27% of FinOps Practitioners Don’t Know FOCUS:
The 27% Nobody Talks About
Why more than a quarter of FinOps practitioners have never heard of the standard designed to solve their biggest problem, and what the data says about closing the gap.
By Sima Niaztalkhouncheh · MSc Data Analytics, BSBI / UCA · Supervised by Dr. Anuj Batta
In a recent mixed-method study of twenty-eight FinOps practitioners operating in Hybrid-IT environments, twenty-seven per cent had never heard of the FinOps Open Cost and Usage Specification (FOCUS). That is the very standard designed to solve the comparability problem they experience most acutely. This finding, drawn from a survey supplemented by five in-depth interviews with senior figures at the FinOps Foundation and across the enterprise community, sits at the heart of an MSc dissertation completed at BSBI (in partnership with the University for the Creative Arts) in July 2026. The awareness gap is not the whole story, but it is the single most important one. It deserves the attention of every FinOps team already grappling with mixed cloud and on-premises cost data.
The problem practitioners feel, but cannot name
Hybrid-IT is the dominant operating architecture of contemporary enterprise infrastructure. Eighty-nine per cent of the study’s respondents confirmed they operate in Hybrid-IT settings, aligning with the broader industry pattern that most organisations run cloud workloads alongside persistent on-premises systems. The financial governance of these environments faces a structural challenge: cloud cost data are generated continuously through native billing APIs, while on-premises cost data emerge episodically through capital expenditure cycles, depreciation schedules, and asset management processes. Comparing the two within a single analytical frame is operationally difficult, and every practitioner surveyed acknowledged this.
What emerged from the data was striking. Respondents who had never heard of FOCUS reported the strongest agreement that comparing cloud and on-premises cost data is difficult, with a mean Likert score of 4.00 out of 5.00. This was higher than any other awareness group. The people most acutely aware of the problem are the least likely to know the solution exists.
This pattern is not a statistical curiosity. It is a diffusion gap. FOCUS, developed under the auspices of the FinOps Foundation, provides a common schema for cost and usage data across cloud providers, and its extensions increasingly reach into the on-premises domain. Yet the practitioners for whom FOCUS was designed are, in a substantial minority of cases, entirely unaware of it.
The awareness gradient, a statistically significant pattern
The study asked practitioners two related questions: whether they had heard of FOCUS, and whether they believed a standardised cost data schema would significantly improve their cost management. The responses aligned along a monotonic gradient. Practitioners who had adopted FOCUS reported the strongest belief in its value, with a mean of 4.33 out of 5.00. Those planning to adopt it reported 4.00. Those who had heard of it but had no plans reported 3.20. And those who had never heard of it, the largest single group, reported 3.29, essentially neutral.
A Spearman rank-order correlation between awareness position and belief in FOCUS value produced a coefficient of 0.535 with a p-value of 0.005. This is a large effect by Cohen’s (1988) conventions, and the strongest single inferential finding of the survey phase. The relationship is not a coincidence. Familiarity with FOCUS drives conviction in its value, and the reverse also holds: those who have not encountered FOCUS default to a non-committal position, not because they oppose it, but because they have no basis for evaluating it.
In practical terms, this reframes the adoption challenge. The barrier to FOCUS uptake is not resistance. It is exposure.
What the insiders said
The interview phase of the study included Beau Nelford, an architect of the FOCUS specification at the FinOps Foundation, and Rob Martin, the Foundation’s VP of Member Strategy and Education. Both were asked directly about the twenty-seven per cent finding.
“27% is far too low. I would have expected it to be higher. The community is still moving from asking ‘what is FOCUS?’ to asking ‘how does it support my data centre and my AI workloads?'”
Rob Martin, VP Member Strategy & Education, FinOps Foundation
Rob’s framing is important. His assessment was that awareness is trending in the right direction. Questions asked at Foundation events in 2024 were more foundational than those asked in 2026. But the community remains at an early stage of diffusion. Beau’s contribution reinforced this view from the specification side. He estimated that roughly one in five practitioners is now using FOCUS in production, a substantial improvement on earlier years, yet still leaving the vast majority of the addressable community outside the specification’s practical reach.
“This research is really well needed. There’s a gap between being aware of FOCUS and starting to use it, and that gap is where most of our community sits today.”
Beau Nelford, FOCUS architect, FinOps Foundation
A third interviewee, Victor Garcia, editor of FinOps Weekly, described the twenty-seven per cent figure as “surprisingly high” for the sector he covers. The convergence of these three perspectives, from inside the Foundation, from the specification, and from the community media, provides qualitative triangulation for the quantitative finding.
Why this matters for practitioners
The awareness gap has direct implications for organisations attempting to mature their FinOps capabilities. Three follow from the data.
First, internal FinOps education is under-invested. The most accessible improvement any FinOps team can make is to expose colleagues to the FOCUS specification, even at a superficial level. The study’s inferential result suggests that partial exposure measurably shifts perceived value. A one-hour internal briefing on what FOCUS is, what it standardises, and where it does not yet reach may generate more strategic value than another dashboard iteration.
Second, the awareness deficit is not neutral. It is asymmetrically distributed. The Hybrid-IT practitioners most acutely aware of the comparability problem are the least likely to know about FOCUS. This suggests that organisations facing the most acute analytical difficulties are the least equipped to name their own solution. Executive-level FinOps leaders in Hybrid-IT contexts may benefit from a deliberate audit of internal awareness before commissioning technical solutions to problems that FOCUS already addresses.
Third, the study’s evidence supports a straightforward strategic recommendation for the FinOps Foundation. Education is doing what technical development alone cannot. The specification exists. The tooling is emerging. What remains is diffusion. The relationship between awareness and conviction is now empirically documented. Every additional practitioner who encounters FOCUS becomes, on average, a more convinced advocate for it.
What comes next
The full dissertation, of which this article summarises a single finding, is openly available on Zenodo. Three additional strands of the same research merit their own treatment: the trust-led cluster of barriers to Machine Learning adoption in FinOps, the empirical relationship between data quality and ML uptake, and the practical extension of FOCUS to on-premises environments through hypervisor-level sampling. Each of these is being prepared as a separate practitioner-facing article.
The twenty-seven per cent figure will not close itself. It requires the sustained diffusion work that the FinOps Foundation, its Ambassadors, and its practitioner community are already undertaking. What this research contributes is empirical confirmation that the effort is worth it, and a measurable target against which progress can be assessed. If the same survey were repeated in eighteen months and the figure moved to twenty per cent, that would be a real shift in the state of the practice. If it moved to fifteen per cent, it would be a transformation.
The gap is nameable. The gap is measurable. And the gap is closable.
About this research
This article summarises one finding from Sima Niaztalkhouncheh’s MSc dissertation, “Developing a Data-Driven FinOps Framework for Automated Cloud Cost Allocation and Variance Analysis in Hybrid-IT Environments using Machine Learning”, supervised by Dr. Anuj Batta and submitted at BSBI (Berlin School of Business and Innovation) in partnership with the University for the Creative Arts (UCA) in July 2026. The empirical work comprised a Machine Learning experiment on FOCUS-aligned Hybrid-IT data, an online survey of twenty-eight FinOps practitioners, and five semi-structured interviews with senior practitioners and standard-setters. The full dissertation is available at https://doi.org/10.5281/zenodo.21359671.
The author is currently based in Berlin, focusing on FinOps practice and open to collaboration.
