CFOs will fail to realise the full value of new technology investments unless their teams are equipped with five key digital competencies which are most crucial for delivering high business impact, said Gartner recently.
Gartner’s survey of 173 global CFOs in November 2020 revealed that plans for substantial digital investments topped CFOs’ agendas in 2021.
Without improving digital competencies, finance departments will likely struggle to fully benefit from a range of incoming investments including advanced analytics, robotic process automation (RPA) and artificial intelligence (AI), the advisory firm pointed out.
CFOs are leaning into the ‘digital mandate’ and are investing heavily in next-generation technologies, said Alexander Bant, chief of research in the Gartner Finance practice.
“However, they must remember that digital transformation is a two-part equation involving not only the technologies themselves, but also ensuring they have the staffers who know how, when, where and why to leverage these new technologies,” Bant noted
The five competencies that finance need
To help CFOs focus in the right areas, Gartner analysts sorted through 50 digital competencies and assessed them according to the following three criteria, the firm said.
Firstly, they were ranked according to their newness — the extent to which these are genuinely new competencies.
Secondly, according to staying power or how relevant they are to practical real-world technologies in use in finance.
Thirdly, according to applicability — the extent to which a digital competency relates to finance specifically.
According to Gartner, the top five digital competencies that finance teams need include:
Technological literacy. This refers to an understanding of how to exploit digital technology to drive better outcomes for finance and the business.
This competency is key to deriving value from new technologies that CFOs will be investing in this year, from advanced analytics to machine learning (ML) and AI.
Technological literacy among finance staff ensures that new technologies will be put to use in a manner that contributes to real business value and supports future business growth.
Digital translation. This is the ability to explain how digital technologies interact with finance stakeholders, processes and systems. This competency builds on previous business partnering competencies, by connecting business partner problems to the highest value digital solution.
Finance teams with effective digital translation skills can serve as a conduit between business partners and digital experts (such as data scientists) to ensure that digital technologies deliver insights that are relevant and can be acted on by business partners.
Digital learning. This is the ability to quickly meet new digital learning requirements within new environments.
Old models of training relying on manager-led sessions at set intervals are no longer viable in an environment driven by constant change.
Finance employees themselves must take ownership of their learning journeys and quickly understand how to adapt new technologies and incorporate them into the current stack.
Digital bias management. This is the ability to detect and articulate bias in ML and manage the associated risks.
This competency is vital for improving ML models, monitoring data quality and increasing stakeholder trust in these technologies.
Finance teams with digital bias management competencies have a higher awareness for flawed results generated by ML and can better mitigate and prevent them.
Digital ambition. This is a willingness to embrace new technologies and new ways of working.
Finance employees with this competency have a proactive mindset and desire to constantly build their digital skillset. Finance employees with digital ambition have an authentic interest in how new technologies can improve their work and business outcomes.
“While CFOs tell us that it is a struggle to secure just one of these competencies, let alone all five among their teams,” said Bant. “The good news is that the majority of these competencies are trainable and can serve as building blocks for a better return on finance technology investments.”
