The DNA of the CFO Is Changing

Advances in technology and disruption have created some great outcomes in business. However, for the CFO it has created a constantly changing business landscape.

This week Finance Monthly hears from Mohit Manchanda, Head of F&A and Consulting EXL Service UK/Europe at EXL, on the ever-evolving DNA of a CFO.

Business leaders have to stay relevant and ahead of the curve and adapt to the constantly evolving world of finance. This development has become ever apparent for the Chief Financial Officer (CFO) whose role now includes, strategies, operations, communication, and leadership as well as building knowledge surrounding the impact of emerging technologies within the finance sector.

Business outcomes

Advances in data software and automation are opening up avenues for businesses to generate valuable insights that can lead to major productivity improvements. Within the finance and accounting areas, technology is becoming a catalyst for change, driving innovation and providing operational efficiency in business-critical functions.[1] It is essential for CFOs to rethink how to utilise this opportunity to streamline their processes for efficiency, compliance and risk management.

CFOs have many objectives to commit to and by using cutting-edge solutions to enhance the transparency and accuracy of financial data, they can better manage the financial management process. Using automation within finance helps to free up high-value tasks and alleviates the pressure on the CFO to perform traditional activities such as, transaction processing, auditing and compliance.

Human X Machine

It is becoming more and more evident that the CFO will be looked up to, to drive the utilisation of new technologies, however they should try not to get ahead of themselves and forget about the day to day business. Becoming too attached to the hype surrounding Automation and Analytics can put other business objectives on the back burner. For example, managing costs and coming up with new ways to generate profit are tasks that require the CFO to use their own industry knowledge rather than relying on data or analytics.

New technologies can speed up processes and lessen tasks for CFOs; it is important for them to make choices and identify processes where AI, Automation and machine Learning adds value. An investment in one area of a business can create savings in another. In most companies, a high percentage of staff still perform tasks that can be automated through Machine Learning, and these tasks can be performed exponentially faster if self-learning algorithms are applied.

Given the pace of technological change, CFOs should carefully evaluate their point of entry and roll out multiple pilots or proofs of concept (PoC) to test and secure validation before deploying these new technologies.

New technologies can speed up processes and lessen tasks for CFOs; it is important for them to make choices and identify processes where AI, Automation and machine Learning adds value.

Introducing innovative technologies within the finance sector does aid in mitigating lesser tasks for the CFO, however it is not only the technology alone that enables a more streamlined work process. By combining talent, skill set and technology together creates a unified approach, resulting in major improvements throughout the business. For CFOs it means that they can move away from everyday traditional accounting tasks, therefore freeing up time to use their industry knowledge to focus on new business opportunities and provide strategic guidance.

Data & Domain

Organisations regardless of their size will collect large masses of data of which most will never be utilised. It is important for CFOs to understand which data sets are of value and which ones aren’t. Some may be needed for regulatory purposes and others for commercial predictions and products, however by disregarding the sets that are not of value helps to create a more streamlined result.

Starting to experiment with data will help identify potential risks before they are put into production. Machine Learning is all about data experimentation, hypothesis testing, fine tuning data models and Automation. Bringing data, technology and talent together in the form of ideation forums, innovation labs and skunk work projects allows discrete data to be tested for the first time. By bringing in Machine Learning, it can identify hidden patterns that could potentially harm the production process.

In order to drive the business forward, CFOs can translate data and combine it with industry knowledge. The data helps to provide insight within the industry which then contextualises their business decisions. Using data driven decisions CFOs can be confident in their choices within the organisation and use it to back up or prove their conclusions.

Putting data under the business lens enables a CFO to understand the repercussions that can occur through the improper use of big data. A business’ reputation is on the line if data violations occur. Not only will this result in legal sanctions, it will limit business operations, which will have a domino effect on resources and a company’s position compared to its competitors.

Therefore, CFOs should review all of the potential consequences before putting their experimented data findings into practice, including any legal, financial, and brand implications. This is where industry knowledge comes into play, using an expert committee on business data to inspect algorithms for unintentional consequences, results in less risk than normally associated with Machine Learning.

For CFOs to thrive in the digital age, it is essential for them to have a unified approach combining industry knowledge, data, technology and talent.

For CFOs to thrive in the digital age, it is essential for them to have a unified approach combining industry knowledge, data, technology and talent. By employing new technologies, data, talent and knowledge as one package, CFOs can add continuous learning opportunities for critical talent pools, and assist in the overall improvement of productivity within the business.

[1] https://www.business2community.com/big-data/17-statistics-showcasing-role-data-digital-transformation-01970571

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