How Will Technology Disrupt FP&A This Decade?
There’s no question that modern technology is disrupting industries across the board. We’ve been living in a digital revolution for the last few decades, and the recent pandemic served as a catalyst for enhanced technological innovation and disruption.
For instance, a recent survey from McKinsey found that companies have accelerated the digitization of interactions by four years, internally within organizations and between customers and vendors through their supply chains. On top of that, these companies revealed that their portfolio share of digital or digitally-enabled products sped up by seven years.
So, what do all these technological and digital disruptions mean for those of us in the finance services sectors or in finance functions, especially those in FP&A?
Let’s dig in to see how technology will reframe our industry over the next few years, primarily in the form of artificial intelligence (AI) and machine learning (ML).
The Rise of the Machines (Sort of)
When people hear “artificial intelligence” or “machine learning,” they often think of characters from sci-fi books and films. However, today’s AI is less threatening (and exciting) than the Terminator or Robocop.
That doesn’t mean AI isn’t disruptive, however. On the contrary, AI will alter how FP&A professionals do their jobs completely. The jobs won’t disappear – instead, they will be redefined and reshuffled.
AI in FP&A
The most significant use case for adopting AI in FP&A is routine data reporting and core analysis.
Today’s FP&A teams are moving further away from a traditional reliance on spreadsheets (i.e. Excel and Google Sheets) for planning and analytics. A recent survey from IBM found that 58 percent of companies still rely on spreadsheets for planning and budgeting purposes, yet 41 percent know that Excel is incapable of handling their large datasets. It’s just too manual for significant scale and too bottlenecked by data volume restrictions.
That’s because, when it was developed, Excel was never intended to serve as a data analysis tool. So, companies that need more data handling capabilities than what Excel can offer are becoming more interested in how AI and ML can help.
Because spreadsheets were never that great for achieving planning and analytics objectives, the move away from spreadsheets is creating many opportunities and much excitement for FP&A teams. It’s highly unlikely that Excel and Google Sheets will ever disappear, because they’re outstanding organizational tools and serve a vital role for ad-hoc analysis and dynamic modeling. However, it’s unlikely they’ll ever be fully capable of processing and analyzing large data sets the way that robotic process automation and AI can.
How AI and ML Tools Benefit FP&A Teams
Here are some exciting ways AI and ML tools enable FP&A to perform duties with increased accuracy and efficiency.
Create a more agile environment
Companies that could recalibrate quickly during the pandemic were more likely to survive and thrive than those that didn’t have systems in place to make fast changes. AI tools can give FP&A teams immediate access to data that can be used to drive organizational changes in a short period of time. Because AI synthesizes large amounts of data, historically aggregated, AI-enhanced decision-making can be leveraged quickly with a high degree of tangible support.
Get rid of siloes with centralized information
One challenge with using spreadsheets is they’re difficult to maintain while concurrently keeping track of different versions and disparate data. One team might be working from an older version of a spreadsheet, which means any modeling they do will soon be inaccurate and out-of-date. The challenge with version control is a common frustration among FP&A teams, as it can lead to a significant slowdown in productivity at best, and erroneous work product at worst.
AI tools often require establishment of a centralized database warehouse that ensures everyone in an organization has access to the most updated information at all times. Working from a single database, or source-of-truth, allows teams to improve collaboration and significantly reduces the chances of redundant work occurring. Additionally, it increases transparency across the organization and enables all stakeholders to have instant access to the same company financial data. There are no questions about which datasets are correct and which are unreliable.
Improve data and reporting accuracy
Spreadsheet work encourages a heightened degree of human oversight and this can be seen as a positive or negative. Anything done manually is prone to human error – in other words, more touches likely mean more critical review is taking place, but it also means that more data updates, missed formulas, and version control issues need to be monitored. By transitioning to AI tools, FP&A teams increase the automation of updates and accuracy of their data, which can significantly improve their planning and analysis.
Enhance forecasting
A primary benefit of AI and ML tools is that they can process enormous amounts of data faster than humans can, literally as fast as the speed of light. This speed gives the human users quicker access to data that can be used for predictive analytics. FP&A teams, then, can use AI to evaluate trends and patterns with greater accuracy, leading to more informed forecasting that can directly impact the company’s top and bottom lines. To achieve this degree of capability, it’s imperative that companies take the first steps in collecting, harvesting, and organizing data so it can eventually be relied upon for this purpose.
More time for planning and analysis
Analyzing data is a primary responsibility of FP&A. Yet, how often do FP&A teams find themselves spending the better part of their day tracking down data and manually entering it into a spreadsheet? According to The Association for Financial Professionals (AFP), survey participants suggested this may be close to 50%.
By using AI tools, FP&A teams can spend less time on tedious, manual tasks and more time on their primary responsibilities of planning and analyzing data, communicating the insights and supporting vital decisions. Stated earlier, AI and ML tools aren’t taking jobs away from professionals – they’re providing opportunities for humans to spend more of their time on thought-centric tasks that can benefit their organizations and less time on repetitive tasks that are necessary but aren’t value-add activities. These can be addressed by software.
Finding the Right AI and ML Tools
Of course, FP&A professionals can only tap into AI’s potential if they have the right tools. Historically, because of the lack of robust solutions, there was heavy reliance on spreadsheets through Excel and later Google Sheets. Fortunately, the explosion of planning tools and interest in AI and ML has led to a decentralization of software. The competitiveness of the landscape has also pushed pricing down. That means there are dozens of excellent solutions on the market that are becoming increasingly affordable, even to mid-sized and small businesses.
Adopting AI technology doesn’t mean companies should prepare to get rid of Excel completely. As noted above, Excel can still be used as an organizational tool among FP&A teams. But it should be used intentionally when it’s the right solution for the right problem, not the default because it’s the only tool the team knows how to use. The key to navigating this technological disruption is understanding which situations require Excel and which ones would provide greater efficiency and accuracy through the use of an AI-powered tool.
Additional Considerations of FP&A Tech
FP&A teams that adopt AI- and ML-powered tools will be able to access and analyze more data at faster speeds than was ever possible. However, there are still several factors that need to be considered by humans.
For one, FP&A teams will need to decide when they have too much information. We are constantly bombarded with articles and white papers inferring that more data is better. However, FP&A needs to be mindful about which data is most relevant, and separate meaningful data from the noise. The latter can distract and inhibit gaining further insight that will benefit the organization.
As AI becomes more mainstream in today’s and future organizations, FP&A professionals and leaders will need to be cognizant of the challenges posed by having extreme amounts of data. There is such a thing as information overload. The evolution of FP&A will require human thought, skill, and understanding, determining how much data is actually needed to move an organizational decision forward. Maturity will also require ongoing assessment of the degree to which insights will be offloaded to software platforms versus those that will remain the focus of human brains.