Predictive analytics help finance leaders manage uncertainty

We have entered what could be the most volatile and uncertain economic period in decades. The Covid-19 lockdown, with its sharp economic contraction and wide-scale retrenchments, has driven many companies to revisit their strategies both domestically and abroad. We are not alone: there is a growing sense of social unrest and political instability globally.

It is the finance leader along with the CEO that will be responsible for navigating through the uncertainty ahead to ensure the company can follow through on its plans. Both will need to maintain a cool head and rely increasingly on predictive analytics to find that path through millions of rows of data.

SA is arguably better prepared than many countries: according to new research by Sage, 64% of SA finance leaders already spend more time analysing data than they do on actual old-style number crunching. This compares, for instance, with only 50% of financial managers in the UK.

The report, “CFO 3.0: Digital transformation beyond financial management”, where 311 senior in-house financial decisionmakers from SA were surveyed, revealed the extent to which predictive analytics-based technologies are changing how finance leaders operate at board level. The survey confirms the changing role of heads of finance.

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Where to start?

If finance teams aren’t already using predictive analytics, a good place to start is with the basics — an evaluation of the extant state of financial systems and processes in the business:

• Has the organisation automated processes for statutory reporting and generating financial statements?
• Does it have a modern, integrated business solution in place that provides people in the business with fast and easy access to financial information?

If the answer to either is no, the finance leader should consider replacing inflexible legacy platforms and manual processes with scalable, cloud-based solutions that offer real-time visibility into the organisation’s processes and supply chain. Until the right foundation is in place, the organisation will find itself cobbling together spreadsheet reports that are based on yesterday’s information.

Equipping finance teams with skills

Finance departments and CFOs may need to look outside the finance field to acquire the expertise needed to live up to the demand for richer analytics. For example, people with storytelling, technology, and data science skills can help develop analytics solutions that deliver insights to the right business stakeholders in the right format.

Developing the skills will require dedicated time and effort. A good place to start is for finance leaders to look at creating upskilling opportunities for those already in finance with a strong aptitude for data and technology, and identify gaps where they might require specialised skills from outside the team.

Building a culture of automation

Finance teams can streamline their analytics processes by taking advantage of automated data analytics. Automation is a reliable way to improve the quality of financial data, for example, through streamlining data preparation and aggregation tasks.

Building a culture of automation can increase one’s productivity through a reduction in manual processes, fewer errors and faster processing times. Automation enables quicker business-wide decision-making while improving regulatory compliance and ensuring accurate financial statements. Today’s technology can automate many standard reporting functions as well as the creation of dashboards.

Speeding up processing

As the pace of change in business operations increases, finance teams can leverage data analytical tools to better engage with their business partners and manage enterprise performance. Finance leaders should invest in ensuring that real-time data and analytics are available at the points where operational decisions are made, speeding up processes and lowering costs through automation.

Self-service business intelligence tools that allow people to interrogate data using familiar interfaces such as Excel, or to look at visual representations of business trends in graphs and tables, can be used to help those at the coalface make faster and better operational decisions.

The Sage report makes it clear that where businesses don’t have some level of cloud-based financial management, there is a lack of overall strategic direction. In contrast, predictive analytics enrich finance processes by offering insights into business problems and areas of potential.

Finance leaders are already putting predictive analytics to use in the following ways:

• Predicting revenue: A multitude of marketing, sales, operation and customer behaviour data make it possible for finance teams to both forecast revenue more accurately and anticipate future demand for products.
  
  
• Improving supply chains: Finance leaders are increasingly using predictive analytics to maximise efficiency in more creative ways, from ranking vendors according to vulnerability to fraud, to identifying equipment that may fail.
  
  
• Analysing loss drivers: Predictive analytics can identify trouble spots that are driving company losses. For instance, companies can use predictive analytics modelling to analyse indicators of customer loyalty, permitting action plans to address the issues and retain them.
  
  
• Detecting fraud: Finance leaders have been especially keen on tapping analytics to detect potential fraud.

This article was paid for by Sage.