CFOs facing data management challenges

CFOs facing data management challenges

Called by specialists the new oil of the 21st century, data is rapidly becoming a central concern. Acquiring, selling, collecting, harmonizing, sorting and analyzing data has been considerably accelerated and facilitated by today’s technologies. As a result, companies in all sectors of activity are flooded with a large and constant stream of data. The key challenge is to transform this data into usable, profitable knowledge. To meet this challenge, the parties involved must adapt their objectives, constraints and ways of working. CFOs and their finance departments are no exception; on the contrary, they are among the first to be affected. Let’s look at how data intelligence poses new challenges, how it impacts their role in the company, and what solutions are available to meet these challenges. 

Table of Contents

The 4 key stages in the CFO's data journey

Today, data management is essential for all companies and financial managers, enabling them to extract analyses of market trends, consumer needs and new opportunities. All this provides precious insights for developing the company’s business, understanding its market and adapting its investments. However, many companies are still struggling to exploit the full potential of their data.  

Why is it important for finance professionals to rethink their function and place data at the heart of their strategy? How does this change their role? Data and its management present several challenges. You need to know how to collect data, of course, but also how to make it reliable, analyze and protect it. 

Collecting data

Collecting data essential to analyzing a company’s activity is no easy task. As a result, CFOs are often looking for solutions that can handle large volumes of data, but which also enable them to collect data scattered over time and across different departments. So, it’s not just about collecting data, but rather identifying, collecting and aggregating data.  


Here, of course, we’re talking about financial data, but not only: extra-financial data is also taking on an increasingly important role and is essential for feeding the thinking that goes into strategic decision-making. In collaboration with the company’s CDO (Chief Data Officer) or IT department, CFOs are increasingly turning to data collection automation solutions to meet the twofold challenge of data volume and dispersal. What’s more, these automation solutions offer multiple advantages, including data centralization and accessibility. Finally, in addition to the ability to work cross-functionally, CFOs generally also look to these solutions for data storage and archiving capacity. 

Fiabiliser la data

According to an Accenture study, CFOs spend up to 90% of their time on data. Simply collecting data is only the first step. To be exploitable, data must be accurate and efficient. That’s why data reliability is a major challenge for CFOs. 

Making data reliable means putting in place the means to detect errors, redundancies and discrepancies. It also means ensuring compliance with processes and data harmonization. For example, when it comes to transactions, it’s essential that they are all recorded in the same way, wherever possible. 

Reliable data reinforces the CFO’s role as a trusted player and his credibility within the company. It also enables better-informed decisions to be taken, and improves the organization’s overall performance. 

In a nutshell, making data reliable is an essential process for CFOs wishing to gain efficiency and credibility. 

Analyzing data

As important as data collection and reliability are, the key to success remains data analysis. This is the part that really changes the way we think about the finance function today and tomorrow, and it’s also the part where the rise of new technologies plays a decisive role. 

Quality over quantity“. This saying is also true for data: it’s better to have relevant, high-quality data than lots of it. In fact, the trend is to reduce the volume of data, to have only the essentials. With the rise of “Big Data”, it’s easy for companies to feel overwhelmed by the sheer volume of useless data, so it’s also important to communicate relevant data – the data that matters. 

Identifying relevant data is made possible by advanced analytics. Analytics enable CFOs to reinforce their active, strategic and even proactive role in anticipating the company’s future. 

A PWC study makes an interesting observation, highlighting that 55% of CFOs believe that the role of tomorrow’s CFO will be to lead their company’s digital transformation. Within the company, the CFO is among the best placed people to define the directions to be taken, the new data management processes and to train departments in data analysis. 

Many companies invest in advanced, sophisticated and expensive analytics solutions, only to be disappointed by the results. This is often because they choose complex but inflexible software and fail to exploit the full potential of analysis due to a lack of skills/training or support. 

To make the most of these solutions and benefit fully from their efficiency, you need not only to choose a flexible solution adapted to your business and needs, but above all to prepare your teams. The potential of a tool alone cannot be considered as the sole criterion for a decision, the skills development required to maintain the finance function in its role as a driver of change must not be overlooked. 

Protecting data

Finally, protecting data has also become an indispensable part of data management, as the threats are numerous (cyber-attacks, among others) and so are the stakes (ethical responsibility, consumer confidence, etc.). Cybersecurity departments are becoming more widespread in companies, which are allocating larger budgets to them every year. In large groups, it is the IT department or the cybersecurity division that is responsible for this aspect of data protection. 

Although CFOs are often not directly involved in securing data from external threats, they are nonetheless responsible for it in relation to certain regulations. Indeed, the regulations in terms of protecting the financial data of consumers, customers, suppliers or partners, defined in the GDPR law (General Data Protection Regulation) for example have “put many CFOs to the test” and have been “one of the biggest challenges of regulatory evolution ” in 2018 (Michael Page). 


Indeed, the GDPR law has accelerated CFOs’ digital transformation. To comply, it is now necessary to show proof that the company protects the personal data of its customers and partners (including financial data) against cyber-attacks, but also that it carries out ethical data processing. As financial data is included in personal data, and is one of the most sensitive, the CFO has been directly impacted, and has had to completely rethink the way he manages data. 


Conclusion & lessons learned

All in all, the high stakes involved in data intelligence are leading us to rethink the finance function in general, and the role of CFOs in particular. From the CFO’s point of view, the 4 key steps in the data journey are data collection, data reliability, data analysis and data protection. 

Rapidly collecting large volumes of reliable data, and consolidating it, is essential for CFOs to identify relevant data to communicate to the company. 

The analysis of this data is essential for today’s CFOs, not only to establish future predictions or simulations, but also to enable them to have an informed opinion in the company’s strategic decision-making. 

For this reason, data centralization, access and verification are essential elements in the choice of data management solutions. Advanced data analysis, on the other hand, cannot be carried out without considering the team’s hard skills and sometimes requires training or coaching. Tomorrow’s CFO will therefore be able to find the right tool for his or her data management needs, set up an efficient yet flexible process that can comply with regulations, and highlight his or her expertise. 

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