership strategy to technician-level interventions.
Optimize decision-making processes, especially for well-established operations. Make analytics the basis for innovation and overall development, even for complex decisions where optimization may still involve manual oversight.
Implement decision intelligence frameworks that recommend next best actions for key scenarios and incidents across the IT landscape, including incident management, workload balancing, capacity planning, and remediation.
Stay ahead by monitoring and adopting cutting-edge techniques like GenAI, deep learning, agentic AI, and autonomous analytics frameworks to meet shifting IT demands.
Extend your AI-driven systems to handle complex and high-impact decisions, triggering actions autonomously based on real-time recommendations and forecasts.
Explore intelligent agents capable of independently identifying issues, recommending solutions, and executing actions–minimizing human intervention while maximizing operational speed and precision.
Dedicate efforts toward experimentation, custom model development, and strategic use of AI and ML to lead your industry in data-driven IT operations.
Analytics Plus offers a user-friendly, drag-and-drop reporting interface that empowers IT teams to build custom dashboards without technical expertise. With one-click data integration across tools like ITSM, monitoring, security, and network management, your teams can establish a single source of truth. Prebuilt reports and dashboards accelerate your journey, making it easier to transition from isolated, ad-hoc reporting to unified, centralized analytics.
Analytics Plus bridges the gap between data silos and actionable insights. With its self-service BI, an intuitive drag-and-drop interface, and robust integration across 250+ ITSM, ITOps, network, and security tools, it empowers even non-technical users to build and explore reports. Its diagnostic analytics capabilities, including drill-downs, correlation reports, and automated RCA, help simplify investigation efforts, reduce firefighting, and provide early signals of emerging issues, enabling your team to proactively manage IT operations with clarity and control.
Analytics Plus equips you with a full suite of advanced AI and ML capabilities designed for IT teams. It allows you to derive deeper insights and simulate IT outcomes by utilizing features like clustering, multi-variate forecasting, and scenario analysis. Furthermore, you can develop and deploy custom ML models specifically tailored to your IT data and operating conditions, all without writing a single line of code. You can tap into Zia, the AI-powered analytics assistant, which provides automated diagnostic insights, narrative summaries, and instant answers to natural language questions, ultimately reducing time-to-insight and enabling faster, smarter decisions.
Analytics Plus revolutionizes the journey from predictive maturity to intelligent action by providing unified, real-time IT views, transforming scattered metrics into a strategic IT data fabric. Its decision intelligence capabilities offer automatic, actionable recommendations based on system conditions, trends, and forecasts, highlighting high-impact areas for resolution. The platform is also enhanced by Zia, a GenAI-powered analytics assistant, which simplifies complex data through natural language insights, automated summaries, and instant answers, significantly accelerating the time to informed action. Furthermore, Analytics Plus' scenario analysis capability lets you model "what-if" scenarios to determine optimal IT strategies pre-execution.
Analytics Plus is purpose-built to fuel continuous innovation and support your journey beyond predictive analytics. It lets you deploy custom AI/ML models for domain-specific intelligence. With GenAI and LLM-powered decision intelligence and analytics assistants. You can get real-time recommendations, narrative insights, and automated root cause analysis through natural interactions. The platform also enables closed-loop automation by integrating insights with IT orchestration systems for immediate, autonomous action, triggering workflows to address hidden anomalies across your IT landscape. This means you're preparing for the future with systems that analyze, decide, and act without relying on traditional analytics tools, making Analytics Plus your IT's real-time decision intelligence engine, not just another reporting tool.
