Organizations are saturated with data — yet information often gets lost in the process. Why? Because technology teams analyze metrics, logs, and alerts, while business teams focus on outcomes, KPIs, and customer experience. Daily operations remain fragmented. Data exists in different systems, formats, and contexts. Seventy-nine percent of teams work in silos, data structures are redundant, and reports contradict each other.
The answer is not collecting even more data. It is creating a shared source of truth — a Single Source of Truth in which IT and business see the same reality. One reliable, consistent data foundation. It may sound idealistic, but it is neither theoretical nor aspirational. SSOT is technically achievable and strategically essential.
When Data Complicates Daily Operations
Employees spend an average of 2,4 hours each day gathering the information they need for their work. Organizational information flow is further constrained by the fact that 79% of teams say collaboration occurs along silo lines: information often does not reach the people who need it, when they need it.
More data does not automatically mean better insight. Seventy-two percent of respondents have experienced situations where the volume of data hindered rather than supported decision-making. Eighty-six percent reported that information overload reduced their confidence when they needed to decide quickly. As a result, eight out of ten leaders later questioned whether they made the right decision — not due to a lack of information, but because they lacked consistency and a clear point of reference.
What Is a Single Source of Truth?
A Single Source of Truth (SSOT) is an operating model designed to ensure that every stakeholder in an organization works from the same reliable, unified, and up-to-date data foundation. It does not refer to a single database or system, but to a consistent data structure where information is accessible in context and interpretable by everyone.
In a well-designed SSOT environment, the path of data is fully traceable. Customer information, transactions, events, and system logs do not live in isolated tables across separate databases — they are available through a unified logical layer. Finance, IT, digital teams, and the contact center all rely on the same structure, which means they see the same information about a failed transaction, a slowdown, or the impact of a campaign.
SSOT and Observability: How Do They Work Together?
An SSOT cannot function effectively with a unified data model alone. It also requires real-time insight into how technical events influence business outcomes. This is the bridge that observability provides.
Observability platforms — such as Dynatrace — collect and organize data in a way that creates a single coherent view across applications, infrastructure, user experience, and business metrics. Raw logs, metrics, and traces become contextualized, connected information. A slow page load or a failed API call immediately appears as a drop in transaction success, revenue impact, or increased churn risk.
In an SSOT-enabled environment, observability acts as the system’s sensory layer:
- the same platform identifies where an IT issue originated,
- and shows which business processes or customer journeys were affected,
- all in real time, enriched with historical data and full traceability.
This eliminates the divide between business and technology. During a prolonged incident, it becomes immediately clear which services are affected, how critical the impact is, and which intervention will reduce risk the fastest. In optimization work, improvements can be directly linked to conversion rates, cart abandonment, or reductions in customer complaints.
Why This Matters for Executive Decision-Making
Effective decision-making does not depend on the amount of data available, but on how clear, consistent, and real-time the underlying picture is.
In large enterprises and public sector environments, most executive decisions happen under time pressure. There is rarely room for lengthy alignment, report reconciliation, or interpretive debates. A Single Source of Truth eliminates these friction points:
- the question “which data is correct?” disappears,
- conflicting reports are eliminated,
- unnecessary loops and delayed decisions are reduced.
In a functioning SSOT–observability model, technical signals, service quality, and business impact form a single process. A performance degradation or API error can immediately be linked to:
- lower conversion,
- an increase in customer complaints,
- heightened regulatory exposure,
- or rising cloud costs.
Summary
Organizations today do not lack data — they lack unified interpretation. Fragmented systems, siloed operations, and divergent business–technical perspectives create parallel versions of reality. This slows reaction time, increases risk, and weakens decision-making.
A Single Source of Truth resolves this by providing a shared, reliable, real-time data foundation for every team. Observability ensures that this foundation is complete: it connects technical events with business outcomes and adds the context needed for meaningful decisions.
Together, these approaches transform operations. Not by adding more data, but by establishing a clear point of reference. Not by multiplying dashboards, but by creating a shared reality. Not by accelerating analysis, but by enabling faster, more confident decisions.
Closing
The Telvice advisory approach is built on this foundation: the goal is not more tools, but a unified, real-time operational logic that the entire organization can rely on. This is what enables the stability and predictability that, in the AI era, are no longer competitive advantages — they are operational requirements.
