I started looking at #Flow from an observability perspective.
As in, Flow Observability. 👇 The term observability is originally borrowed from control theory, where the “observability” of a system measures how well its internal state can be determined from its outputs.
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I started looking at #Flow from an observability perspective. 👀
As in, Flow Observability. 👇
The term observability is originally borrowed from control theory, where the “observability” of a system measures how well its internal state can be determined from its outputs.
In software observability (from reliability engineering), the same concept applies: it’s about measuring how well a system’s state can be understood from telemetry like metrics, logs, traces, and profiling.
Now, let’s extend that to Flow Observability—measuring how well a System of Work can be understood from telemetry, such as flow metrics, aggregations, and normalisations.
How does Flow Observability differ from traditional Metrics Dashboards?
1️⃣ Real-Time Insights
2️⃣ Contextual Understanding
3️⃣ Intelligent Anomaly Detection
4️⃣ Holistic System of Work Health Monitoring
5️⃣ Automated Recommendations for course correction
6️⃣ Enhanced Visibility Across Silos
7️⃣ Robust Alert System
Imagine: Contextual advanced analytics, predictive capabilities, comprehensive monitoring, and alerting.
That’s how I see Flow Observability—a platform designed to provide deep, actionable, real-time insights into the flow of work in large, complex organisations.
💬 What are your thoughts on this concept? Do you see value in Flow Observability? 👇