It’s time to move beyond viewing observability as just a way to detect and resolve technology-related availability and performance issues. Instead, let’s start thinking about observability as a driver of value and a catalyst for business transformation.
Why has your business invested in observability or monitoring tools?
Typical answer: “To improve our Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR) when incidents or problems occur.”
Worrying answer: “We haven’t yet...”
I completely understand where this thinking comes from. For years, vendors have focused on performance improvements—reducing downtime by 20–30%, making applications run better. Those results are real and, very importantly, measurable. In fact, across Global 2000 companies, we’ve seen a 53% reduction in application and infrastructure downtime when organizations invested in building a leading observability practice. *
But today, there’s a more powerful reason to invest: observability is a strategic enabler of growth, agility, and innovation—especially in the era of AI which is forcing every organisation to rethink how they operate. Banks are providing AI assistants to their employees to augment their daily work, restaurant chains are launching AI-powered drive-throughs, electric cars are increasingly becoming data centers on wheels, researchers and doctors are transforming patient care.
While the possibilities are endless, the path forward isn’t straight or clear. Unified Observability has a critical role to play for organizations to successfully figure out how to quickly adapt and invest in the future. Other organizations are likely to lose relevance.
It’s time to shift from seeing observability as a tool for reacting to problems to seeing it as a proactive foundation for business velocity.
Instead of looking for simplicity in a single product, look for platform advantage—a unified, correlated, and contextual view of all your data, no matter where it lives. This gives you a single robust version of the truth for faster, smarter decisions.
Start with the data. Your tech stack likely includes between 23 and 50 monitoring tools—just for IT.**
Now add in OT and IoT. It’s no surprise clarity is hard to achieve when these tools all sit in silos.
Persona-specific tools can still exist, but everyone should work from a consistent, correlated dataset that spans IT, OT, IoT, and beyond.
Think about your value chain—the end-to-end processes that deliver customer outcomes. Each process is powered by people, technology, and critical user journeys. Observability optimizes these component parts—making them faster, more efficient, more intelligent. When every part performs at its best, your business does too.
With that insight, you can:
There is no one-size-fits-all path. Your organization’s maturity across people, processes, and tools will shape your observability journey.
Start by defining your end vision—Not just a technology vision but a vision of how technology will support business goals and drive growth. Then work backward to identify today’s most pressing gaps.
Often, the first step is simpler than you think.
For example: A European bank ran an observability maturity assessment with one of our partners. They found 49 gaps. Of those, 40 were technology-related—and 35 of those capabilities already existed within our solution. The remaining 5 were on our roadmap, the rest related to people and process maturity.
So, in conclusion:
*Source: The Hidden Cost of Downtime, Oxford Economics / Splunk, 2023
**Source: State of Observability, Splunk, 2024
1 Gartner Report, Key Functional Considerations to Define Your Observability Platform, by Martin Caren, Gregg Siegfried, Matt Crossley, Mrudula Bangera. Jan 2025
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