The dependency on Cloud in enterprises are increasing at the fastest pace in this era of digital transformation. The global public cloud computing market is set to exceed $330 billion in 2020 and to reach $623.3 billion by 2023. Whether the cloud be public, private or hybrid the overall CAGR is expected to be at 18% and would consume a third of any organisation’s IT budget.
With the ongoing move-away movement from traditional data centres to cloud, it is becoming increasingly imminent to have control over the cost and spending on the resources being utilised on cloud. Lack of strong cloud capabilities both from technical setup to more increasingly towards budgeting and forecasting for cloud spending is becoming a serious issue with business leaders, especially the CIO and CTO.
Every cloud Vendor has multiple robust offerings towards the overall spend and the kind of resources being used, but almost none come with a strong Visual analytics and breakup of spending. When it comes to the breakup of shared services being utilised by multiple cost centres located around the globe, the availability and offerings from cloud vendors is not much. The organisations are left to find their own ways to deal with the situation and become compliant on their own, to make it feasible.
Data sciences and Artificial Intelligence with strong Visual Analytics tools, comes as a rescue to predictive analysis on the Organisations IT spending towards cloud. With use of AI and ML the analysis becomes more and more robust as we nose dive in the future with dependency on Cloud. In accordance with the usage on cloud and identifying the linkages between the Billing information provided by cloud Vendors and the auditing capabilities available, it is possible to gain a strong understanding on the organisation spending. More than that analysis on historical data availability with data sciences capabilities, it is possible to gauge into the future spending of the organisations. The predictive analysis can provide insights to a level of daily, monthly or yearly trend indication of resources, projects, initiatives, increments and enterprise level spending. It shows the way to lead the organisational independence from cloud vendors and doing its strong analysis on the overall spending. AI and machine learning, with a consistent support and analysis from data scientists, can show a clear path to proceed. The shared services analysis can provide a relief to transfer the cost to the respective cost centres.
“Cloud is about how you do computing, not where you do computing.” – Paul Maritz, CEO of VMware
It is possible to approach it in a structured way and by using the capabilities offered by the cloud platform itself. Small steps can make a huge impact. It is recommended to start with understanding the extent of what we want to achieve, dive into the cloud offerings used on initiatives, projects and how the organisational setup is created. Understand the billing information being offered by the Cloud Vendor. Combine the information from above together to understand analytics capabilities we want to achieve and formulate some definitive KPI’s. Once this is done, identify the data required and the tools which can provide and help in doing the analysis. It is important to start small, keep small, increment regularly, learn iteratively and make it large as part of your roadmap. Small independent and self- reliant dependent teams are the future. We can be there to help each other together to support the People, with the strength of the Relationships and a strong acumen to technology …………..