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.
|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.
|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.
|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.
|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.
|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|