“Digital transformation” and “data-driven decision-making” are familiar buzz terms but inescapable realities. CFOs, controllers and finance teams are sitting at the epicenter of this corporate sea change. No longer viewed solely as bookkeepers and number crunchers, finance departments are increasingly responsible for turning numbers into insights, information into stories, and data into meaningful analysis that helps business leaders make the right decisions quickly — over and over again.
Automation holds the key to success in this new cut role. For finance teams to make the leap from bean counters to strategists, the approach to working with data and reporting processes also needs to change. This means a shift from static to real-time data, and from manual to instant and repeatable reporting processes that are less prone to errors introduced by human manipulation. Only then can finance teams deliver real value to their organizations. For example, offering guidance to the C-suite on an ongoing basis, not just at end of month or end of quarter. Or creating reports for an impromptu board of directors meeting and deeper drill-down reporting in the middle of those meetings — all based on data that is live, not days or even weeks old.
Just how automated are finance teams today?
We’re making progress. Many finance teams have begun incorporating reporting automation over the last few years and are reaping the benefits: faster and more accurate reporting, less reliance on IT, and better business outcomes. But a 2019 accounting and finance benchmarking report (registration required) from Robert Half revealed 54% of U.S. companies were still manually reconciling financial reports.
And we’re only at the beginning of the technology journey. It’s a path that will lead to new levels of business agility and productivity, but also comes with a new set of demands and expectations.
Below are three predictions that will impact finance teams by 2025:
1. Finance professionals will become data scientists.
The amount of data pouring into organizations will continue to increase, especially as emerging technologies, like IoT, gain momentum. More than ever before, finance teams will need to move away from transactional tasks, relying on automation for compilation of numbers and reporting, and focusing efforts on strategic analysis and even data modeling so that data is categorized in a way that is relevant for analytics and the business overall.
Compounding the need for modeling skills, 80% of the world’s data will be unstructured within five years, according to IDC. Most finance departments today do not analyze or make use of unstructured data (such as text from emails, call transcripts or social media channels). The ability to combine and analyze structured and unstructured data will become an important asset as finance teams looking to implement automated controls and create an early warning system to highlight hidden risks to aid risk management and compliance.
2. RPA will gain ground as a key automation technology on the road to AI.
A recent article reported that LinkedIn saw a 60% increase in financial job postings requiring skills related to AI, machine learning and data science in the last year. While the end goal is true artificial intelligence, the journey to AI will go together with increased optimization of everyday processes and automation. Automated data extraction and reporting already help finance teams gain productivity and efficiencies. Within the next five years, most finance teams will be working in environments with even deeper levels of automation. One of the most notable examples is robotic process automation (RPA), which some studies show can reduce repetitive data entry tasks in areas like accounts payable, tax accounting and financial closings, and automate processes by up to 80%.
While actual AI as a mainstream component of finance teams is likely up to 10 years away, more organizations will begin to engage with RPA and other technologies as the first steps in reaching true intelligent automation, which is a combination of process-driven (RPA) and data-driven (AI) tasks. For example, RPA can help to speed up data entry from existing supplier invoices that are in a standard, well-understood format. But AI will be required to process a new invoice from a new supplier and to understand the value of the invoice, the due date and the payment terms.
3. Reliance on predictive analytics will grow.
By 2025, most finance departments will be using predictive analytics in some way, shape or form, whether they know it or not. In the report Gartner Magic Quadrant for Cloud Financial Planning and Analysis Solutions, by John Van Decker, Robert Anderson and Greg Leiter, August 2019 (registration required), 46% of survey respondents said they aimed to deploy predictive analytics technologies by 2021 to improve business insights. Finance departments will use it for more automated and intelligent planning and forecasting and to identify trends, uncover risks, and make better decisions. Real-world applications might include tracking items like days sales outstanding across customers, business units and product lines, as well as alerting accounts payable in advance if signals are pointing to an increase in this area.
There’s no question that the future of finance will involve sophisticated technologies that deliver higher levels of intelligent automation. This is good news for finance teams, who can focus on bringing more strategic value to their organizations as data scientists and analysts. Is your team ready?