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FinOps for Data Center: Structuring Data Center Cost and Usage Data

This Paper is Part 3 of a FinOps for Data Center series outlining how applying FinOps Principles—focused on operational expenditure (OpEx), detailed cost attribution, and FinOps Framework Capability-driven practices—enables organizations to align Data Center investment with business value. By providing timely, accurate financial insights, FinOps empowers executive leadership to make more informed executive decisions.

The FinOps for Data Center Series

Why FinOps for Data Center

The Data Center is evolving from a passive cost center to a key enabler of business performance. FinOps provides a framework that allows organizations to:

  • Integrate financial oversight into strategic infrastructure planning.
  • Unify financial and operational visibility across multiple platforms.
  • Enable better decisions on multi-year planning, investments, risk, and scaling by executive stakeholders.

By adopting FinOps, organizations can shift from fragmented infrastructure reporting to a comprehensive, data-informed model that aligns cost transparency with strategic goals.

FinOps for Data Center

This document provides high-level, vendor-agnostic FinOps guidance for Data Centers, outlining the scope of FinOps practitioners’ roles, the application of the FinOps Framework, and relevant theoretical and practical considerations. While FOCUS™ is referenced, detailed data-level information will be addressed separately.

Who Should Read this Paper

This paper applies to FinOps practitioners who have been asked to manage technology spending that extends FinOps concepts beyond the scope of public cloud into Data Centers. Links to relevant material are contained in the Related FinOps Material section of the paper.

Prerequisites

An existing understanding of the FinOps Framework Domains and Capabilities for public cloud, along with being familiar with the content and concepts in Part 1: FinOps for Data Center – Context for Creating a FinOps Practice Profile, and Part 2: FinOps for Data Center – Applying the FinOps Framework.

Introduction and Purpose

A FinOps Scope refers to a segment of technology-related spending where FinOps Practitioners apply FinOps concepts. FinOps Scopes extend the Framework’s operating model to encompass intersecting areas of technology spend, particularly as the practice evolves to include activities in addition to public cloud.

According to the State of FinOps 2025 survey, 22% of practitioners are currently engaged in managing Data Center costs, with expectations rising to 36% by 2026—a 14% increase. These trends suggest that FinOps is increasingly being applied to broader areas of technology spending beyond public cloud services.

By collaborating with Core and Allied Personas, FinOps Practitioners may help shift organizational culture away from traditional finance, procurement, and technology silos toward a more integrated, data-driven approach that supports planning, cost analytics, and optimization.

The purpose of this paper is to explore the FinOps Scope for Data Center and to support existing FinOps Practitioners in understanding this area and the application of the FinOps Framework.

Data Center Definition & Characteristics

In the context of FinOps Scopes, “Data Center” is a broad term used to describe non-cloud IT services delivered from facilities either directly owned or managed by the client through contractual or service agreements. The Data Center scope includes all technology-related spending and decision-making activities associated with planning, acquiring, operating, and optimizing the physical and virtual infrastructure that supports an organization’s technology needs.

Read more about how a Data Center is defined for the purposes of this FinOps for Data Center series, the characteristics and special considerations related to private clouds — including approaches for the Data Center scope that could support the enhancement of traditional infrastructure management by applying FinOps principles to fixed-cost assets – in Part 1: FinOps for Data Center – Context for Creating a FinOps Practice Profile (LINK)

FOCUS™ for Data Center Overview

The FinOps Open Cost and Usage Specification (FOCUS™) is an open standard supported by the FinOps Foundation. It provides a consistent, detailed structure for cost and usage data across cloud, SaaS, Data Center, or any billed technology service.

By adopting FOCUS™-formatted datasets—whether from cloud providers or internal systems—organizations can apply FinOps practices more easily. The consistency of data structure reduces complexity, accelerates time to value, and simplifies tool adoption.

For Data Center owners, formatting internal cost and usage data to the FOCUS™ standard creates a unified view across the technology estate, enabling optimized decision-making for cost, usage, and performance.

FOCUS™ Enables Standardization and Scale Across Scopes:

  • Standardizes terminology for cost dimensions and usage metrics
  • Unifies KPIs and measurements, regardless of data source
  • Simplifies onboarding and integration of tools, dashboards, and automation
  • Eliminates normalization overhead, speeding time to insight and action
  • Streamlines ingestion and processing, improving data quality and trust
  • Enables consistent hiring and training, with common processes across teams, tools, and environments

FOCUS™: Proposed Column Mapping for Data Center Application

Here are some key elements of the FOCUS™ standard that are particularly useful for companies managing Data Center cost and usage:

