--- title: Insights — Matter + Energy | ITFM, FinOps & AI Governance description: Perspectives and research on ITFM, FinOps, AI governance, and federal procurement, and on making technology investments defensible. image: https://www.matternenergy.com/hubfs/matter-energy/og-default.jpg --- [![Matter + Energy home](https://www.matternenergy.com/hs-fs/hubfs/matter-energy/logo/me-logo-horizontal.png?width=273&height=32&name=me-logo-horizontal.png)](https://www.matternenergy.com/) - [Home ▾](https://www.matternenergy.com/) [Who we are](https://www.matternenergy.com/company) [Technology Ecosystem](https://www.matternenergy.com/technology-ecosystem) [Teaming & Partnerships](https://www.matternenergy.com/teaming) - Solutions ▾ [Overview](https://www.matternenergy.com/solutions) [Technology Value Management](https://www.matternenergy.com/it-financial-management) [AI Adoption & Productivity](https://www.matternenergy.com/solutions/ai-adoption-productivity) - Services ▾ [Our Approach](https://www.matternenergy.com/services) [Maturity Assessment](https://www.matternenergy.com/services/maturity-assessment) [Proof of Value](https://www.matternenergy.com/services/proof-of-value) [Integration & Data Architecture](https://www.matternenergy.com/services/integration-data-architecture) [Retained Operations](https://www.matternenergy.com/services/retained-operations) - Government ▾ [Federal Capabilities](https://www.matternenergy.com/government) [Commercial Solutions Openings (CSO)](https://www.matternenergy.com/government/commercial-solutions-offerings) [OTA & Rapid Prototyping](https://www.matternenergy.com/government/rapid-prototyping) [Solutioning as a Service™](https://www.matternenergy.com/solutioning-as-a-service) [Book a Lab Session](https://www.matternenergy.com/schedule-lab-sessions) - [Insights](https://www.matternenergy.com/insights) - [Events](https://www.matternenergy.com/events) [Schedule a Call](https://www.matternenergy.com/discovery) [![Matter + Energy home](https://www.matternenergy.com/hs-fs/hubfs/matter-energy/logo/me-logo-horizontal.png?width=205&height=24&name=me-logo-horizontal.png)](https://www.matternenergy.com/) Home ▾ [Home](https://www.matternenergy.com/) [Who we are](https://www.matternenergy.com/company) [Technology Ecosystem](https://www.matternenergy.com/technology-ecosystem) [Teaming & Partnerships](https://www.matternenergy.com/teaming) Solutions ▾ [Overview](https://www.matternenergy.com/solutions) [Technology Value Management](https://www.matternenergy.com/it-financial-management) [AI Adoption & Productivity](https://www.matternenergy.com/solutions/ai-adoption-productivity) Services ▾ [Our Approach](https://www.matternenergy.com/services) [Maturity Assessment](https://www.matternenergy.com/services/maturity-assessment) [Proof of Value](https://www.matternenergy.com/services/proof-of-value) [Integration & Data Architecture](https://www.matternenergy.com/services/integration-data-architecture) [Retained Operations](https://www.matternenergy.com/services/retained-operations) Government ▾ [Federal Capabilities](https://www.matternenergy.com/government) [Commercial Solutions Openings (CSO)](https://www.matternenergy.com/government/commercial-solutions-offerings) [OTA & Rapid Prototyping](https://www.matternenergy.com/government/rapid-prototyping) [Solutioning as a Service™](https://www.matternenergy.com/solutioning-as-a-service) [Book a Lab Session](https://www.matternenergy.com/schedule-lab-sessions) [Insights](https://www.matternenergy.com/insights) [Events](https://www.matternenergy.com/events) [Schedule a Call](https://www.matternenergy.com/discovery) Insights # What we know about the problems *you're working on.