Artificial intelligence will liberate FDs to become more strategic, says Angela Mazza Teufar
The more reliant businesses become on data, the more adding value for a CFO means bringing data analysis to their jobs, as well as number-crunching.
Being successful in the digital age means so much more than being good with numbers. Yes, a working knowledge of P&Ls, accountancy practices and forecasting is still needed, but the skillsets of the CFO have had to become far broader. CFOs are now expected to offer strategic insights to their teams – and the CEO. In fact, nearly half of businesses have changed their models to become more agile and the CFO is expected to be the driving force behind that.
Pushing that agility could be anything from helping departments unearth new opportunities to improve their performance internally, through to recommending focus areas for a new product or customer service.
Shifting to strategy
But why does this responsibility fall to finance? Finance departments are in a unique position. Aside from the CEO, finance employees are the only ones with a ubiquitous insight into the running of the organisation and, to the data pertaining to all parts of it. This is especially the case post-GDPR. If your team is one of the few with a true oversight of all information, then you’re going to be the best people to create value from it. That means big, important decisions are now on CFOs and the finance department, as eyes turn to them for the best possible strategy.
But moving to a model where CFOs and finance teams become the strategic guide for a number of important business decisions on top of everything else they’re already doing seems asking for the impossible. How to navigate a complex economic landscape, become data scientists </i>and</i> be the CEO’s right-hand? It takes more than just high-level thinking and experience to achieve this, it takes highly-powered technologies capable of supporting decision-making at the top level quickly and accurately. Especially as many finance teams (86 per cent) are still doing planning and analysis with static spreadsheets and traditional, labour-intensive processes.
It’s a dilemma CFOs know too well: how to open up enough resource to focus on business strategy when basic tasks still need to be done?
Automate to innovate
This is where artificial intelligence (AI) and machine learning are coming in as the saviour of the finance department.
Automation takes care of the more manual tasks that form part of the CFO’s routine – and tasks that are still incredibly important in keeping the business up and running. But, without jobs such as vendor invoices or purchase orders on their plate, they’re freed up to achieve so much more as well – towards the more strategic, value-add tasks that will help them tap into their ambitions, differentiate them from their peers and actually drive the business forward.
Recent Accenture research showed finance staff spend an average of 60-70 per cent of their time on tasks such as processing transactions, accounting, controlling, compliance and reporting, that’s a lot more time back in their day.
When equipped with predictive analytics software that incorporates machine learning techniques, the finance function can build on its data to help business units identify opportunities for change that may open up in the future and, in some cases, take the lead in developing predictive models for other departments.
‘Machine learning can help finance teams look ahead’
Large-scale automation initiatives can minimise or eliminate the manual execution of the most repetitive transactions. And along with reducing the human error that comes hand-in-hand with manually running these processes, machine learning can help finance teams look ahead.
So much pressure is on CFOs to become the strategic guidance the business needs in the current age of digitalisation. As we start to use more data, this onus on the CFO and the finance team to make use of it is only going to get more intense. It’ll require CFOs and their teams to take on business strategy as well as data science, so they’re going to need the right tools in place which will support them in that role. AI and machine learning will be extremely important here, freeing up enough time in their busy days to focus on gathering the insights which will help the business progress and move forward.
Angela Mazza Teufar is senior vice president of ERPM at Oracle