The Machines Behind the FinOps Curtain: Operationalizing Your Strategy with AI

FinOps is gaining steam, but companies shouldn’t just forge ahead. They should carefully consider their approach to FinOps. The tech—which garners most of the headlines—is only one ingredient. The amount of data cloud services generate is so complex that people and processes are just as important.

Think about what FinOps has to do:

The human brain can’t possibly do all of this. So, today’s typical human tools—manual processes and spreadsheets—are not up to the task.

So, what do you need to do FinOps right?

Integration: Cost management requires integration to discover shadow IT and evaluate usage across hundreds of SaaS apps, as well as private and public IaaS. Integration is crucial so you can understand, in granular detail, cloud usage. In turn, this helps put boundaries around spending and can track dynamic pricing. FinOps should work in synch with financial management systems and should be able to produce general ledger files.  

Real-time AI, ML, behavioral analytics (BA), and predictive analytics (PA): Handling all the data that the cloud produces means FinOps platforms must handle the cloud usage data that comes along for the ride. Multiple times a day, you’ll have to crunch expansive data sets, track dynamic pricing (which can change daily), and compare your service configurations to millions of other pricing schemas—all while normalizing cost data across multiple providers. AI, ML, BA, and PA can help with this task.

Cloud optimization and CEM working together: FinOps requires cloud service usage optimization and expense management to work in unison. Cloud optimization tools alone can only go so far. Yes, you need usage optimization tools that identify waste and unused resources, recommend lower-cost storage tiers, and help with rightsizing. But you also need an expense management platform to handle and automate invoice processing, cost allocations, and forecasting. And you need it all automated with a single-pane view, so you leave the manual headaches in the past.

Automated response (closed-loop automation): Insights are useless if you can’t act. FinOps solutions and tech platforms should generate more than recommendations. They should be integrated into IaaS service control panels so you can approve a recommendation and ensure the system makes suitable service modifications automatically, which speeds up the time to savings.

FinOps case study

How a tech research firm moved from manually managing the cloud to FinOps and started controlling multi-cloud infrastructure costs.

Talking about FinOps in the abstract is one thing. Seeing it at work is something else.

Senior IT and financial leaders at a technology research firm faced visibility, management, and cost control challenges after migrating much of the company's network infrastructure to the cloud. As their digital transformation matured, they found the cloud resource intensive.

Every month, IT financial analysts manually evaluated millions of dollars in expenses with little control over costs and invoice information. Analysts had to study tens of thousands of rows of billing information to decipher which departments were using each cloud service. Allocating each cost to its associated department was also a manual process. With roughly 500 departments, this administrative work had mushroomed into a full-time job for a larger group of employees. Because this work had become so laborious, finding the time to optimize costs seemed nearly impossible.

Gaining multi-cloud visibility and control in 30 days

The company had been using a third-party cloud optimization tool for several years. As a point solution, it could highlight ways to optimize costs but couldn’t automate IaaS financial management tasks. The company asked Tangoe to solve both problems, replacing the existing tool with one comprehensive FinOps solution for improved productivity and cost savings—and do it all in 30 days, just before their contract expired.

Using the Tangoe One Cloud for IaaS solution, expense management experts implemented a proof-of-concept that worked across Amazon Web Services, Microsoft Azure, as well as Google Cloud Platform to deliver what the existing tool could not:

Forty Hours of Manual Work Completed in Minutes

The company recognized productivity gains in both IT and financial departments. What used to take IT financial analysts an estimated 40 hours of manual work every week or month now happens in just minutes.

Today, company leaders have one complete solution giving them the peace of mind that comes from knowing their cloud investments are being utilized responsibly, and their spending is under control across their multi-cloud estate.

DIY might be fun at home, but for FinOps, it’s a mistake

Taking a DIY approach can be risky unless you can build all these tools in-house with homegrown systems.

You need a sophisticated technology platform behind your cost management program and team. Tangoe is one such system. I recently wrote a buyer’s guide titled, “What To Look For In A Cloud Expense Management Solution.” You can access it here.

Zeus Kerravala is the founder and principal analyst with ZK Research.

Read his other Network Computing articles here.

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