* Perspectives on Technology Value Management, AI adoption, federal procurement, and the intersection of cost intelligence and measurable outcomes — written for practitioners and leaders who need substance, not filler. [Perspectives](https://www.matternenergy.com/insights#perspectives) [Industry Case Studies](https://www.matternenergy.com/insights#case-studies) [Resources](https://www.matternenergy.com/insights#resources) Topics We Cover ITFM & FinOps AI Governance Federal Procurement OTA & Prototyping Cost Transparency Technology ROI Agentic AI Enterprise AI TBM & ITFM OMB & FITARA NIST AI RMF Cloud Cost Governance Planning & Forecasting AI Adoption Maturity Models Automation SDLC Acceleration CSO Authority Written by Practitioners Working Arguments, Not Trend Pieces FinOps Starts With the Cost Model AI Governance Is an Accountability Problem Why AI Pilots Don't Scale OTA and CSO Authority, Explained What FITARA Scores Miss Automation Without AI, When It Fits Written by Practitioners Working Arguments, Not Trend Pieces FinOps Starts With the Cost Model AI Governance Is an Accountability Problem Why AI Pilots Don't Scale OTA and CSO Authority, Explained What FITARA Scores Miss Automation Without AI, When It Fits Perspectives ## Written by practitioners. *For people doing the work.* These are not trend pieces. They are working arguments about problems we encounter repeatedly — on cost modeling, AI governance, federal acquisition, and the operational discipline that separates programs that deliver from programs that report. ![](https://www.matternenergy.com/hs-fs/hubfs/matter-energy/website-insights.jpg?width=1920&height=1080&name=website-insights.jpg) Featured ITFM · FinOps 6 min read ## The Allocation Model Problem: Why Most FinOps Programs Fail Before They Start Organizations invest in FinOps tooling and then discover the real problem was never the tool — it was the cost model underneath it. A look at what actually separates programs that produce defensible numbers from ones that produce reports nobody trusts. [Read the piece](https://www.matternenergy.com/insights/allocation-model-problem) ### [5 min read AI Governance The Governance Gap Is Not a Technology Problem Only 16% of AI initiatives have scaled enterprise-wide, according to CEOs surveyed by IBM. The technical capability exists. The models work. What's missing is the accountability infrastructure that makes deployment defensible to leadership, auditors, and oversight bodies. Read the piece](https://www.matternenergy.com/insights/governance-gap) ### [7 min read Federal Acquisition OTA Prototype Authority: What Program Managers Get Wrong OTA is often treated as a contracting workaround. It's a congressionally designed acquisition authority for the kind of commercial AI and software capabilities agencies are trying to deploy now. Read the piece](https://www.matternenergy.com/insights/ota-what-program-managers-get-wrong) ### [4 min read Strategy The Best Solution Is the One That Fits the Problem Not the most sophisticated solution we know how to build. Not the simplest one we can justify billing for. The calibration between those two poles is where most technology programs succeed or fail before a line of configuration is written. Read the piece](https://www.matternenergy.com/insights/best-solution-fits-the-problem) ### [5 min read ITFM · Federal What the FITARA Scorecard Measures — and What It Misses Federal agencies have spent years chasing FITARA grades. The scorecard measures CIO authority, data center consolidation, and cyber hygiene. It does not measure whether leadership can answer a basic question: what does our technology portfolio actually cost? Read the piece](https://www.matternenergy.com/insights/fitara-scorecard-what-it-misses) ### [4 min read Automation · AI Automation Without AI: The Case for Keeping It Simple When Simple Works Not every automation problem needs an AI component. Some of the highest-value workflow improvements are built on rule-based logic and conditional routing — no model required. The compulsion to add AI where it isn't needed is its own form of gold-plating. Read the piece](https://www.matternenergy.com/insights/automation-without-ai) ### [6 min read AI Adoption · Federal Why AI Pilots Don't Scale: The Program Management Argument The AI scaling gap isn't a model problem. It isn't a data problem. It is almost entirely a program management, organizational design, and governance problem — and the fix doesn't start with the technology. Read the piece](https://www.matternenergy.com/insights/ai-pilots-dont-scale) Industry Case Studies & Technology Outcomes ## What this class of work *produces.