FinOps has come a long way, yet there’s a critical gap that many practitioners continue to overlook: the metrics we use to define and measure success.

Let’s address the elephant in the room. Most FinOps teams default to “cost reduction” as their primary success metric—tracking how much money they’ve saved over a given period. While this metric has its place, stopping there creates a significant blind spot. We’ve reached a point where the industry understands that FinOps isn’t solely about cutting costs. Consider a FinOps engineer who’s successfully driving cultural transformation within their organization; they might struggle to show traditional “savings,” yet their work is elevating the organization’s FinOps maturity in meaningful ways.

Rethinking Success: Beyond the Dollar Signs

So how do we tackle this challenge? We need to expand our measurement toolkit beyond pure cost impact.

Measuring cultural change isn’t easy, but it’s far from impossible. Here are some creative approaches:

  • Engagement metrics: Track the ratio of FinOps-initiated versus engineering-initiated tasks in your project management tools (like Jira).
  • Collaboration indicators: Compare how many design meetings you organize with engineering teams versus how many you’re invited to join.
  • Timing scores: Implement a scoring system based on when FinOps gets involved in feature development—with early-stage involvement (idea/design/roadmap) earning higher scores than post-deployment consultation.

The key is thinking creatively about what you measure and how it reflects your FinOps practice’s integration within your organization.

Measuring Operational Excellence

But what about the broader practice? Beyond tracking FinOps involvement, we need metrics that capture:

  • How quickly we identify inefficiencies
  • Our response time to open cases
  • How rapidly we adapt to organizational needs in the FinOps space
  • Our agility in embracing new technologies and demands

Engineering-Driven FinOps Metrics

From an engineering perspective, I propose these additional metrics for tracking FinOps performance over time:

TTA (Time to Automate)

How quickly can we transform manual processes into automated, scalable workflows? This includes reporting, cloud resource management, and responding to engineering queries. Manual work and operational overhead represent one of the biggest challenges for FinOps practitioners (I’m sure this resonates!). Too often, we find ourselves performing repetitive tasks—generating the same reports with different filters. In today’s AI-powered era, your FinOps maturity is reflected in how fast you can automate these tasks—not just identify them. That’s where platforms like Wiv come in.

TTR (Time to Resolution)

Once we identify an inefficiency, how quickly can we address it? This could involve automated remediation, establishing appropriate SLAs for engineering teams, or implementing alerts for policy violations. For instance, if a team has allocated a detached EBS volume, the TTR tracks how long it takes to resolve this inefficiency.

TTD (Time to Data)

How quickly can you access the specific data you need? Traditional BI platforms often fall short here, as the required information may not be readily available in standard cost reports. Consider this scenario: you need to identify all EKS cluster versions in production. How long would that take today? Whose assistance would you need?

The Wiv Approach

At Wiv, we’re addressing these challenges by democratizing automation, making it accessible to both technical and non-technical users. Our platform replaces the traditional cycle of “see insight, open ticket, wait for engineer” with a no-code automation engine that lets FinOps teams act immediately—without writing a line of code. Need to identify all your EKS versions? That’s a two-step workflow. Want to generate a report from that data? Just add another step. Want to open a Jira for the engineering teams? As simple as clicking a button.

We empower organizations to build and mature their FinOps practices while improving all the metrics mentioned above. Rather than just presenting data, we enable action. When you’re driving cultural change in your organization, these metrics become essential for demonstrating progress and engagement levels. The bottom line? Automation is no longer a nice-to-have—it’s the operational foundation for real FinOps maturity.