Why cloud spend management is hurting your productivity

Fewer contracts, but tons of administration and balancing growth vs optimization.

Matt Parsloe | MAR 20, 2024

8 min read

The cloud has enabled companies to expand their technological offerings and capabilities far beyond what they could before. But it’s a complex world, and requires near constant attention and administration to keep costs from spiraling. 

This is nearly all done manually by engineering teams. And given how important they are to modern businesses, how much is this hands-on approach to cost optimization hurting company productivity? Do the costs saved balance out the time spent away from growth-focused tasks?

What’s taking so much time?

Having undergone explosive growth, we discovered spend on cloud can range from 5 – 20% of a company’s budget (depending on its size). And to show the speed of its growth, 55% of companies are spending more on cloud year-on-year with 24% describing their upward spend as ‘significant’.

But does this growth necessarily mean extra administration? 

There are fewer contracts, for example – cloud products tend to be more ‘plug-and-play’ and are controlled by the engineering department, rather than spread across the whole company. This should help increase visibility, maintain cost control, and reduce administrative tasks. 

In theory. PluralSight found that more than 70% of organizations keep over half of their infrastructure in the cloud, and 44% adopt the latest cloud products as soon as they are available. That’s a lot of license administration to enable adoption and implementation – and this takes time to complete. 

We’ve also found that nearly a third (32%) of cloud spend can be better optimized- due to idle or underused cloud resources. This isn’t an indicator of inefficient working – no engineering team wants a bloated cloud environment! They are all too aware of the security risks and potential downtime this could cause.

Engineering teams would much rather focus their time on integrating new products, R&D, and ensuring that the cloud environment can scale as needed. So going back and constantly optimizing the cloud isn’t a high priority for them, especially given that they are usually overstretched and under-resourced in terms of staff and time.

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But I use Reserved Instances, these save time and money right?

Theoretically yes, they do. However the optimization of Reserved Instances (RIs) can require almost constant attention to predict and implement optimal usage at all times.

It’s a bit like managing electrical supply. You need to know when to supply more to meet demand, and to slacken it off, so you’re not wasting any. RIs work the same way. 

It’s the responsibility of DevOps, Engineering and their management teams to take this on. This can pull a lot of time, focus, and ultimately productivity away from revenue-driving operations. To properly optimize your RI’s, you need time dedicated to:

  • Understanding your current coverage
  • Managing your current RIs
  • Predicting what other RIs you will need, and when
  • Conducting manual optimization tests
  • Implementing these new RIs, and then trading/selling them when necessary too

At present, these are all manual tasks. We found that up to 20% of an engineer’s focus is on Cloud Cost Optimization and monitoring RIs per month. In terms of their time, that’s 32 hours a month, or 384 hours a year – enough to become fluent in another language (maybe not Python though!)

Engineering teams know optimization is a major part of a successful cloud environment, but it takes so much time away from their other growth-driving duties.

Can an Account Manager help? 

You usually get an Account Manager (AM) with your AWS relationship, and they help you with product management. But they are not solutions architects – they act in an advisory and support capacity. For example, they can advise you on areas of your cloud they may have spotted that might not be in use, but they can’t make the fixes for you. 

You might also be leaning on them for some data insights into your cloud usage and products, in order to action an optimization program. However, consider their limitations too. Unless you are a large enterprise brand, they are likely to be balancing multiple similar requests from a portfolio of hundreds of brands. So there will be a delay in their replies – and then it also might not be the exact information you need unless you are super descriptive.

Do finance understand the importance of spending on the cloud? 

Consider the following:

  • The cloud is extremely complicated, and widespread understanding of it is uncommon outside of engineering. 
  • Engineering teams are usually the only people who administer the cloud, including buying new products for it.
  • Capacity needs can fluctuate and spike, either at predictable peaks or at random events (e.g. a new customer).
  • CIO’s want to push capabilities and experiment with what their cloud environment can do to find improvements, as well as fulfill capacity at all times.

Those in engineering are focused on pushing boundaries and ensuring that their cloud environment is in top shape and working constantly. Inefficient cost consideration can stifle this. This is where working with finance leaders is key to find the balance.

However, a lack of understanding of the cloud means that finance sometimes has to rely on engineering’s knowledge when it comes to financial decisions. For example, when new products need to be purchased or scaled, finance leaders have very little choice but to trust the engineers. They do not have the data or critical understanding to analyze the necessity, and cost implications, behind the request – or at least in a suitable time frame.

This means that, without a granular view into the cloud’s architecture, it’s easy to lose track of products and spend. Regular audits and meetings, from both teams, are required to stay on top of things – taking time away from more productive activities.

Ballooning technology prices are also forcing finance leaders to be careful with every penny. If it’s not understood, it’s less likely that money will be granted for future purchases without more intricate (and time consuming) cost/benefit analysis. This can slow up new product purchases and entire cloud-related projects designed to spur growth and capacity.

Is automation the savior?

The solution seems simple. Enable clear insight into cloud spend with easy-to-understand data. This means engineering can procure what they need within necessary monetary conditions, and finance can better plan for engineering’s budget growth in the future. 

And there may be processes already in place that facilitate this. However they are usually manual audits that lack the speed and clarity to be truly useful.

In an industry where algorithms and AI are becoming more important and useful, it seems automation holds the answers to lessening the burden for engineering teams when it comes to spend administration. 

Take RI’s, for example. If programs and workflows can be plugged in that monitor RI usage, predict optimized amounts, and buy/sell/trade accordingly in real time, this would immediately free up this large chunk of time and productivity that engineers are sinking into this currently manual task.

Whilst educating finance leaders about the cloud might take too much time, having a clear view into cloud spend with easily digestible data will help them understand what products are being used, what they are for, and where optimization opportunities are. All without taking time away from the engineering team to do so. And engineering leaders can work collaboratively with finance to decide where to optimize, and where to reinvest.

Cloud Cost Optimization is the perfect solution

Luckily for cloud specialists and finance leaders everywhere, Vertice’s Cloud Cost Optimization tool is designed to do exactly this. 

Not only can it help you optimize by up to 25%, but it also ensures that you aren’t impacting your productivity either. Algorithms automate buying and selling RI’s on your behalf, and in real time – so you don’t have to worry about this extremely manual task (you get all those hours back!). This is based on regular and automated optimization tests, so the decisions are being made on the latest and best data.

And granular visibility into your cloud spend means finance leaders aren’t constantly in negotiation with the engineering department around costs. It’s all laid out for them. So engineering can do what they do best, and finance can control spending more easily and effectively. 

See for yourself – book a demo today

Or, to learn more about where spend management is affecting your business productivity, read our latest report about how SaaS contract management is hurting your efficiency and growth.

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