The digital revolution we are immersed in is a permanent revolution. We live in an era where the ability to respond quickly, almost immediately, to changes has become an indispensable requirement for every company (and we would also say for every worker). 

In this context, data is the most precious and strategic resource: it represents the new capital (“the new oil,” as we often hear) on which to build operational efficiency, innovation, and competitiveness. 

In the field of IT Service Management (ITSM), the value of data is even more evident: it is thanks to real-time insights that organizations can make proactive decisions, optimize services, and prevent incidents. 

Be careful, though! It’s not enough to collect the maximum number of information possible: you need to transform it into Actionable Data in ITSM, that is, data ready to guide immediate and concrete actions. 

And it is precisely on this point that we have focused the continuation of this article: not yet another contribution on the abstract importance of so-called “Big Data,” but a very practical journey that starts from the advantages of Actionable Data, then focuses on their impact in ITSM, with the related challenges to face. 

From Simple Data to Actionable Data in ITSM 

The IT departments of any type of company collect enormous quantities of information every day: support tickets, performance metrics, system logs, user feedback; and much more. An enormous mass of raw data… which, however, serves little purpose if it is not “refined.” The real challenge consists in making this information immediately readable, organizing it, and contextualizing it. Only in this way can value and therefore competitive advantage be extracted from data. 

To put it another way: Actionable Data in ITSM means having processed and “deep” data that supports operational and strategic decision-making with maximum effectiveness and in the fastest possible times. 

In practice, intelligent use of data allows you to: 

• Move from reactive to proactive incident management 
• Optimize resource utilization and improve workflows 
• Drastically reduce downtime 
• Improve user experience through targeted and predictive interventions 
• Support continuous improvement and innovation tailored to your specific needs 

And we return to these advantages in more depth in the paragraph below. 

The Main Advantages of Actionable Data in ITSM 

From information to action: this is what happens with the breakthrough of Actionable Data in ITSM. Just above we listed some of the advantages that derive from their exploitation; here below we explore them in depth, grouping them into what seem to us the three most important cores. 

From Reactive to Proactive Management 

Real-time analysis allows identifying trends, anomalies, and weak signals that, if caught in time, allow intervention before serious problems manifest. 

Solutions like EV Observe from EasyVista, for example, allow analyzing data in real time and activating predictive alerts. 

In short, it’s the old (and always valid) adage: prevention is better than cure. Translated into more contemporary terms: moving from reactive management to a proactive approach that aims to make IT infrastructure anti-fragile and minimize the impact of incidents on business. 

Indeed, pushing the reasoning to its limit, a good exploitation of Actionable Data in ITSM significantly reduces the very number of critical incidents. 

Service Optimization 

Naturally, it’s not just about incident management. Through correct interpretation of data, it’s possible to identify bottlenecks, inefficiencies, and areas for improvement in normal IT workflows. 

It’s like having a very high-definition photograph of everything that happens in the company; a photograph that evolves from moment to moment. And this is the indispensable starting point for perfecting processes, optimizing resource utilization, and reducing downtime. 

The final result? Increased productivity and simultaneous reduction of operational costs. 

Also in this case, a practical example: a product like EV Service Manager helps optimize request management processes, improving efficiency and significantly reducing time-to-resolution. 

It’s a product that leverages the power of Artificial Intelligence systems; and this brings us directly to the next point, related to automation. 

Automation as a Trigger for Continuous Improvement 

Data is the starting point, but also the endpoint. It’s the basis on which to test, correct, and refine processes and strategies. Consequently, by constantly monitoring KPIs and operational metrics, organizations can trigger the virtuous spiral of continuous improvement to their IT services. 

And there is no continuous improvement without automation: the two sides can only reinforce each other; indeed, now we can say that one makes sense only in relation to the other. All this is valid on a large scale, on the IT macro-structure, but also on a small scale, on individual processes. 

