Amidst the sea of economic uncertainty, one thing is emerging as a non-negotiable for tech companies: a well-defined cloud economic model. With the escalating requirement to optimise costs, controlling cloud expenditure has taken a prime position on the priority lists of CIOs. Even though the first quarter of 2023 alone saw an overwhelming expenditure of more than $63bn on cloud services, recent history would dictate that as much as 30% of this spend is unnecessary. This startling fact puts a spotlight on the need for organisations to have a cloud technology plan that matches their financial expectations. Let’s delve into the three key areas tech companies should focus on.
1 – Understand the “why”
One of the first pieces of advice I give to businesses looking to move to the cloud is arguably even more relevant when assessing or defining a cloud economic model – make sure you understand why you are doing this in the first place. That means thinking beyond just a business outcome or “cloud is a cool technology that everyone is using”. Instead, you need to equate three factors here:
The business factor – From a business perspective, you need to be clear on the objectives you intend (or originally intended) to achieve through migration. Is it for attaining greater scalability or fostering agile development? Are you seeking cost reduction or chasing performance enhancement? Having this clarity will not only guide you in developing a successful cloud strategy but also shape your economic model.
The technical factor – On the technical side, there’ll be a whole host of factors that may not always equate with the business reasons for moving to the cloud. Things like functionality, resiliency, availability & security requirements – even if some of these are part of your original plan, expectation vs reality can be a real factor here.
The economic factor – So finally, we come to the all-important question, how much is this going to cost? If the business reasons and technical requirements aren’t aligned, which is often the case due to the disjointed nature of teams defining them, the economics will fall short of expectations, resulting in the dreaded ‘Billshock’. Therefore, it is vital to devise a tech plan and model that matches expectations.
2 – Consider the data lifecycle:
A common pitfall that businesses stumble upon while defining their cloud economic model is ignoring the data lifecycle. You need to think about where data is going to sit, and what it’s going to cost – but this doesn’t (and more importantly, shouldn’t) stay the same over a seven-year data lifecycle.
Your economic model should walk hand-in-hand with the data lifecycle, taking into account its evolution over time. The cost of storing data should diminish as it ages. Fresh data demands more resources, residing on high-performance, transactional types of storage. On the flip side, data approaching the end of its mandatory retention period doesn’t necessitate cutting-edge storage. Cloud providers may allow you to use snapshots indefinitely, but this could prove as costly as production.
The data lifecycle progression can be broadly classified into three phases – performance tier, object storage, and archive storage. As you plan this lifecycle, remember to consider other crucial factors like ransomware resilience and regulatory compliance. If your data resides on higher category storage than necessary, you’re flushing money down the drain.
3 – Discard the security vs economy dichotomy:
Security and resilience are often perceived as standing in opposition to economic considerations. This especially holds when businesses are looking to upscale with the cloud, but this doesn’t have to be the case. Remember that the two main driving forces behind the shift to the cloud are enhanced resilience against ransomware and reduced costs – it’s possible to do both. Immutability originated in the cloud, and cloud-powered disaster recovery is now a staple for most businesses, with the Veeam Data Protection Trends Report 2023 revealing that 84% of businesses employ the cloud for their disaster recovery function.
This false dichotomy usually stems from technical debt, a result of not including security in the cloud plan from its inception. Such an oversight can lead to a catastrophe or, at the least, hefty expenditure to correct the mistake. The problem magnifies when the business and tech teams operate in silos, which sadly is becoming more and more common. The solution? Factor in security right from the design phase and incorporate it into the economic model. Ensure that the tech teams are aligned with the business teams. Enter with a mindset balanced between ransomware resilience and your economic model. Embed security into your cloud strategy from day one. Be intentional and holistic in your approach to prevent creating further technical debt.
As businesses navigate the choppy economic landscape, creating a cloud economic model rooted in the ‘why’ and balancing business, technical and financial considerations is crucial. A well-defined cloud economic model is not just a “nice idea” anymore – it’s a necessity for survival and growth.