At its core, financial planning and analysis (FP&A) is the process of analysing past data to gain insight into the financial situation of a business, for regular reports and strategic projections, as well as ad hoc “what-if” simulations. When done right, this type of analysis enables CEOs and CFOs to make informed decisions about the strategic direction of the company.
The FP&A process is typically carried out by a team of finance professionals working heavily with spreadsheets to compile and analyse data. Without proper FP&A, decision-makers are essentially flying blind.
Didi Gurfinkel, CEO of DataRails, has strong feelings on this subject. “FP&A is a critical aspect of forecasting for businesses, but unfortunately the methods we use to carry it out aren’t evolving as quickly as the rest of the landscape,” he explains via email.
Despite its importance, FP&A processes tend to suffer from serious issues. For one, there’s a lot of time-consuming manual work involved. Another major problem lies in ensuring accuracy and preventing human error during manual data manipulation.
FP&A, like other finance tasks, relies heavily on Microsoft Excel. While Excel is certainly a powerful tool, using it to compile and analyse data requires someone to either manually comb through cells or create and maintain complex formulas and functions to pull the needed data.
Reliance on legacy spreadsheets is inefficient and causes a tremendous amount of overhead and friction for analysts – the opposite of what you want in a process that should be essential for every business.
Many of the solutions to these problems involve moving away from Excel entirely, which also isn’t practical in many cases. Smaller businesses, in particular, may not have the time or manpower to migrate their data and the deep logic they’ve built into their Excel sheets to a new platform.
“While the rest of the business world moves to powerful, cloud-based SaaS solutions driven by AI and automation, finance departments remain entrenched in Excel,” says Gurfinkel. “While it’s a powerful tool, it lacks modern features that could help drive better forecasting. The ideal solution is one that builds on Excel to leverage its strengths while minimising its weaknesses, rather than trying (and failing) to replace it.”
Leveraging automation to streamline financial data
“Automation” has nearly reached buzzword status at this point, but that doesn’t mean the advantages it offers aren’t real. Automation has the potential to transform nearly every facet of work – including financial planning.
As mentioned, one of the biggest challenges faced in FP&A is repetitive, manual work taking time away from actual analysis. Automated tools can pull in data from multiple Excel sheets as well as cloud-based repositories, and organise it clearly, allowing for easier analysis.
They can also provide more flexibility in how data is visualised, easily going from a big-picture view to a detailed look at a specific department or timeframe.
Additionally, modern tools like DataRails can automatically track the history of cells in Excel, providing valuable insight into where the numbers came from. This information is often useful in analysis, but keeping up with it requires an intentional effort on the part of those doing the data entry – another large time sink.
Ensuring reliable plans and forecasts with AI
Another major issue with the current standards for financial planning is the possibility for human error. Manual data entry (and even manual creation of formulas) always carries the risk of error – anything from a mistyped number or missing cell to a formula that misses a key component.
In the best case, data entry errors require time, as it can take hours for someone to track down the source of the problem and correct it. If they go unnoticed, though, the worst case scenario can be critical budget problems – either spending too much and running out of funds for a project, or underestimating how much you have available and needlessly limiting an initiative that could have benefited from more funding.
What this means in practice is that teams have to spend additional time ensuring financial data accuracy that could be better spent elsewhere. Even then, there may be lingering doubt as to whether or not a forecast is accurate.
If businesses could trust their numbers, it would remove a tremendous amount of stress during planning and free up finance professionals to spend more time analysing data and providing deeper insights. Using linked data sources, then, is a big aspect of circumventing Excel’s pitfalls, while AI makes updating projections more accurate.
“It’s important to me to give financial professionals confidence in the validity of their numbers,” says Gurfinkel. “This confidence then trickles down to the rest of the organisation. Marketing, engineering, logistics, sales and purchasing departments can make decisions with assurance.”
AI-based solutions help avoid these errors and can assist in tracking them down if they do occur. The end result is more reliable numbers and more accurate forecasts. With so many industries leveraging the power of AI to ensure reliability and streamline processes, it’s about time that FP&A caught up.
Better financial planning is possible
Finance professionals spend a lot of time searching for information, consolidating it, and entering it into spreadsheets. There’s a lot of data manipulation involved. This work is important in the sense that it enables analysis, but it doesn’t directly contribute any actual value to an organisation.
The analysis itself is what’s truly valuable. This is where the insights hidden in the numbers are uncovered – what they say about the business and what needs to be done about it.
For all its power, Excel is far from smart. That’s where the new generation of financial analysis software comes in. Tools like DataRails promise to reduce time spent on data entry and manipulation, enabling finance teams to spend more time analyzing the numbers and giving direction to leadership.
