Enterprises are leaning into finops systems to cut costs. However, if that’s the only metric, you could derail the overall business benefit of cloud computing. The rise of finops programs and tools is scaring me a little. I believe that many enterprises are misapplying them, and in many instances, finops technology is working against returning value to the business. Some people driving finops don’t even understand that they are being counterproductive. If left unchecked, many of these misguided finops programs could end up doing real damage. To be sure, many enterprises do find the cloud cost savings they are seeking these days. However, their finops programs are also having a negative effect on the business. How does this happen? Here is the core reality around how cloud computing drives business value. Saving cloud costs, such as reducing the number of resources and optimizing each resource, has a net savings on operational costs, but there also needs to be a focus on something that many don’t consider: The effect of value returned to business, which is not necessarily in sync with saving operational dollars. We’ve all heard the saying, “penny-wise and pound-foolish.” Saving money, while generally a good thing, may have a net negative effect on the core business, specifically driving value. As an example, let’s imagine a healthcare tech company. The team driving a new finops program talks about their ability to “manage cloud spending better.” This includes only allowing very specific cloud storage systems, where a good price was pre-negotiated, and limiting cloud resources to set allocations in each period. The company realizes net savings of about 30% to support the same number of applications and databases. Good, right? Unfortunately, our fictitious company found that they missed several market opportunities, such as building net-new applications to support a new health trend that leverages data from your last blood test to create a nutrition plan customized to your specific physiology, using huge amounts of biomedical data and a generative AI system. (I’m making this up, in case you want this.) The company discovered that those charged with creating new products were so limited by the choices of AI systems, storage and compute spending, and databases that building a new product to capitalize on this trend was difficult. Rather than push back on the limitations imposed by the new finops technology and processes, it was easier just to do nothing. This might be an extreme example, but the message is clear: Using cost savings as your only finops metric is a bad idea, but too many enterprises are doing exactly that. This is because of its simplicity and the fact that only a few finops systems consider value creation as a metric. Most focus on operational cost savings and cloud usage optimization and typically ignore value because it’s difficult to define and even harder to prove. But, if you don’t have the ability to consider the trade-off between value creation and cost savings, you’re going to indeed be “penny-wise and pound-foolish.” It can be done. When you set up any finops system, establish business value creation as your objective, and don’t focus just on cost savings. Yes, smart management of cloud spending can create more value; for instance, the ability to do the same or more with less often has a positive effect on business value. However, companies need processes that evaluate all activities that are likely to create value, and they need other metrics that consider risk/reward and the ability to drive innovation and creativity. This is not easy. It takes some creative metrics modeling to come up with the correct way to consider cloud spending using something that’s dynamic and not static. However, if your cloud finops systems don’t consider all the impacts on the business, you’re likely to be very successful with cost savings, but you’ll kill your business at the same time. Related content analysis Azure AI Foundry tools for changes in AI applications Microsoft’s launch of Azure AI Foundry at Ignite 2024 signals a welcome shift from chatbots to agents and to using AI for business process automation. By Simon Bisson Nov 20, 2024 7 mins Microsoft Azure Generative AI Development Tools analysis Succeeding with observability in the cloud Cloud observability practices are complex—just like the cloud deployments they seek to understand. The insights observability offers make it a challenge worth tackling. 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