Technology Economics: The Future of ITFM and FinOps
Technology Economics: The Future of ITFM and FinOps
We built MagicOrange because the problem was real and the existing tools were not good enough. That has not changed. What has changed is the scale of the opportunity.
When we founded MagicOrange, the pitch was simple: enterprises were spending enormous sums on technology with minimal visibility into what that spend was actually delivering. The tools that existed either forced organisations into rigid taxonomies that did not reflect how they actually operated, or produced reports so slow that by the time the numbers arrived, the decisions had already been made.
We believed we could build something better. A platform that was genuinely flexible, that could ingest messy, incomplete data and still produce a clean, auditable cost model. That could adapt to the way organisations actually operate. That could sit inside the Microsoft ecosystem and work with the reporting tools finance teams already trusted.
My background is in management accounting and financial systems. I spent years at Credit Suisse and Morgan Stanley watching how financial institutions tried to make sense of their technology spend, and later at Keyrus working with enterprises across industries on performance management. The pattern was consistent: the ambition was there, the data existed, and the tools were the bottleneck.
MagicOrange was built to remove that bottleneck.
Joining the FinOps Foundation Governing Board is a milestone that reflects how far the platform and the discipline have come.
When we started, ITFM and FinOps were largely separate conversations. Today they are converging, and that convergence is being accelerated by AI.
AI is the most significant product challenge and opportunity we have faced. It is not simply another cost category to track. It introduces a fundamentally different economic model: consumption-based, highly variable, difficult to attribute, and expanding across every business function simultaneously. The question our customers are asking is not just how do we see our AI spend. It is how do we connect AI investment to business outcomes, govern it across teams, and make decisions in real time rather than waiting for the month-end report.
Greg Guye is the Co-Founder and Chief Product Officer at MagicOrange, an enterprise financial management platform focused on IT Financial Management, FinOps, cost allocation and technology cost transparency. He has extensive experience across financial services, consulting, performance management, and enterprise technology cost management. He previously held senior roles at Credit Suisse and Morgan Stanley, and served as CEO of Keyrus, a global performance management consultancy.
Those are product problems. And they are ones we have been building toward.
Our platform today combines ITFM, FinOps, and what we are calling Technology Economics: the discipline of connecting technology investments, including cloud, AI, SaaS, infrastructure, and people costs, directly to business outcomes and economic value.
This means bringing together cloud costs, AI consumption, SaaS licensing, on-premise infrastructure, and people costs into a single, coherent model. As enterprises accelerate AI adoption, understanding what technology costs is no longer enough. Leaders increasingly need to understand what those investments deliver, how they influence business performance, where to optimise future investment, and how technology contributes to overall business value.
Running that model on highly optimised architecture, with Databricks at the core, enables organisations to analyse complex technology and business datasets at enterprise scale. Our partnership with Databricks is an important part of this journey, bringing together large-scale data processing, AI capabilities, and financial governance to help organisations manage the economics of technology in an increasingly AI-driven world. This also enables organisations to better understand the unit economics of technology consumption, from cloud and AI services through to SaaS, infrastructure, and workforce investments.
While reporting remains important, we believe the future extends beyond dashboards. Enterprises increasingly need role-based AI agents that understand the context of different stakeholders and proactively deliver insights, recommendations, and actions. Moving from static reporting to intelligent agents allows finance leaders, technology executives, product owners, and business managers to engage with technology economics in a way that is directly relevant to their responsibilities, objectives, and decisions.
The next generation of Technology Economics is not just about seeing the data. It is about helping organisations make better decisions, faster, through intelligent, contextual guidance that connects technology investment to measurable business outcomes.
The FinOps Foundation Governing Board includes enterprise practitioners from some of the most sophisticated technology organisations in the world. Being part of that community means our product roadmap is informed by the practitioners who are solving these problems at scale and helps ensure that MagicOrange remains aligned to the evolving needs of the industry.
At FinOps X in San Diego in June, we will be showing what the next generation of Technology Economics looks like in practice. If you are a practitioner, a technology leader, or someone building the financial governance framework for your organisation’s AI journey, we would love to hear from you.
This is the problem we came to solve. The scale of it has grown considerably. So has our ability to address it.
Greg Guye | CPO & Co-Founder, MagicOrange
MagicOrange has joined the FinOps Foundation Governing Board, helping shape the future of AI cost management and Technology Economics.
Read the full announcement: MagicOrange Joins the FinOps Foundation Governing Board
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