Data quality is regarded as one of the biggest threats to reputation according to finance leaders. Data quality has become one of the biggest issues requiring attention according to senior finance leaders. As businesses continue to look towards data to enhance performance, the risks and challenges related to poor data have become even more important.

Focusing on increasing the quality of data can create many positives. In the latest IBM 2021 Global C-Suite Study, 70% of senior finance leaders believe that implementing company-wide data standards is a key priority in supporting their business with consolidating systems, cost reductions and scaling effectively.

CEOs are requesting finance leaders to take further responsibility in terms of standardisation, integrations and other associated services. Representatives of the board are demanding more insights, real-time reporting and analytics. These insights are unreliable and have limited use if not based on reliable and consistent information. It can, however, be challenging as raw data is generally quite messy and CFOs can find it difficult to maintain consistency and keep the information clean.

Many larger businesses have approached data quality by hiring a chief data officer (CDO), but in smaller businesses, CFOs generally take on the CDO role themselves.

CEOs understand that positioning the CDO in other functions can create bias in the way data is collected and interpreted, but CFOs are viewed as independent. They are generally regarded as the key to financial data accuracy and are appropriate for controlling other internal and external data.

As organisations become more reliant on data, the effects of poor data on decisions and overall performance will become more serious. More often than not, businesses will invest great sums of money into cleaning, integrating and managing data that may not even really matter to their organisation. Many CFOs often regard the cleaning and management of data sources as an additional burden. The reality is, the insights can be very important to making critical business decisions and have the ability to transform the role and finance function of CFOs.
With a solid platform of cloud-based data, CFOs can transform services in the finance industry by implementing automation in accounts receivable, accounts payable, reconciliation and report, enabling them more time for other valuable duties.

Sarah Ghosh, director of Onyx AI believes that the roles of CFOs were expanding partly due to advanced data analytics and machine learning technologies offer new ways to discover value in the data and delivering new business insights. Applying these technologies effectively requires a big focus on data quality.

Approximately 70% of businesses have made major decisions with inaccurate financial data, according to a survey by software company BlackLine. A further 55% of finance leaders stated they aren’t confident that they are capable of identifying financial errors before generating reports. It, therefore, comes as no surprise that there have been several stories about the detrimental impacts of misinterpretation of information.

External data from outside the finance departments can be even less reliable, with many senior leaders stating aside from cybersecurity, poor data is now the biggest issue to the future of boards and management. This pressure has accelerated even further during the pandemic. One particular pressure on finance leaders has been the rising demand for data by a combination of management, other markets and regulators. In some cases, regulators have utilised data to interpret themselves, which can result in varied results. In this industry, accuracy has become a critical element.

Businesses of various sizes are attempting to manage a range of systems that do not necessarily communicate with one another, which can make data management a big challenge. Generating quality requires effort to assess, validate and reconcile data, and the ability to correct errors.

Thankfully, cloud systems provide more flexibility and integration solutions that generate new insights from both structured and unstructured data.

Combining cloud with analytics tools can simplify data consolidation and cleaning, instead of applying the conventional means of spreadsheets. To manage these tools, the CFO may not necessarily require new skills but must be capable of understanding the variety of skills they may need to incorporate into their finance team. In an ideal situation, this would be a data scientist or analyst with strong business experience. The need to find people with these skills is critical and is causing challenges, due to the lack of such talent being available.
CFOs are exploring how to deliver an optimal mix of expertise and solutions to establish data governance and management teams with a clear framework for monitoring and support. A deeper understanding of these structures will allow to CFO to create teams and allocate the necessary budget to generate improvements and efficient returns, without requiring the need for more detailed technical knowledge.
Applying the data quality role enables businesses to have the chance to increase their technological, analytical and presentation skills. If they can implement all of this successfully, CFOs can confidently lead their businesses into the future.