Cloud Forecasting Principles: Breaking Free from Wishcasting
Cloud computing has become an integral part of how businesses operate and scale their IT infrastructure. However, the dynamic and often unpredictable nature of cloud services can lead organisations down a perilous path of financial waste if they fail to implement a well-defined forecasting process.
In this article, we’ll explore the concept of wishcasting and the evolution of IT expenditure forecasting, along with various methods and models to help organisations make more accurate and cost-effective cloud spending forecasts.
The Pitfalls of Wishcasting
Wishcasting is a trap that organisations can fall into when they interpret information or situations in a way that portrays them in a positive or desirable light, even when there’s no supporting evidence. In the context of cloud spending, wishcasting can lead to unexpected expenditures and unnecessary costs. Without a clear understanding of past spending patterns and future requirements, organisations risk overspending on cloud services. To avoid this pitfall, a robust forecasting process is essential.
The Evolution of IT Expenditure Forecasting
Before the advent of cloud computing, IT expenditure forecasting was primarily centred on the annual budgeting cycle. This process involved creating business cases for capital expenditures, but it was often a one-time effort that didn’t require ongoing collaboration with other business units. Predicting future IT costs was akin to gazing into a crystal ball — a highly uncertain and imprecise endeavour.
As organisations shifted to cloud-based solutions, the need for more precise forecasting methods became apparent. Cloud expenditure forecasting now demands increased cross-departmental collaboration and communication processes to align with budgets and business objectives. Variable cost models have become the norm, and inaccuracies in forecasting can have significant financial consequences.
Forecasting Methods
To make more accurate cloud spending forecasts, you have several methods at your disposal:
1. Naïve Forecasting: This method relies on historical spending data to assume that future spending will mirror past patterns. However, the dynamic nature of cloud services can make this approach risky, as unforeseen increases in demand can drive up costs.
2. Trend Forecasting: Trend forecasting uses historical cloud spending data to predict future expenses based on past trends and patterns. While useful, it may not account for sudden changes that can lead to additional spending.
3. Driver-Based Forecasting: Also known as multivariate forecasting, this method considers various business metrics to enhance accuracy. Integrating business drivers into cloud spending forecasts can be highly effective in improving precision.
Each of these methods has its strengths and weaknesses, but organisations can create more robust forecasts by combining them to mitigate biases and errors inherent in individual models.
Choosing the Right Forecasting Model
Selecting the appropriate forecasting model depends on the scale and complexity of your cloud consumption. Consider the following models:
1. Composite Forecasting: This approach enhances prediction accuracy by combining multiple forecasts from different models and averaging the results. It leverages the strengths of various methods to improve overall accuracy.
2. Static Forecast: Suitable for highly predictable and stable spending situations, a static forecast is generated once at the start of a predefined period (e.g., 12 months) and remains unchanged until the end of that period. However, it may not be suitable for dynamic business environments.
3. Rolling Forecast: Similar to a static forecast, but it is regularly regenerated at predefined intervals. This adaptability makes rolling forecasts the preferred choice for organisations looking to enhance financial planning, cost control, and decision-making processes.
In Conclusion
Cloud expenditure forecasting is an essential practice for organisations seeking financial efficiency and cost control. By understanding the pitfalls of wishcasting, embracing more precise forecasting methods, and choosing the right forecasting model, businesses can navigate the cloud landscape with confidence and optimise their IT spending for the future.
If you have any questions related to cloud cost optimisation or any licensing matter, please go to our website or contact us.
About the author
Karl O’Doherty is a Principal License Consultant at Version 1.
