Accurate, real-time data an adjuvant for businesses to navigate finance challenges

Pieter Bensch, Executive Vice-President, Africa & Middle East at Sage, explains the need for finance leaders to have access to accurate, real-time data in order to enable them help navigate their organizations through today’s challenging business landscape.

Pieter Bensch, Executive Vice-President at Sage Africa & Middle East

Finance leaders need access to accurate, real-time data that they can trust as they steer their organisations through today’s challenging and dynamic business landscape. As their role expands beyond financial recordkeeping and compliance to encompass strategy, they can no longer rely on legacy systems to deliver the critical insights they need.

The writing is now on the wall for financial leaders and those who fail to invest in modern technology will continue to endure the burden of time-intensive manual processes and slow reporting. The good news is that today’s cloud finance solutions address all their essential needs, through offering an efficient and modular architecture that enables them to optimise the full potential of data.

In the pre-cloud era, business leaders would embark on enterprise software replacement projects rather nervously, expecting them to be complex and expensive efforts that could take months, or sometimes years, to complete. Today, however, modular and cloud-based business software offers a more flexible alternative to the rigid, monolithic systems of the past.

For starters, businesses can implement the functionality they require most urgently, and add new features and modules as their business needs evolve. Modern plug-and-play architectures are designed to support the core system’s extension and integration with other business applications – without requiring complex interfaces and customisation.

Advanced analytics

One of the core reasons to modernise enterprise applications is to prepare the business to adopt next-generation technologies. Today’s scalable, cloud-based platforms are designed to manage a deluge of real-time and near real-time data from multiple sources. This data can be used to fuel robotic process automation (RPA), machine learning (ML), natural language processing (NLP), and other forms of artificial intelligence (AI).

AI and RPA can automate tasks such as capturing invoices, generating expense reports and logging payment transactions. In addition, such technologies also scrub and review data in real-time at volumes beyond the scale of human comprehension, feeding systems with accurate information so that CFOs always have complete, up-to-date information about the business’s performance.

Predictive analytics

Today’s financial leaders have easy access to predefined reports to help them answer static questions. For example: “How much did I sell, and to what customer type or region?” Likewise, they need access to analytics tools that offer answers to bigger-picture questions such as: “Where and how will I have the most success in gaining or growing revenue? Are all sales down, or is it the sales rep, the region, the customer, or the product offering that are affecting the numbers?”

Today, AI and ML solutions can get to the correct answers faster and more easily than was possible in the past. What’s more, they can start predicting trends rather than responding to them. Predictive analytics is all about detecting patterns and scoring probability, typically measuring risk or opportunity (think predicting cash flow or forecasting demand) using powerful ML algorithms.

Keeping pace with unusual times

As businesses try to keep pace with the evolution in technology, regulation, customer expectations and the increasingly competitive landscape – it is now more important than ever for financial leaders to drive efficiencies and gain better access to real-time information to support decision-making.

One reason why today’s financial leaders are looking at modular, cloud-based solutions is to address the complexities of their expanded role as strategic trailblazers in modern enterprises as legacy systems, which are no longer up to the task and cheaper to maintain.