Many FP&A leaders invest in dedicated software to make the budgeting and forecasting process quicker and more accurate, but they often find the technology isn’t widely used. Business units cling to their spreadsheets, for example, as they don’t like the inputs that corporate FP&A preloads into the models. To drive usage, get stakeholders on the same page.
“FP&A applications are often used in different ways throughout the organization, which makes them less effective,” says Vaughan Archer, Director, Advisory, Gartner. “These discrepancies often occur in a highly disrupted environment, such as COVID-19 has created, or corporate finance and a business unit prioritize different inputs to the budget and forecast because they have different scopes of operation.”
Reflect on the differences between managing performance in a business unit versus the whole organization
To spur usage and increase the return on these investments, set data-governance standards, establish shared buy-in on the drivers of performance that budgets and forecasts track, and regularly share context for budget and forecast data to maintain buy-in.
Set standard rules and definitions for data
Set consistent enterprisewide rules and definitions for budget and forecast data. The outputs are only as good as the inputs. To advise the organization’s senior leaders, corporate and business-unit managers need confidence in their data. This starts with data quality and integrity — and consistency across corporate and business-unit FP&A models.
“When business units all have their own arcane approaches to budget and forecast management, it can erode confidence, not just in their advice but in already-accepted sources of data,” says Archer. “FP&A leaders should form a data governance committee with other experts in their organization and aim to establish organizationwide standards for all data that serves a core finance or business objective.”
First choose what data to standardize, for example, the data most typically used in a budget or forecast. Second, review the different sources of data and assign each an owner. The data governance committee should decide on the scope of that dataset, its unique identifiers, and various common or specific attributes it should have.
Commit to shared budget and forecast drivers
Corporate and business FP&A teams often differ over business performance drivers. When adopting technology, corporate FP&A often designs the system it needs. Business FP&A teams may not agree with their model, and therefore create their own measurements, resulting in a haphazard approach.
To avoid this pitfall, make sure corporate FP&A works with business-unit leaders to map enterprise drivers on a scale for historical accuracy (scaled along the X axis) and cost impact (y axis).
Ensure that corporate finance’s interpretation of the data becomes established as the dominant perspective
The most important drivers are those that can be modeled most accurately (things the enterprise knows will occur) and have the largest cost impact (top right quadrant). The least important are those that can’t be modeled accurately and have very little cost impact.
“This exercise presents an opportunity to reflect on the differences between managing performance in a business unit versus the whole organization,” says Archer. “It forces you to acknowledge that business units have specific drivers and gauges their impact on the efficiency and accuracy of budgets and forecasts.”
Provide context for data
Provide context for the data you present to business units. Examples are:
- Dashboards that track performance against the identified drivers
- Insights about how to use these drivers for forecasting and budgeting
- One- to two-minute narrated presentations that summarize financial updates and trends
“Providing rich, qualitative context to the data in a short and accessible format helps to keep people engaged in the organizationwide approach to budgeting and forecasting,” says Archer. “It is a way to ensure that corporate finance’s interpretation of the data becomes established as the dominant perspective and leads to better organizationwide understanding of financial data.”
Read more: It’s Time to Upgrade Your Finance Analytics