3 driver-based budgeting tips for CFOs

3 driver-based budgeting tips for CFOs

The life of a finance team during budget season is arduous and often frustrating. CFOs tasked with budget presentations often find themselves explaining numbers and assumptions that are far out of date by the time they stand before key stakeholders. Outdated, static budgeting processes simply cannot keep up with today’s lightning-fast economic environment.

CFOs using driver-based budgeting, on the other hand, can create a dynamic and agile finance-centered process that helps stakeholders make informed decisions tied to operational goals. This enables CFOs to transition from a tactical to a strategic leader, aligning forecasts and projections with external as well as internal drivers (e.g., changes to the corporate tax rate or labor contracts).

A strategic budget tool for a fast-moving world

Driver-based budgets do more than static budgets, and they do it faster. In addition to allocating resources based on past performance, driver-based budgets enable CFOs to help drive business priorities, respond more quickly to changes in the marketplace, and create a dynamic, data-driven process. These budgets enable active and continuous budget planning, rather than annual and fixed planning that culminates in hundreds of unread pages.

Agility is a buzzword for a reason. CFOs hoping to build confidence in their numbers can no longer rely on static budget tools to get the job done. In a world with increased regulatory volatility, supply chain mobility, labor market changes, and technology evolution, a CFO must be agile, or generate irrelevant reports and budgets that no one reads.

Eliminate data silos

Traditionally, CFOs assemble budgets using data from multiple sources throughout the organization. Departments input budgets with no idea how their performance ties to larger initiatives, and finance teams are left guessing how everything fits together. This siloed approach to budgeting keeps stakeholders in the dark about the impacts of revenue and expense projections downstream.

Take this story of a disaster-relief nonprofit. The organization relied heavily on a partnership with Tough Mudder, an extreme sports event held throughout the U.S., for 20% of total annual revenue. In past years, Tough Mudder pledged 1.5% of all ticket sales to the nonprofit. The assumption that this revenue would continue a 3% growth rate became a central budget assumption—but only for some of the budget team. The chief development officer created a series of what-if scenarios based solely on his models, rather than conversations with the donors or the CFO. Meanwhile, the CFO ran a parallel process that left Tough Mudder revenue out of the budget altogether, based on some initial talks with the sponsor. Until the chief development officer and the CFO sat together and agreed on revenue and expense assumptions, budget chaos reigned.

Regardless of company size or industry, CFOs can generate greater collaboration and eliminate budget silos by identifying a single source of data, generating rolling forecasts, and creating a centralized and accessible planning resource. Upstream data integration helps operational units view budgets in a larger context and makes it easier to line up support from key stakeholders.

Ultimately, eliminating silos creates a dynamic budget process that drives rather than reacts to business performance.

Identify KPIs that drive finance and tie to the operational plan

3 driver-based budgeting tips for CFOs

KPIs are operating activities that encompass everything from customers to installations to deliveries to transactions. CFOs might track different KPIs (e.g., booking versus revenues, sales by geographic location), but more KPIs isn’t always a good thing.

In the case of one healthcare organization, disagreement about KPIs nearly derailed the budget process. Tasked with tracking patient-specific revenue, the budget committee initially identified quality of care metrics as a revenue KPI. The assumption that satisfied patients would return to the facility for care, thereby driving up revenue, ultimately proved less accurate than conducting a demographic analysis. Eventually, the budget committee concluded that indicators like patient age, location, income, race, health status, and utilization histories were more effective KPIs than stand-alone satisfaction metrics. This materially changed the budget and aligned it more closely to organizational goals.

Integrating KPIs into the budget process empowers CFOs to make course corrections and measure overall business performance, while creating buy-in throughout the organization.

Differentiate forecasts from targets

CFOs using driver-based budgeting must differentiate between forecasts—where the organization is headed—and targets—where the organization hopes to go. Forecasts should be based on a run rate of previous performance, whereas targets tie to aspirational goals (market expansion, new product launches, etc.). By separating targets and forecasts, CFOs create a robust budget process that continually course-corrects and adapts to market factors.

Investors in a new production facility, for example, would need the finance team to present scenarios based on when the facility would be online, potential construction delays, and other unknown variables. A driver-based budget-oriented CFO would ask important questions like: Do we have a hiring plan in place? What happens if the product components increase from $40 apiece to $50 apiece? She would create best, worst, and likely scenarios against which results would be measured. Targets, on the other hand, relate to where the organization (whether board, leadership, or investors) hopes to go. In the case of a new facility, the revenue target might be 100% production-ready by Q3.

Today’s CFOs are expected to navigate complexity through standardization, automation, and the streamlining of processes, systems, and data. Driver-based budgeting helps support growth initiatives, drive margin expansion, and manage business performance through better analytics and reporting.

This blog was originally published by Adaptive Insights

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