Today, we take it for granted that digital services simply work. We book flights, initiate transactions, pay bills. Behind all of this are complex IT systems. When these business-critical systems fail to operate as expected, business operations are immediately affected. As a result, an increasing share of business issues becomes visible through digital systems, even when they appear first as business symptoms.
Partial solutions already exist for individual aspects of this challenge. Addressing it as a whole, however, required a new approach. This approach is known as business observability.
What Is Business Observability?
Business observability is the capability that allows an organization to understand, in real time and in context, how its business processes operate through digital systems, and how technical events translate into business impact.
Implementing business observability typically does not require entirely new data sources. The starting point is the vast amount of IT data that modern systems already generate. The difference lies in how this data is interpreted: aligned with business questions rather than viewed purely through a technical lens.
This enables organizations to answer critical questions that previously remained unclear:
- Which business process was affected?
- What is the impact on revenue, customer experience, or costs?
- Is immediate intervention required, and if so, where?
The fundamental advantage of business observability is that business operations become the focal point, rather than isolated technical components.
This results in real-time decision support, which is especially important in environments where digital operations run continuously and even minor disruptions can lead to rapid business consequences.
How Did We Get to Business Observability?
2000–2010: The Era of IT Monitoring
In this period, the primary goal of IT visibility was to ensure systems were running. The focus was on infrastructure and basic service availability: whether servers were up, applications responded, and network connectivity was intact. Traditional monitoring tools were effective for these needs.
This approach aligned well with business realities at the time. Systems were mostly monolithic, business processes relied less on digital channels, and change happened more slowly. Technical failures typically had limited and delayed business impact.
2010–2015: Growing Complexity
As digital services expanded, IT environments became more complex. Web applications, integrations, and service-oriented architectures emerged. Business processes increasingly spanned multiple systems, and failures could no longer be traced to a single component.
Monitoring still indicated that “something was wrong,” but it became less effective at explaining why issues occurred or where to intervene. Troubleshooting took longer, while business impact became visible much faster.
The limitations of traditional monitoring approaches became truly evident with the rise of complex systems. According to a 2025 study, 73% of organizations reported significant visibility blind spots in modern, distributed architectures, where issues often only become apparent after their business impact has already materialized.
2015–2020: The Emergence of Observability
With the rise of microservices, containerization, and cloud platforms, observability gained prominence in its technical sense. By correlating logs, metrics, and traces, teams could uncover technical cause-and-effect relationships, diagnose issues more quickly, and stabilize operations.
This represented a major step forward for IT teams. They could see not only that an issue occurred, but also how a request moved through the system. Interpretation, however, largely remained focused on technical behavior.
The adoption of observability practices has led to measurable operational improvements. According to the study, organizations using such approaches reduced mean time to detect issues by up to 60%, while average resolution times decreased by 45% compared to traditional monitoring.
2020–2023: Cloud Observability
As hybrid and multi-cloud environments became common, IT operations turned fully dynamic. Infrastructure changed continuously, workloads fluctuated, and business processes increasingly operated in real time. In this phase, cloud observability became a baseline requirement for maintaining operational stability.
Technical visibility improved significantly, yet business leaders increasingly needed to understand what system behavior meant for business processes, not just for infrastructure health.
2023– : Business Observability
Business observability does not appear overnight. It usually begins when an organization senses that something is wrong from a business perspective, yet cannot clearly identify the root cause. Metrics decline, customers grow dissatisfied, processes slow down, while technical indicators initially appear normal.
At this point, the focus shifts. Organizations stop looking at systems in isolation and start examining business processes. Questions change: Where does an order stall? Why does a case take longer to complete? At which step does customer experience deteriorate? IT data gains new meaning when directly tied to these operational questions.
As this mindset spreads, responses change as well. Not every anomaly demands immediate action, and not every alert represents a business issue. Attention moves to where impact truly matters. Over time, this fosters closer collaboration between business and IT teams, built on shared language and shared goals.
Where Does Business Observability Stand Today?
Business observability is not yet a universal state. It is better described as a direction of travel. Few organizations can claim full maturity; most are progressing through experiments, partial implementations, and varying levels of readiness.
In reality, many organizations already have some form of IT observability in place. Data exists. Dashboards exist. Technical visibility is often advanced. What is frequently missing is the integration of the business perspective, which prevents a complete understanding of cause and impact.
Organizations that have reached a more mature level of business observability rarely see dramatic technological breakthroughs. The advantage appears elsewhere: problems are detected earlier, issues do not escalate unnecessarily, and decisions are made with clarity rather than intuition. This sense of control and confidence is what creates meaningful long-term business differentiation.
How Can Business Observability Be Implemented?
Executives typically ask three questions: how much does it cost, how disruptive is the change, and when results will become visible. From this perspective, business observability is often less risky than expected.
If an organization already uses an observability platform such as Dynatrace or Datadog, additional technology investments are often unnecessary. The data usually already exists. The primary change occurs at the level of interpretation rather than tooling.
Implementation does not happen all at once, nor across the entire organization. It usually starts with a single business-critical process—where uncertainty is already costly. This incremental approach keeps change manageable and avoids disrupting day-to-day operations.
In many cases, initial results become visible within weeks as existing information finally connects into a coherent picture.
Telvice Zrt. supports its customers in turning predictable operations into a deliberately built organizational capability.
We help organizations prepare for growing complexity and AI-driven operations by building on existing observability foundations.
Get in touch with us and request a free expert consultation or demo to explore what business observability could mean in your environment.
Sources
Dynatrace – Business observability drives digital transformation
Sharma, A. (2025) – The Evolution of Observability: From Monitoring to AI-Driven Insights, European Journal of Computer Science and Information Technology
Dynatrace Observability Lab – What Is Business Observability (video)
Dynatrace Observability Lab – Business Flow Analysis and Real-Time Decision Making (video)
Broadcom – From Kalman to Kubernetes: A history of observability in IT
