The automation of routine finance planning and analysis (FP&A) processes to create bandwidth for value-adding activities is unsustainable, a Gartner, Inc. study finds.
This comes despite ongoing modernisation, as the FP&A department still struggle to keep up with the increased demand for decision support in an era of heightened economic turbulence.
In a Gartner survey, which polled 273 FP&A managers and finance business partners and 102 senior decision makers at organisations with more than US$250 million in revenue, only 15% of FP&A leaders reported having a sustainable delivery model where their teams can maintain a consistent level of decision and planning support across decision makers while supporting complex, new decisions without burning out FP&A staff.
“FP&A teams are over-extended: always in reactive mode, juggling complex requests that burn out staff, and they are still leaving service gaps because they can’t serve all the decision makers that need support,” says Randeep Rathindran, Distinguished Vice President, Research, in the Gartner Finance practice.
“The typical modernisation approach of automating routine FP&A processes to create capacity for in-person decision support is simply not keeping pace with elevated demand in most organizations, and the current trajectory is unsustainable.”
Gartner says the most common scenario in FP&A functions – the internal consulting model – is to use automation to free staff capacity, so that FP&A teams have more time to spend on value-added activities such as finance business partnering.
However, leading FP&A organisations have discovered a far more sustainable and scalable way for FP&A to deliver value-added insights to the enterprise: the capability diffusion model.
This new model allows technology to be the default channel for providing decision support and in-person business partnering is the exception.
Figure: Maximum Impact on Sustainability of FP&A’s Delivery Model
Source: Gartner (April 2024)
Gartner says the rapid evolution in technology is making it possible for the first time to scale FP&A from a specialised finance team into an enterprise capability, where decision makers can become more self-sufficient by using FP&A decision support that is embedded into technology tools.
Rathindran views that the key is to think bigger and look at technology as a way to extend FP&A into the wider business rather than as just a way to boost internal capacity.
“New developments in the finance technology vendor market, and the prevalence of tools with embedded capabilities such as graph analytics, machine learning and generative AI make it easier than ever before for FP&A to transfer expertise to decision makers for complex decisions," he adds.
Finance business partners (FPBs) should move towards a teaching and tool-training role to help decision makers become more self-sufficient in using FP&A’s tool-based analysis and insights, easing demands for hands-on FP&A support.
Once in-person FBPs are no longer the default for decision support, FP&A will have greater flexibility to support the most complex or new-in-kind decisions.
