A big majority (80%) of finance leaders agree finance must significantly accelerate its implementation of digital technology, such as robotic process automation (RPA) and artificial intelligence to effectively support the business by 2025, according to a survey by Gartner.
When implementing RPA, CFOs see investment in process mining as key to unlocking returns from the technology.
A December 2021 survey of 400 finance leaders showed a broad expansion of the CFO technology toolkit being used to drive efficiency, agility and productivity. RPA remains the technology most often cited by respondents in supporting their hyper-automation objectives, but the technology has yet to deliver a high level of value to finance departments.
“Despite ongoing investment in RPA, CFOs are realizing they need a broader toolkit to realise their full automation objectives,” says Nisha Bhandare, vice-president analyst in the Gartner Finance practice. “To realise higher value from their RPA investments, CFOs are turning to a suite of complementary efficiency technologies, such as process mining, which will remain a future driver of growth for RPA in the coming years.”
As part of the survey, CFOs were questioned on 16 different technologies within the category of process automation and optimisation. Only three technologies within the category are expected to see an increase in investments from current levels over the next two years: reporting automation, RPA and process mining. Of those three technologies, only reporting automation was rated as currently delivering “high value” to finance departments.
“Finance processes are complex, exception-heavy and reliant on judgment and subject matter expertise,” says Bhandare. “This currently puts a ceiling on RPA’s value creation, and CFOs need to explore additional options both to enhance RPA’s usefulness, and in some cases, select better fit technologies for their automation goals.”
Gartner’s analysis of the survey results indicates three key drivers of growth for RPA over the coming two years: embedded machine learning, cloud delivery and integration with process mining. While process mining is still an exploratory technology, not yet being widely adopted by finance departments, the potential to enhance current RPA implementation makes it an attractive technology within the category.
Process mining is designed to discover, monitor, and improve real processes by analysing event logs in information systems. Finance leaders can review exactly what happened during the execution of their process after the event logs are analyzed by the process mining algorithm.
Process mining can be used in three distinct and additive ways, including:
* Process discovery – Build a model to reveal how a current process is operating “as is”;
* Process conformance – Compare the actual event’s process to its ideal model; and
* Process enhancement – Improve or extend processes, including with RPA.
“Process mining gives finance leaders a tool to identify the root causes of inefficiencies and exceptions in real-time,” says Bhandare. “This provides the opportunity to streamline and correct processes that may have been perceived to be resistant to automation and introduce more opportunities to use RPA – and automation more broadly – in achieving additional efficiency and cost gains.”