5 Ways to Forecast Your Cloud Spend

Posted January 14, 2021 in Business Technology & Digital Transformation Strategies
5 Ways to Forecast Your Cloud Spend

Do you need a forecast of your cloud spend? In this Advisor, I investigate five cloud spend forecast methods, with their pros and cons, to help you make a choice.

Disclaimer: Business life happens, and no model can account for every aspect of reality. A forecast is a prediction, so a forecast will always be wrong to some degree! Without exception.

Option 1: My Usage Is Constant and Planned to Stay Constant

Summary: Take the last-period consumption and assume the same for the future.

Example report: Last month, we spent US $10,000 on the cloud. There are no changes planned next month, so we expect to spend another $10,000.

Best suited for: Predictable workloads over the selected period.

Effort level: Almost null. Look at the last number and use that.

Pros Cons
Immediately available Extremely sensitive to change
No effort needed  
Very accurate when nothing changes  

Option 2: Take Last Period and Add (Remove?) X%

Summary: Take the last period number, add X% (or any other value).

Example report: Previous-year cloud costs were $100,000; based on a business growth of 20% we estimate next year to be around $120,000.

Best suited for: Providing a single number covering an extended period. Usually, to feed a financial model where the cloud costs are directly in correlation with business growth. Effort level: Low, as the % to add (or remove) should be provided by a financial model.

Pros Cons
Very fast Very generic
Very easy Very static number
Backed by business data (kind of)  

Option 3: Using AWS Cost Explorer Forecast (or Other Cloud Vendor Tools)

Summary: AWS and other cloud vendor forecasting tools.

Example report: Based on our past data and using the algorithm provided by AWS, we can estimate our cloud costs to be between $x and $y.

Best suited for: A fast, backed-by-others forecast easily presentable to non-IT.

Effort level: Low and usually self-service.

Pros Cons
Available immediately Based only on data available to the cloud vendor, so no business connection
An innovative company offers the results Future scenario modeling requires the use of additional tools (e.g., Excel)
The graphs look great The methodology is unknown
Provides minimum, maximum, and expected values The accuracy drops fast

Option 4: End-of-Month Forecast

Summary: Create an end-of-month forecast based on the already-known monthly consumption and projecting the last 24 hours until the end of the month.

Example report: The most recent optimizations, introduced on the 14th, have reduced the monthly projected spend by 15%.

Best suited for: Proving the value of individual changes and to keep an eye on the impact of daily activities on the monthly budget.

Effort level: Significant as the methodology is, it is not available by default and requires extracting data from the cloud vendors and analyzing it.

Pros Cons
Available on some dashboards Needs to be implemented
Great to show the impact of cloud initiatives Data management and ETL knowledge are requirements
Capabilities to follow the monthly budget on a day-to-day basis Understanding the cloud vendor’s financial reporting files is a must (e.g., AWS cost and usage report)

Option 5: Use Business Data (Sales Projections)

Summary: Identify a cloud cost per unit of work (e.g., $/user or $/transaction) and map on the financial model used in the business.

Example report: Our cloud infrastructure has a fixed cost of $100,000 per month. Each customer costs $12 per month. By using the planned growth in the sales forecast, we can project the following monthly cloud cost.

Best suited for: A dynamic representation of the cloud costs mapped on the company’s units of business measure with forecasting based on a well-known financial model.

Effort level: Significant, requiring expert consultants.

Pros Cons
Converts IT slang into money, making it easy to understand for other departments Complex to implement
Easy to recalculate, even daily Requires bespoke modeling
By mapping cloud costs to the company units of goods sold, the results are more comprehensible to non-IT A change in the business model requires an update in the algorithm
Any IT effort to reduce the cost per customer is made visible  

About The Author
Frank Contrepois
Frank Contrepois is a Senior Consultant with Cutter Consortium’s Business Technology & Digital Transformation Strategies practice. As a cloud expert, he has developed and implemented innovative solutions relating to cloud installation, configuration, customization, and integration. Mr. Contrepois is a driven, innovative, and entrepreneurial leader with extensive experience within the technology sector. He is adept at incorporating a culture… Read More