Enterprises are embedding observability into their decision-making frameworks, enabling a shift from reactive troubleshooting to proactive innovation.

Digital businesses today generate a flood of telemetry—metrics, logs, traces, and events—at a scale that grows exponentially with every new application, cloud service, and user interaction. In one recent IDC survey, every organization reported sharing observability data across teams, yet nearly half said poor collaboration still prevents them from identifying performance problems. This paradox highlights a critical challenge: As the volume and complexity of digital signals surge, the ability to create shared understanding and orientation within organizations becomes both more difficult and more essential.
 
The problem: Exponential telemetry and human limits

The rise of digital business has led to a dramatic increase in the amount and diversity of telemetry data. IT estates now span hybrid clouds, microservices, edge devices, and global user bases, each emitting streams of data that must be collected, processed, and interpreted. Observability platforms emerged to help teams sift through this wave of data, using advanced signal processing and machine learning to surface anomalies and root causes. However, the sheer scale of telemetry now routinely exceeds human capacity to comprehend, making it harder for teams to collaborate, innovate, and drive meaningful change.
 
This challenge is not just technical. As organizations attempt to lead transformations, they encounter barriers rooted in the lack of shared mental models. Without a common understanding of what the signal means and how it relates to business outcomes, teams are forced to restore systems to a known good state rather than additively driving toward desired results. This creates a cycle of troubleshooting, missed opportunities for innovation, and organizational tension.
 
The state of the industry: Tools, personas, and the need for shared context

Observability tools have evolved rapidly, often optimized for specific personas such as developers, operations, SREs, or business analysts. Each tool provides tailored dashboards, alerts, and analytics, but this specialization can fragment context and hinder cross-team collaboration. IDC research found that 43% of organizations struggled with collaboration while 37% faced scaling challenges and 33% reported integration issues with their current observability tools.
 
Vendors have responded by accelerating feature releases and expanding integrations, but the pace of change can outstrip the ability of teams to keep up. Executives interviewed by IDC frequently cited outdated documentation, failed professional service engagements, and difficulty understanding how new features interact with existing environments. The underlying issue is not just with the technology itself, but with the absence of a shared orientation framework, a cognitive toolkit that helps teams interpret signals, set boundaries, and make decisions together.
 
In practice, many organizations default to whatever processes are embedded in their chosen tools or rely on informal models held by a few heroic individuals. This approach is fragile, especially under high cognitive load or rapid change. The lack of formalized, adaptable practices makes it difficult to scale collaboration, maintain innovation, and ensure decisions align with business goals.

 
The solution: Rethinking observability as part of digital decision-making

To address these challenges, organizations must broaden their understanding of observability. Rather than viewing it as a set of tools for solving isolated technical problems, observability should be seen as one component of a larger decision framework. This framework encompasses not only the collection and analysis of signals, but also the creation of shared context, orientation, and purposeful action.
 
Orientation is a cognitive process that requires people to talk, think, and work together toward common goals. Observability platforms can support this process by providing shared views, standardized taxonomies, and mechanisms for mapping technical signals to business outcomes. However, vendors must go beyond presenting root causes and correlations; they need to help organizations build the mental models and practices that enable effective collaboration and decision-making.
 
IDC's research highlights the importance of partnership between enterprises and observability vendors. Executives increasingly seek partners that will codevelop orientation frameworks, participate in leadership processes, and embed organizational practices directly into the tools used to manage the digital estate. This shift reflects a growing recognition that technology alone cannot solve the challenges of exponential telemetry and organizational complexity; human skills, shared understanding, and adaptive practices are equally vital.

Impact: Toward a new era of digital collaboration

The move toward shared observability and orientation has profound implications for how organizations operate. By integrating observability into a broader decision-making framework, enterprises can transform reactive troubleshooting into proactive innovation. Teams gain the ability to interpret signals in context, align actions with business objectives, and adapt rapidly to change.
 
This evolution will require investment in both technology and human skills. Leadership must prioritize the development of informal, adaptable practices that foster collaboration and creativity. Vendors must design platforms that support shared context, explainability, and codevelopment. The ultimate outcome is a more resilient, innovative, and aligned organization, one that can navigate the signal tsunami and turn data into meaningful action.
 
Message from the sponsor
HPE is ranked as a major player in the IDC MarketScape: Worldwide Observability Platforms 2025 Vendor Assessment. In its quantitative and qualitative assessment, the MarketScape highlights HPE OpsRamp Software strengths in unified visibility across metrics, events, logs, and traces, supported by native OpenTelemetry intake, eBPF-based auto instrumentation, dynamic discovery, service mapping, and automated delivery. The report also notes HPE OpsRamp Software delivery maturity as demonstrated by its software-as-a-service (SaaS) platform, which processes billions of metric samples daily and terabytes of data per customer. Read the excerpt to understand how collaborating with the right observability provider can enable greater scalability and resilience across your complex, distributed environments.

By Author:
Shannon Kalvar,
Research Director for Enterprise Systems Management,
Enterprise Client Platforms, Observability, and AIOps at IDC