* These examples come from case studies published by the technology providers whose platforms Matter + Energy implements. They show what this class of work can produce; they are not Matter + Energy engagements. Our own case studies will be published as engagements complete and clients approve them. ITFM · TBM DoD Combatant Command ### From Spreadsheets to a Single Source of Truth *for a $20B IT Portfolio* A global warfighting command managing over $20 billion in IT assets and 90 mission-critical services had no defensible cost model. In the final two quarters of each fiscal year, service managers spent 10–20 hours a week preparing for budget reviews. Unplanned, unfunded resource requests averaged about $5 million a year. The command implemented TBM-standard cost modeling and IT financial management tooling to create a single authoritative source for all financial planning and execution data. Budget review prep reduced from days to a few hours per cycle Monthly and annual leadership reviews shortened from two weeks to three days Budget variance reduced 20–30% with real-time obligation tracking Engineering time redirected from reporting to mission delivery Source: [IBM Apptio case study](https://www.apptio.com/case-study/governmental-command-adopts-tbm-to-promote-organizational-and-cultural-change/) [Discuss a similar engagement](https://www.matternenergy.com/contact) ITFM · TBM Federal Civilian Agency ### TBM for Refresh Planning *and Cloud Cost Tracking* A federal agency managing more than 100,000 end-user devices across 2,000 locations needed to forecast technology refresh and track cloud migration costs. TBM taxonomy implementation gave Finance and IT a common language and automated previously manual reporting. 95% reduction in time spent on asset refresh monitoring and reporting Real-time cost monitoring across 100+ cloud-migrated applications TBM taxonomy reporting automated through operational processes TBM taxonomy used for active investment decision support Source: [IBM Apptio case study](https://www.apptio.com/case-study/governmental-agency-uses-tbm-to-accelerate-business-agility/) [Discuss a similar engagement](https://www.matternenergy.com/contact) AI Adoption · Agentic Automation IBM (internal deployment) ### Agentic AI Deployed at Scale *Across the Enterprise Workforce* IBM deployed an agentic AI assistant across its workforce to handle employee requests and route work that previously needed human coordination. 300,000+ monthly automated interactions at steady state 16,000+ hours of employee time saved 73% workforce adoption — sustained, not just launched Source: [IBM product blog (AskIBM)](https://www.ibm.com/new/product-blog/turning-data-and-ai-agents-into-trusted-outcomes-with-watsonx-data-and-orchestrate) [Discuss a similar engagement](https://www.matternenergy.com/contact) AI Governance · Agentic AI Infosys ### Governing 2,700+ AI Use Cases *Without Slowing Deployment Velocity* Infosys, scaling AI across functions and geographies, deployed AI governance tooling as infrastructure rather than a compliance overlay, with lifecycle monitoring and policy enforcement built in. 150% increase in operational efficiency across AI-governed workflows 2,700+ AI use cases processed with consistent governance controls Governance deployed as infrastructure, not post-deployment retrofit Source: [IBM case study, Infosys](https://www.ibm.com/case-studies/infosys) [Discuss a similar engagement](https://www.matternenergy.com/contact) Resources ## Curated research from the sources *that inform how we work.* These are the frameworks, reports, and reference materials we return to — from standards bodies, government oversight agencies, and research organizations. Each one is annotated with why it matters and what it means for the problems our clients are solving. ITFM & FinOps ### [TBM Council ITFM · Cost Modeling · Standard Technology Business Management Standard The foundational taxonomy for IT cost modeling — defining towers, cost pools, and allocation logic. Matter + Energy's ITFM methodology is built directly from this standard. If you're evaluating any ITFM platform or cost model design, this is the reference framework everything else is measured against. View Standard](https://www.tbmcouncil.org) ### [FinOps Foundation FinOps · Cloud Cost Governance · Maturity Model FinOps Framework & Maturity Model The industry standard for cloud financial management — phases, capabilities, and