The Role of a Chief Financial Officer in a Digital Age
As organizations around the globe migrate to digitalization, the role of a Chief Financial Officer has undergone a radical shift. Now, the CFO leads the finance team and drives overall business strategy.
To do so, they need to understand and utilize the latest technology capabilities. They must also develop skills to communicate strategic choices, financial results, and accounting rules to non-finance stakeholders.
In the digital age, a CFO like Mark Hirschhorn must be proficient in business intelligence. It allows companies to turn data into valuable insights that guide strategic and tactical choices.
BI provides users with a comprehensive view of their organization’s data and helps companies make natural time adjustments, eliminate inefficiencies, and adapt to market shifts and supply issues.
It’s a powerful tool for businesses of all sizes, helping them make faster, fact-based decisions. It also makes information easier to access and interpret, saving organizations significant time, money, and effort.
Automation is a term that describes the use of computer and software technologies to digitize, store, process, and communicate routine tasks. These processes include the earliest automatic telephone switchboards to electronic navigation systems and self-driving cars.
The technical potential for automation varies across sectors and activities. For example, physical work such as welding, cutting, and soldering has a technical potential of 59 percent, while a customer service representative’s automation potential is less than 30 percent.
However, it can be challenging to predict which tasks will be mechanized or which individuals will lose their employment due to automation. Typically, companies need to consider the cost of labor and related supply-and-demand dynamics before making an automated decision.
Analytics is a critical business driver, providing insight into business processes and systems, helping organizations improve revenue, and operational efficiency, optimizing marketing campaigns, and bolstering customer service efforts. They also help businesses respond rapidly to emerging market trends and gain a competitive edge over rivals.
Analytics also allow CFOs to identify new sources of value that can be created in an organization. It can involve identifying groups delivering greater importance to the organization, such as asset builders (automakers), service providers, and technology creators.
To drive these changes, the CFO needs to bridge the gap between strategic and operational decision-making and ensure that all critical processes are equipped with data and insights. It requires a high commitment and a willingness to invest in a small team of talented people.
Data Science is a multidisciplinary field that includes data engineering, data preparation, data mining, predictive analytics, machine learning, and data visualization. It requires substantial knowledge of statistics, mathematics, and software programming.
It also requires a keen understanding of business, curiosity, and critical thinking. Those skills are needed to communicate data insights effectively.
The manufacturing industry is an excellent example of a business where data science can help improve efficiency by optimizing production processes and supply chains. It can also identify inefficiencies and recommend improvements to save money and resources.
Data Science can also analyze a customer’s online shopping cart and show them product recommendations. It can also be used to manage promotions and discounts in real time.
Cybersecurity is one of the top business issues on the minds of executives today as the number of cybersecurity breaches continues to rise. Malicious cybercriminals primarily cause these attacks.
These attacks can have a significant impact on financial stability. They can prevent people from being able to use online services, including mobile money apps and remittances.
It is a significant concern for CFOs, who must ensure the budgets allocated to implement cybersecurity measures are well-matched to risk.
It requires developing a cost-benefit analysis that considers both short-term and long-term costs associated with a data breach. It also needs to account for the possible damage to a company’s reputation and stock price.