FP&A teams should spend less time explaining the numbers and more time working with the business to manage them.
This article originally appeared on CFO.com.
Can financial planning and analysis (FP&A) groups keep up with the rapid, profound changes in many companies?
Consider, for instance, what’s shaking up the media industry. Consumption patterns have changed as traditional television viewing’s share shrinks, digital streaming rises, and content creators can more easily self-publish and distribute their shows. FP&A teams at media companies thus need to assist with insights around the shift in revenue and profit from traditional television viewing to digital streaming models; around more ways to monetize content; and around the investment required to set up direct-to-consumer models.
Similarly, the software sector has been moving from a traditional license and maintenance model to a subscription model. Here, FP&A teams are called on to assess the impacts on growth and profitability and to reallocate operating expenses and capital spending.
The Covid-19 pandemic and subsequent lockdowns accelerated some of these trends, compressing several years’ worth of shifts in digital behavior into months, as well as intensifying cost and liquidity pressures on many industries.
Business leaders and CFOs want their FP&A teams to become stewards of value creation. FP&A should spend less time explaining the numbers, they say, and more time working with the business to manage them. As one finance executive told us, “I need an operating thought partner and not someone that is just keeping score.”
CFOs have recognized the need to transform FP&A for some time. Yet despite years of hard work redesigning processes and investing in new technology and data, many have not achieved the results they expected. In our experience, they encounter five challenges when trying to transform the FP&A function.
1. Lack of alignment or buy-in
Successful transformations require a strong partnership between finance and the business leaders from the start, rather than finance acting independently and then reporting back to the business on the results. That’s because the business must make the trade-offs on the future sources of value creation and the path and timing to get there.
2. Sticking with the traditional approach to FP&A organization
Traditional FP&A organizations tend to rely on a group of generalists to carry out a broad scope of responsibilities. However, the bar for expertise in FP&A continues to rise as companies enter and exit customer segments, products, countries, business models, and channels. With deeper specialization now at a premium, organizational design can help make this happen, and CFOs are increasingly turning to new organizational models for FP&A, most notably hub-and-spoke configurations and centers of excellence.
One example is Nielsen Global Media. Over several years, Nielsen moved from a highly decentralized to a more centralized organization. In the process, Nielsen created a central FP&A analytics hub that owned the data to create a single source of truth and performed cross-functional analytics used by the entire organization. Teams colocated in the business were smaller and focused more on interacting with the business than on running the analytics. As a result, Nielsen reaped cost savings and also improved the service level of the business—by simplifying forecasting, cutting the budgeting process time in half, and minimizing the time that operational and commercial teams spent on planning.
3. Persistent gaps in critical skills
FP&A teams composed only of people with a traditional finance or accounting background often lack a deep understanding of the business domain. Partial allocation of staff time between FP&A and other areas also limits the ability of finance professionals to build competence in FP&A.
To build the required skills, it’s critical to first dedicate some group of finance professionals to FP&A work and not split them between FP&A and accounting or other transactional work. The best finance leaders look beyond traditional skillsets for people with backgrounds in business or data science or analytics. They also invest in training and rotational programs.
4. Inability to adopt or scale up new ways of working
This pitfall manifests itself through the failure to adopt innovative practices, or the tendency to make a large number of small bets with scant results. The main remedy is to pick a few areas in which to double down investment, where innovation will have the largest positive effect on the business goals.
As part of a major cost-reduction campaign, one large telecommunications firm took the opportunity for the FP&A function to reinvent itself. FP&A installed better tracking of performance management and initiatives, which improved accountability. It built a budgeting tool that improved key performance indicator (KPI) analysis and general reporting. And a cloud-based, initiative-tracking tool ensured that savings initiatives stayed on course.
5. Inadequate technology and data
As economic volatility grows, the business is increasingly requesting more frequent forecasts from finance. However, FP&A teams preparing the forecast spend half their time on data gathering and preparation, a recent survey by the Association for Financial Professionals found—an unsustainable situation.
Waiting for a large core system upgrade will take many years and have questionable ROIs. Instead, it pays to take a phased approach using a portfolio of existing and new technology solutions. Cleaning data and addressing other data issues is a good start, after which FP&A can layer on more advanced tools and use of the cloud.
Microsoft’s finance organization has been on a transformation journey since the early 2000s, improving the control of data and standards across the company. Finance has fostered a culture that continuously brings innovative technology solutions to its internal customers, particularly in FP&A. Examples include a business management portal, self-service analytics on a global KPI lake, and machine learning in forecasting processes.
Many of these innovations were developed and launched quickly—for example, 8 to 10 weeks for machine learning in revenue forecasting and 14 weeks for the global KPI lake adopted by business users. As a result, Microsoft finance has realized a 20% reduction in time spent validating and compiling data and has significantly upgraded the quality of support provided to the business.
As companies commit to transforming their FP&A function, choosing the right focus and pace is essential. They should align with business leaders on the sources of value creation for the future, then work backward to redesign FP&A around them. And they should carefully choose their spots for investment. That will raise the odds of FP&A shifting its role from scorekeeper to a true business partner.