the maturity criteria that distinguish crawl from run. Essential reference before any cloud cost governance initiative. The maturity model is particularly useful for diagnosing where an organization is before deciding what to build next. View Framework](https://www.finops.org/framework/) ### [OMB ITFM · Federal · Budget Formulation Circular A-11: Budget Preparation, Submission and Execution The governing document for federal IT budget formulation. Appendix I covers IT capital planning and investment control requirements. Any federal ITFM program must be legible to A-11 — cost models that can't map to program elements and appropriation categories won't survive OMB or IG review. View Circular](https://www.whitehouse.gov/omb/information-for-agencies/circulars/) AI Governance & Adoption ### [NIST AI Governance · Risk Management · Framework AI Risk Management Framework (AI RMF 1.0) NIST's framework for identifying, assessing, and managing AI risk across the development and deployment lifecycle. The de facto governance reference for federal AI programs — and an increasing number of enterprise deployments. The four core functions (Govern, Map, Measure, Manage) provide the accountability structure that most organizations are missing when AI pilots stall. Download Framework](https://www.nist.gov/news-events/events/2023/01/nist-ai-risk-management-framework-ai-rmf-10-launch) ### [IBM Institute for Business Value AI Adoption · Enterprise · Research CEO Study: The Enterprise Guide to AI Agents IBM IBV research tracking enterprise AI adoption across thousands of organizations globally. The source for the finding that CEOs report only 16% of their AI initiatives have scaled enterprise-wide. Read alongside IBM's governance research, it points to governance maturity as a major factor in which organizations scale AI. Read Research](https://www.ibm.com/thought-leadership/institute-business-value) Federal Acquisition & Oversight ### [GAO Federal IT · Oversight · High Risk High-Risk Series: IT Acquisitions and Operations GAO's ongoing assessment of the federal government's highest-risk programs. IT acquisition and operations has appeared on this list every cycle since 2015. The diagnostic framework identifies exactly where federal technology programs break down — requirements definition, cost estimation, schedule management, and contractor oversight. The patterns are consistent. The solutions are not simple. View Series](https://www.gao.gov/highrisk) ### [DoD OTA · Prototyping · Acquisition DoD Guide to Other Transactions (2023 Edition) The authoritative DoD reference for OTA prototype and production authority — eligibility requirements, participation structures, IP considerations, cost-sharing arrangements, and the follow-on production pathway. Essential reading for any program office considering OTA for a commercial technology or AI acquisition. Most misreadings of OTA authority that slow or derail programs are answered in this document. Download Guide](https://www.acq.osd.mil/asda/dpc/cp/policy/docs/guidebook/DoD%20OT%20Guide%20(July%202023)%20-%20508%20Update_11Jul2025.pdf) ### [McKinsey Global Institute Digital Transformation · Program Management Delivering Large-Scale IT Projects on Time, on Budget, and on Value McKinsey and the University of Oxford's study of more than 5,400 IT projects: large projects ran 45% over budget and delivered 56% less value than predicted. The analysis identifies the distinguishing factors: scope discipline, executive sponsorship, agile execution, and — critically — the decision to measure value delivery against outcomes, not milestones. The gap between what programs report and what they deliver is the central problem this research quantifies. Read Research](https://www.mckinsey.com/~/media/McKinsey/dotcom/client_service/Corporate%20Finance/MoF/PDF%20issues/PDFs%20Issue%2045/Final/MoF45_LargeScaleIT.ashx) External resources are linked directly to their original sources. Matter + Energy does not reproduce copyrighted material. Annotations reflect our editorial interpretation of each source's relevance — not endorsement of all findings or positions. Links are verified periodically; if a link is broken, contact us and we'll update it. 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