Big data, analytics, data science – these are regular terms that we all use. Finance and accounting (F&A) teams at all large companies are increasingly making use of big data analytics, which can determine insights from huge volumes of data that would otherwise be unfathomable. It’s been said that data is the new oil of the digital economy, and with 2.5 quintillion bytes generated every day, organisations big and small need to capitalize on this bountiful resource by extracting value from it, in order to create value and growth.
At the heart of digital transformation for finance and accounting teams is the potential for information technology and open data standards to increase efficiency and underpin new competitive opportunities. For a finance and accounting professional, the digital and data revolution provides massive opportunities, as well as offering exciting career options – such as in data science.
There are three good reasons why F&A professionals make excellent data scientists:
- They have outstanding technical skills. They naturally aggregate information in a manner that summarizes details of transactions and other numbers. Working with descriptive analytics, predictive analytics, and prescriptive analytics comes more easily to them, as they already possess quantitative skills.
- They’re great problem solvers. The jump to predictive and prescriptive analytics requires a shift to an inquisitive mindset; from stacking and sorting information to figuring out how to use that information to make key business decisions. F&A professionals are best suited to make this jump.
- They are also better able to see the larger context and business implications. The true value of data analysis comes not at the point when the data is compiled, but rather when decisions are made using insights derived from the data. To uncover these insights, a data scientist must first understand the business context. F&A professionals, because of their connections within the organisation, understand this context better than any external data scientist would.
With accounting and finance professionals increasingly expected to serve as business partners — particularly as experts who can use data analytics to provide strategic recommendations, they need to be problem solvers and readily adaptable to change. Therefore, finance and accounting professionals need to evolve quickly to emphasize competency in data science, analysis, and visualization.
In a post-COVID-19 world, where the pace of digitization is only expected to increase, businesses will require people to adapt to the new normal. Developments in machine learning, for instance, will transform reporting, oversight, auditing, and monitoring systems. Even though they’re natural data crunchers, accountants don’t need to become expert data scientists, but their reliance on data science and analytical skills will only increase in order to enable more effective decision making and control.
Although demand for data science professionals is rapidly increasing today, the nature of data science will become more integrated into processes with the further evolution of artificial intelligence (AI) and cognitive business. The focus of businesses will not only be directed towards bridging the gap between data analytics and business needs, but also towards providing risk-free financial services to customers, as voluminous data comes with a large number of security threats. F&A professionals who master this will be invaluable.
Big data enables the CFO and his team to proactively identify issues with real-time access to the data, so that businesses can base their decision-making on hard evidence and facts, rather than emphasizing on guesswork and assumptions about customers, employees, and vendors.
In order to improve their abilities related to advanced analytics, F&A professionals need to upskill themselves through on-the-job training programs and professional courses that will further develop both the foundational areas of knowledge and competency along with data science and analytics competence. The leaders of tomorrow will be those who understand data and the impact of information quicker and are able to act upon it in the most efficient way possible by leveraging all the tools, techniques, and processes available in this new Digital Age.