Columns Key Considerations Usefulness for Data Center
Billed Cost assumption → SKU level. Organizations should consider how they would like Billed cost to incorporate other Data Center costs and how it would differ from List Cost. Additional costs could be added in here for Data Center allocation Considered
Billing Account ID Should be used as an index to identify the P&L organization owning a Data Center or set of Data Centers Considered
Billing Account Name Can be used for DC org naming purposes Considered
Billing Currency Represents the charge currency Considered
Billing Period End Based on the main assumption → FOCUS™ BillingPeriod should be evaluated while taking the right perspective on the adoption, if we think to put in shape an Opex approach, in order to represent the associated SKU estimation and allocation within the datacenter itself. Should be considered in the billing/amortization period of the Data Center itself. Considered
Billing Period Start Based on the main assumption  → FOCUS™ Considered
Charge Category Primarily Usage, as taxes, corrections are less likely in the Data Center Considered
Charge Description Text Optional
Charge Frequency Based on the main assumption  → FOCUS™ Considered
Charge Period Start When the usage occurs. Likely artificially batched for capital depreciated asset usage Considered
Charge Period End When the usage occurs. Likely artificially batched for capital depreciated asset usage Considered
Invoice Issuer Likely the name of the entity that owns or leases the Data Center Considered
Provider Likely  the company who owns or leases the Data Center, but could be an org leasing equipment in our Data Center Considered
Publisher Text, likely irrelevant, but could indicate where there are charges coming from entities selling through other Providers. Invoice Issuer, Provider and Publisher are used in conjunction to account for Marketplace purchases in Cloud use of FOCUS™, so consider these scenarios for Data Center usage. Considered
Sub Account ID Can be used as index to identify a group of services for DC, or an individual Data Center Optional
Sub Account Name Can be used to name group of services DC Optional
Contracted Cost If we are negotiating the cost of elements of our Data Center we may have values in here that differ from List Cost Optional
Effective Cost assumption → SKU level, if we are discounting, or accounting for variable discounts, or treating Depreciation as a “prepaid commitment” then Effective Cost may be reduced from List Cost. If not, this would be optional Optional/ Considered
List Cost Flat assumption Considered
Contracted Unit Price assumption → SKU level Considered
List Unit Price SKU Level reference Considered
Pricing Category This point is linked to the adoption model Considered
Pricing Quantity Linked to the above consideration Considered
Pricing Unit Linked to the above consideration Considered
Region ID Likely the physical Data Center ID (internal) Considered
Region Name Likely the physical Data Center Name (internal) Considered
Resource ID SKU index identifier within the DC Considered
Resource Name SKU name identifier within the DC Considered
Resource Type SKU representation level Considered
Tags Allocation/reporting/invoicing/chargeback Considered
SKU ID Adoption layer, This construct could be useful for defining a catalog of SKUs that a particular Data Center would charge for. Considered
SKU Meter Linked to above assumption Considered
SKU Price Details Linked to above assumption Considered
SKU Price ID Linked to above assumption Considered
Service Category Linked to layer assumption, cross-providers Considered
Service Name Linked to layer assumption, cross-providers Considered
Service Subcategory Linked to layer assumption, cross-providers Considered
Consumed Quantity Linked to SKU assumption Considered
Consumed Unit Linked to SKU assumption Considered

Proposed Excluded Columns:

  • Availability Zone,
  • Capacity Reservation ID,
  • Capacity Reservation Status,
  • Charge Class,
  • All ‘Commitment Discounts’

Note: The exclusion of Commitment Discount columns assumes that there are not similar types of discount or commitment constructs at work in the billing of Data Center services.

Suggested Missing Columns:

Missing columns are to be raised formally as a requirement into the FOCUS™ working group for formal discussion and progression where suitable.

  • Site ID/Name: If Region ID or Sub-Account ID are not used by the organization to identify the individual Data Center, then additional columns such as this may be required. Organizations should consider ways to normalize “location” treatment between their Cloud, SaaS and Data Center data to make normalized reporting queries work
  • Rack ID/Name: Location information within the Data Center
  • Asset Contract Number (reference for grouping setup/renewal waves): This would likely be a Tag
  • Asset Tiering Class (For classifying hardware usage): This would likely be a Tag
  • Linked_asset_id: consider assets which are reliant upon other assets. This could be a tag value, or could be usage related.
  • Depreciation: possibly captured in difference between Effective and List Cost metrics

Join the FOCUS™ Project

See Vendors Currently Supporting FOCUS™

FinOps KPIs for Data Center

This section offers a listing of FinOps KPIs for Data Center that could be used by all organizations, regardless of Data Center Hardware provider.

Note: While not specifically for Data Center, there are additional FinOps KPIs listed on the FinOps Foundation’s website, some of which may also be applicable to FinOps for Data Center – http://finops.org/wg/finops-kpis/

  • Calculate cost per business service across hybrid environments
  • Develop resource efficiency unit metrics (e.g., cost per GB stored, cost per virtual CPU)
  • Business unit metrics (e.g., cost per transaction, cost per tenant)
  • Measure and optimize Data Center energy efficiency (PUE)
  • Procurement: Key Metric: Procurement-to-Provisioning Lag Time
  • Commitment: Key Metric: Commitment Utilization Rate
  • CAPEX: Key Metrics: CAPEX ROI and OPEX Efficiency
  • Facility: Key Metric: Facility Efficiency = IT Equipment Power / Total Facility Power * update PUE
  • Optimization: Key Metric: Optimization ROI = (Cost Savings + Performance Gains) / Implementation Cost
  • Cost Integration: Key Metric: Integration Completeness = (Integrated Cost Sources) / (Total Cost Sources) × 100%
  • TCO: Key Metric: TCO per Workload = (Total Costs Over Lifecycle) / (Number of Workloads)
  • Operational Complexity: Key Metric: Operational Load Factor = (FTEs × Hourly Rate) / (Managed Infrastructure Value)
  • Sustainability: Key Metric: Sustainability Efficiency = (Workload Output) / (Environmental Impact) –
  • Key Metric: FinOps Culture Index = (FinOps Initiatives Adopted) / (Total FinOps Opportunities) × 100
  • Waste: Key Metric: Efficiency KPI = ($ amount of potential savings from identified Waste) / (Total IT Cost in a certain scope)
  • Hybrid solutions: Key Metric: Hybrid Cost Efficiency = (Total Business Value) / (Combined Infrastructure Costs)
  • Automation ROI: Key Metric: Automation ROI = (Cost Savings + Efficiency Gains) / (Implementation Cost)

Acknowledgments

We’d like to thank the following people for their hard work on this Paper: