Top 3 cloud financial management challenges
Introduction
As cloud costs continue to rise, comprising an ever-larger share of IT budgets, there is increasing executive scrutiny on demonstrating a return on investment from cloud spend. However, for many organizations, realizing the full business value of the cloud has been constrained by manual processes, limited data, and misaligned teams.
In this blog series, we will explore some of the key cloud financial management challenges and discuss potential technology solutions to help address these gaps. By taking an augmented approach that layers intelligent automation, comprehensive data, and cross-functional alignment on top of cloud FinOps foundations, organizations can break through barriers to maximize value.
Read our in-depth guide to learn best practices for cloud financial management.
Challenge # 1: Manual Processes
A significant finding from recent state of FinOps reports is that despite strong buy-in and prioritization of FinOps, much of the day-to-day operation remains manual. As FinOps analyst Tracy Woo of Forrester notes, “the business impact of FinOps is constrained today by toilsome, episodic human activity.”
This reliance on manual workflows and processes – whether in governance policy implementation, optimization, or reporting – severely reduces speed to action and diminishes the value of any insights uncovered. As Woo states, “every second that passes from insight to action diminishes relevance and value.”
Potential technology solutions:
- Process automation using RPA and integration tools to streamline FinOps workflows
- Self-learning optimization agents that can take autonomous actions to right-size resources
- Real-time data pipelines and alerts that trigger immediate review and prevention of waste
By leveraging automation, organizations can accelerate the impact of FinOps, translating insights into outcomes within seconds rather than months.
Challenge #2: Limited Data
Another clear gap limiting FinOps success is data, with analysis and recommendations often constrained to the narrow domain of cloud infrastructure spend. Without incorporating broader data sources such as on-premises, SaaS, and custom business metrics, the insights are restricted.
“Finops has been starved of much of the data dimensionality necessary to deliver intelligent insight and action,” says Kyle Campos, CPO of CloudBolt. “Bespoke, isolated data streams continue to generate naive recommendations with low business impact.”
Potential technology solutions:
- Ingestion of expanded data sources (on-prem, SaaS, etc.) via standards like FinOps FOCUS
- Leveraging AI/ML for complex pattern recognition and analysis
- Providing a comprehensive, unified data set for accurate decision-making
With a complete picture of spend and utilization across all IT domains, FinOps can evolve from reactive cost management to proactive value optimization.
Challenge #3: Misaligned Goals Across Teams
Finally, organizational misalignments between finance and engineering teams continue to limit FinOps success. Without shared incentives or common data-driven risk models, the impact of FinOps rarely extends beyond finance.
“There is a lack of shared language and incentives between finance and engineering,” Woo explains. “They are still locally optimizing within their own context rather than facilitating outcomes, leading to tension and poor adoption.”
Potential technology solutions:
- Unified platforms enabling cross-team collaboration and shared ownership
- Transparent AI optimization models aligned to business objectives
- Democratized self-service access to FinOps data and tooling
Creating joint understanding and ownership of cloud investments powered by enabling technologies can transform this dynamic to maximize results.
Conclusion
As the cloud becomes increasingly vital to IT strategies, the imperative to demonstrate value rises. We have highlighted three key problem areas constraining higher impact FinOps in most organizations today – manual processes, limited data, and misaligned teams. However, by taking an augmented approach leveraging automation, AI, and unified data to extend FinOps capabilities enterprise-wide, these barriers can be overcome to realize greater ROI.
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