A simple and very common example? In Customer Service systems, starting from the analysis of historical tickets, rules can be created to automatically manage recurring problems. 

Here, with a practical and absolutely everyday case, is the difference between simple data and Actionable Data in ITSM. And at this point, below, we are ready to isolate its key characteristics. 

The Key Characteristics of Actionable Data in ITSM 

We opened this blog post by immediately drawing attention to the difference between simple data and Actionable Data. However, we must be clear: it’s impossible to draw a sharp red line between one and the other. 

What can certainly be done, however, is to identify some characteristics that make data, precisely, “actionable.” Below we analyze 5 of them, choosing those that seem most decisive to us: 

1. Timeliness 

In ITSM, speed is crucial. Data must be collected, analyzed, and made available almost in real time to have real operational value. Only updated data allows for rapid decision-making on emerging criticalities, avoiding escalations that could compromise service quality. 

2. Relevance 

Not all collected data is truly useful. And utility is not measured in abstract terms. Actionable data, therefore, is always closely connected to business objectives and defined KPIs. It’s necessary to select, from the mass of available information, those truly significant for the specific ITSM context, filtering out background noise. 

All this, moreover, must be done in a largely automated manner; otherwise it becomes an immense and unsustainable job from all points of view. 

3. Accuracy 

Data quality is fundamental: errors, incompleteness, or inaccuracies can generate wrong decisions and worsen problems instead of solving them. It is therefore essential to adopt rigorous data governance practices to guarantee the reliability of the information on which IT strategies are based. Also in this case, much depends on the objectives of the individual company, the KPIs, the landscape in which it moves. 

4. Clarity and Readability 

Data must be useful to humans. Therefore, it must be presented in a clear and easily interpretable way by operational teams. Effective visualizations, intuitive dashboards, and synthetic reports help make data immediately usable, reducing the time needed for analysis and interventions. 

5. Contextualization 

Data makes sense only within a framework. To become truly “actionable,” it must be placed in a broader context: correlated to historical trends, integrated with other indicators, interpreted in light of business processes, but also of the specific productive sector in which the company is situated. Only this way can it guide truly effective choices. 

Challenges in Obtaining Actionable Data in ITSM 

Although the potential of Actionable Data in ITSM is enormous, there are several practical challenges that companies must face. Among these: 

• Information silos. When data is distributed in separate systems that don’t communicate with each other, it becomes difficult to have a complete and integrated view of IT processes. Overcoming silos requires information integration strategies, unified platforms, and management policies that favor sharing and transparency. 
• Lack of analytical skills. Data availability is not enough: specific skills are needed to analyze, interpret, and transform them into concrete actions. In short, the added value of human capital is needed. Investing in analytical training and, where necessary, integrating specialized figures like data analysts or data scientists becomes a priority for every modern IT team. 
• Legacy systems. Many organizations still find themselves bound to legacy systems that don’t natively support integration with advanced analysis tools. This limits data accessibility and their valorization. 

Fundamentally, it’s a very normal and human problem of habit and resistance to change: “it’s always been done this way, why change?” The answer lies in the fact that it’s the world around us that continues to change; and standing still is equivalent to losing ground. 

Conclusions 

We live in an era of permanent digital transformation. In this scenario, data analysis is the engine of IT competitiveness. Investing in collection, analysis, and action systems based on Actionable Data in ITSM is no longer an option, but an absolute necessity for those who want to aim for efficiency, proactivity, and continuous improvement of all IT processes. 

FAQ 

What is meant by Actionable Data in ITSM? It refers to analyzed and contextualized data that allows making immediate and informed decisions to improve IT service management. 

What are the main benefits of using Actionable Data in ITSM? Among the main benefits we find: faster and more proactive decision-making, process optimization, incident reduction, and improved customer experience. 

What are the most common challenges in obtaining them? Overcoming information silos, lack of analytical skills in IT teams, and integration of legacy systems.