The coronavirus pandemic has served as yet another reminder of the value of analysing treasury data when navigating challenging trading conditions.
Advanced data analytics skills are increasingly sought after within treasury teams. Data proliferation is particularly evident in this environment, where information is often updated in real time or near- real time.
This had led to increased demand for treasury staff able to think strategically about information and transform data into intelligence. Treasury teams have to respond quickly to changes in both the internal and external financial environment, observes TechnipFMC Treasurer, Fred Schacknies.
“That requires a growth mind set and the perspective of a business analyst,” he says. “A pace of change in the business world that was previously unthinkable has brought with it a need for intelligence, often from incomplete sources of data.”
The role of treasury analyst has become more commonplace because the analytical part of the function was too limited in the past and as treasurers with small team are glued into operations, they tended to leave the analytical part of their job to one side.
That is the view of Francois Masquelier, former Senior Vice President & Head of Treasury and Enterprise Risk Management at RTL Group and CEO of Simply Treasury.
“Treasury departments need employees with knowledge of new tools such as integrated development environments for programming languages,” he says. “They need employees able to build reporting in business analytics services and capable of developing in robotic process automation software to fill gaps in functionality and further automate processes.”
According to Masquelier, the major challenge for heads of treasury departments is determining the optimal combination of traditional treasury skills and new IT and analytical skills.
“Smart treasury requires talent in data mining to deliver ad hoc reports,” he adds. “But instead of producing reports exclusively for accounting, consolidation, IFRS, compliance or tax reasons, why not produce reports for decision-making purposes? Why not adopt a more proactive approach to anticipate risks and enable CFOs to make decisions properly and on time? Treasury reporting must be more prospective and less retrospective.”
Steven Krippner, Treasurer at Baker Hughes, agrees that treasury teams need advanced data analytic capabilities and expertise in the use of data visualisation tools, business intelligence platforms, and machine learning.
“Treasury must have integrated modelling capabilities to understand how shocks impact a company’s financials and understand what levers we have to support the company to work through these shocks,” he adds. “All of this requires an agile, integrated treasury capability that is very good at analytics and financial modelling.”
To be successful, heads of treasury will have to expand their competencies and the competencies of their teams, hiring people with complementary skills in areas such as IT, data analytics, report creation and even project management.
Schacknies accepts that very few people can tick all these boxes and that the best treasuries employ a diverse mix of functional specialists, data scientists and business analysts. However, such skills come at a cost.
“I do not think we need at this stage to recruit internal resources with data mining skills – this may be the case at some point in the future but not right now,” says Masquelier, adding that treasurers may need support from outside to implement solutions such as data mining.
“We should not forget that this support can come from outsourcing,” he continues. “Treasury teams should remain lean and mean while enlarging their skills, which means hiring independent consultants or freelancers and outsourcing part of the additional activities.”
