Buy vs Build: FinOps and CMPs for SaaS CXOs
SaaS leaders face a recurring choice for cloud cost and security governance. Build a custom cloud FinOps for SaaS on top of cloud provider tools, or adopt a third-party Cloud Management Platform. Practitioner experience shows that internal builds look attractive at first, then stall under scale, maintenance, and adoption pressure. For most mid to large SaaS companies operating across regions and clouds, a neutral platform is the faster, lower risk path to sustained outcomes.
Why DIY on native cloud tools breaks down
Drawing on the practitioner points you shared:
1. Vendor bias
Cloud provider consoles are designed to keep you inside one ecosystem. They help, but they are not neutral advisors across providers or services.
2. Slow functional evolution
Native cost pages and basic recommendations improve incrementally. Enterprise needs such as granular allocation, richer forecasting, policy automation, and cross-cloud normalisation outpace those updates.
3. Hidden total cost
“Free” internal solutions are not free. You fund ingestion pipelines, data modelling, warehousing, dashboard development, testing, upgrades, and on-call. You duplicate this effort per provider.
4. Role drift
FinOps practitioners become de facto software engineers. Time spent building pipelines is time not spent changing spend behaviours with product and platform teams.
5. Value density of third-party tools
A competitive market compresses price for capability. You gain features that would take months to build, plus product roadmaps you do not have to fund.
6. BI remains an option
If you need bespoke executive views, pull curated data from the platform into Power BI, Looker, or Tableau. You avoid owning the heavy lift while keeping presentation control.
7. Automation matters
Commercial tools increasingly ship workload scheduling, rightsizing workflows, commitment management, and policy guardrails that reduce toil and headcount load.
What a modern CMP delivers for SaaS
Multi-cloud visibility
A single view across AWS, Azure, and Google Cloud, with consistent dimensions for service, team, environment, and region. Useful for global companies operating in the USA, UK, EU, India, Canada, Australia, and beyond.
Allocation and unit economics
Business mapping to products, customers, features, and cost centers. Report cost per transaction, per workspace, or per tenant, not just per subscription.
Budgets, forecasts, and variance
Rolling forecasts tied to real usage, with alerts on trend breaks so finance and engineering act before month end.
Actionable optimisation
Rightsizing, idle resource cleanup, pricing plan improvements, and commitment coverage workflows that route to owners and track realised savings.
Security posture with cost context
Posture and configuration findings sit next to spend so leaders weigh cost and risk together, rather than chasing the cheapest option that weakens controls.
License analytics for SaaS suites
For Microsoft 365, surface inactive and unassigned licenses, model safe downgrades, and track reclaim outcomes across business units.
Automation and guardrails
Policies to schedule non-production shutdowns, enforce tag standards, and prevent regressions. Approvals where required, automation where safe.
APIs and exports
Data access for downstream BI, data science, and chargeback systems, without rebuilding ingestion and normalisation.
A pragmatic build vs buy framework
1) Time to value
Can you surface owner-routed top savings and posture gaps in weeks, or will a build take quarters. Every month delayed carries real spend and risk.
2) Operating model fit
Will teams actually use it. Adoption comes from clear ownership, shared KPIs, and automation that removes toil, not from dashboards alone.
3) Total cost of ownership
Include engineering, data infrastructure, maintenance, security reviews, audits, and on-call. Compare that with a subscription plus measurable savings.
4) Risk and compliance
Consider regional data handling, audit trails, access controls, separation of duties, and the evidence you must present to customers and regulators.
5) Extensibility
Favour platforms with open schemas, exports, and webhooks so you can build the last mile without rebuilding the engine.
Market landscape, briefly
Well-known options include **Apptio Cloudability**, **VMware Tanzu CloudHealth**, and **Flexera Cloud Cost Management**. You will also see **Harness**, **Ternary**, **Kion**, **CloudBolt**, **Yotascale**, **Spot by NetApp** for automated compute efficiency, and **Kubecost** for Kubernetes cost allocation. Evaluate on data coverage, business mapping, automation depth, and evidence of realised savings.
90-day rollout plan for CXOs
Weeks 1–2: Connect and baseline
Connect cloud accounts and Microsoft 365. Establish a single taxonomy for tags, owners, products, and environments. Publish a first executive view with the top ten savings and top ten license reclaims by team and region.
Weeks 3–6: Operate the loop
Stand up budgets and variance alerts. Route rightsizing and idle cleanup to owners with due dates. Enable non-production schedules and commitment management. Share a weekly scorecard to finance, platform, and security.
Weeks 7–12: Scale and govern
Expand to anomaly detection, posture correlation, and policy guardrails. Export curated data to BI for any custom CFO or board views. Lock accountability by requiring a cost and security owner for every service.
The case for platforms over in-house builds
For global SaaS companies, the goal is not another internal system. The goal is faster, repeatable decisions that lower unit cost and reduce risk, without slowing delivery. Third-party platforms concentrate capability you would otherwise assemble yourself. They reduce bias toward one provider, shorten time to value, and let your FinOps and security leaders focus on behaviour change, not pipeline maintenance. If you have unique reporting needs, keep BI in the stack by pulling cleansed data from the platform. Build only where it differentiates your business.
Conclusion and examples
Selecting a neutral Cloud Management Platform is a strategic investment. It aligns finance, engineering, and security on a common language, accelerates optimisation, and supports multi-region governance. Treat native cloud consoles as inputs, not the system of record. Use a platform for ingestion, normalisation, analysis, and automation, then extend it with your BI and workflows.
As examples aligned to this approach, PowerBoard by Loves Cloud focuses on Azure estates for cost, security, and governance, and OfficeBoard by Loves Cloud focuses on Microsoft 365 license analytics and security posture. Loves Cloud supports CXOs with platform implementation and with operating model design so that tagging, ownership, budgeting, forecasting, and policy guardrails become weekly habits. If you require bespoke executive views, our teams expose curated data to your BI layer while the platforms handle ingestion, normalisation, and continuous optimisation.
Read more about these 2 products: