Cost Optimization & FinOps Assessment
BI Cloud Tech helps organizations explain Microsoft Cloud spend, identify safe savings, and build a repeatable FinOps operating model that protects performance, reliability, security, and delivery speed.
Can you explain every major cloud cost increase?
This assessment is for technology and finance leaders, Azure platform owners, FinOps practitioners, workload teams, and procurement stakeholders after rapid cloud growth, budget variance, an acquisition, migration, AI workload adoption, commitment renewal, or repeated surprise invoices. It is useful when spend cannot be allocated to owners, forecasts are unreliable, optimization recommendations remain unimplemented, or teams are unsure which savings are safe.
We review Microsoft Cost Management and billing scopes, management groups, subscriptions, resource groups, tags, budgets, anomaly and scheduled alerts, cost exports, cost allocation, Azure Advisor recommendations, reservations, Azure savings plans for compute, Azure Hybrid Benefit, Marketplace charges, storage and network growth, Kubernetes and platform costs, and selected Microsoft 365, Fabric, Power BI, or AI workload costs where data and ownership are available.
You receive a Cloud Cost and FinOps Assessment Report, spend baseline and trend analysis, ownership and allocation coverage scorecard, commitment utilization review, optimization opportunity register with estimated savings ranges, risk and dependency notes, and a 90-day FinOps roadmap. Sample findings may include unallocated shared services, missing tag inheritance, idle resources, oversized compute, low reservation or savings-plan utilization, unmanaged storage growth, cross-region egress, premium services without owners, or AI and analytics capacity that is not tied to business demand.
Our process
Turn cloud cost data into practical FinOps actions
We trace spend from billing scope and usage data to business owner, workload, environment, unit cost, optimization decision, and ongoing accountability. Recommendations are validated against availability, performance, security, licensing, and delivery requirements before they are prioritized.
Review cloud spend visibility
We review Cost Management scopes, billing hierarchy, subscription and resource organization, tags and tag inheritance, cost allocation, budgets, forecasts, anomaly and scheduled alerts, exports, dashboards, and showback or chargeback processes. The result shows which spend can and cannot be explained by owner, workload, environment, and business purpose.
Cost visibility
Identify cost drivers
We analyze trend and variance by service and owner, unused or underused resources, oversized compute, storage and network growth, Kubernetes, reservations and savings plans, licensing benefits, Marketplace charges, and selected data, Fabric, Power BI, and AI consumption. Each driver is tied to evidence and an accountable owner.
Cost drivers
Prioritize safe optimization
We separate quick wins from changes requiring architecture or workload testing. Recommendations may include rightsizing, scheduling, cleanup, storage tiering, commitment purchases, data-retention changes, license optimization, or architecture changes, with estimated savings ranges, confidence, risk, dependency, and owner.
Optimization
Build a FinOps roadmap
We define the operating cadence for allocation, forecasting, budget review, anomaly response, commitment management, optimization backlogs, unit-cost metrics, and executive reporting. The roadmap names owners, decision dates, dependencies, and the first 90 days of implementation.
FinOps roadmap
OUR WORK
Duration, inputs, and next steps
A focused assessment typically takes two to three weeks after billing access and scope are confirmed. Participants usually include a technology or finance sponsor, Azure platform owner, billing administrator, FinOps or procurement lead, workload owners, and operations representatives. Provide six to twelve months of cost and usage data, billing hierarchy, budgets, exports, reservation and savings-plan inventory, licensing agreements, architecture diagrams, tag standards, ownership mapping, forecasts, and read-only access or agreed exports. Follow-on work may include tagging and allocation remediation, commitment purchase planning, rightsizing implementation, cost dashboards, AI or Fabric capacity governance, a FinOps operating model, or ongoing optimization reviews.
