Forecast cloud and SaaS spend at the technology and portfolio level

Overview

Cloud and SaaS spending is inherently more difficult to forecast than traditional IT spending because it is consumption-based, elastic, and influenced by application growth, new service adoption, and pricing changes that are outside the organization’s control. Traditional IT budgeting approaches — last year’s spend plus an inflation adjustment — are particularly poorly suited to cloud and SaaS spending, where growth in application usage can produce cost increases significantly larger than inflation, and where rationalization programs can produce cost reductions that legacy budgeting approaches would not anticipate.

Best Practice

Develop cloud and SaaS spend forecasts at both the technology level and the portfolio level using the demand drivers — application growth projections, new service adoptions planned, and rationalization programs in flight — rather than historical trend extrapolation alone. At the technology level: for each major cloud service in the Cloud and Infrastructure Services Inventory, forecast usage growth based on the growth plans of the applications that depend on the service and the committed capacity strategy in place; for each major SaaS platform in the Software Subscriptions Inventory, forecast seat count changes based on hiring plans, adoption programs in progress, and rationalization decisions affecting the platform. At the portfolio level: aggregate the technology-level forecasts into a total cloud and SaaS spend forecast, adjusted for committed capacity discounts, negotiated price protections, and the financial impact of rationalization programs in the planning period. Present the portfolio-level forecast to financial leadership alongside the budget request, with the key assumptions underlying the forecast and the sensitivity of the forecast to changes in those assumptions.

Benefit(s)

Demand-driver-based cloud and SaaS spend forecasting produces budget commitments that are more accurate and more defensible than trend-extrapolation forecasting, because they are grounded in the specific business decisions that will drive cloud and SaaS cost changes rather than in historical patterns that may not persist. Financial leadership develops greater confidence in technology financial forecasts that explain the specific factors driving each change rather than presenting a black-box number. And the forecasting discipline creates the organizational conversation about cloud and SaaS cost drivers — application growth, new service adoption, pricing changes — that connects technology financial governance to business planning in a way that trend-extrapolation cannot.