Data quality has become one of the biggest issues requiring CFOs’ attention. As companies rely increasingly on data to drive performance, the risks of misreporting due to poor data have become critical.
Increasing data quality brings many positives. In the IBM 2021 Global C-Suite Study, 70% of leading CFOs say implementing enterprise-wide data standards is a top priority to help their organisations consolidate systems, cut costs, and scale rapidly. Many CEOs are asking finance leaders to take this responsibility — for example, in overseeing standardisation, clean-ups, and integrations — as they believe they are best placed to do it.
Boards want more insights from sophisticated and real-time reporting and analytics. These insights are risky or have limited use if not based on consistent, reliable data. But it is a tough challenge as, all too often, raw data is messy and CFOs struggle to keep it clean and consistent.
Many large companies have tackled data quality by appointing a chief data officer (CDO), who can report to any senior executive, including the CFO. In smaller companies, CFOs more often take on the CDO role themselves.
“CEOs know that putting the CDO in other functions may lead to bias in the way they gather and interpret data, but CFOs are seen as independent,” said Diarmuid Cotter, ACMA, CGMA, who has 20 years of senior finance experience, most recently as divisional CFO of IBM Digital Sales Europe. “They are already guardians of financial data accuracy, which gives them the right experience. It is logical to expand that to other internal and external data.”
UK-based Simon Bittlestone, FCMA, CGMA, is CEO at Metapraxis, the financial analytics technology business, founder of the Tomorrow’s CFO initiative, and a CIMA global council member.
“As organisations become more data-driven, the effects of poor data on decisions and resulting performance will become much more serious,” Bittlestone said. “But too often, they spend vast sums on cleaning, integrating, and managing data that doesn’t actually matter to the organisation.”
Many CFOs could see cleaning up and organising internal and external data as a burden in addition to their other responsibilities. But they may also see it as the lesser of two evils.
“The CFO needs to stand by the insights they offer to support critical business decisions, so they might as well own it,” Cotter said. “But more importantly, it offers significant opportunity to transform the CFO role and finance function. With a sound foundation of quality, cloud-based data, they can transform finance by automating areas such as accounts receivable, accounts payable, reconciliations, and reports, freeing them for more value-adding activity.”
UK-based Sarah Ghosh, FCMA, CGMA, the director of Onyx AI and a board member for the Association of International Certified Professional Accountants, said that CFOs’ roles were expanding in part because advanced data analytics and machine learning technologies are offering new ways to find value in the data and provide business insights. ”To apply these new technologies effectively, they must focus on data quality,” Ghosh said.
Ireland-based John Pearson, ACMA, CGMA, is an example of this change. He has worked in IT risk, assurance, and data management for 16 years. But in the last year, his data management function was moved under the local CFO as part of the global CFO’s push to further data maturity.
“As it matures, the improved quality of data helps enhance existing automation efforts and make them more sustainable,” Pearson said.
Data quality stresses
Ireland-based Kunwar Chadha, FCMA, CGMA, head of EMEA FP&A at Google affiliate Fitbit, said outdated data is a typical quality issue.
“For example, in a previous role, when we were raising funds, investors requested revenue forecasts,” he said. “When we looked at our sales pipeline data closely, we came across a number of old leads, so some data cleansing was required. As revenue forecasts were visible to key internal and external stakeholders, there was a natural overlap where finance collaborated with sales to ensure accuracy of our pipeline data. In Europe, the General Data Protection Regulation (GDPR) — which carry financial risks — is another reason for the CFO to collaborate cross functionally on data hygiene.”
Nearly 70% of organisations have made a significant business decision with inaccurate financial data, according to a global survey by software company BlackLine. Also, 55% of finance leaders are not confident they can identify financial errors before reporting results. It is no wonder there have been so many high-profile stories about the harmful effects of misreporting.
But data from outside the finance department and outside the organisation can be even less reliable.
Sydney-based Rachel Grimes, CPA (Australia), former president of the International Federation of Accountants, said alongside cybersecurity, poor data is now the biggest issue that could “wipe out” boards and management.
This pressure has increased further during the COVID-19 pandemic. “One pressure on CFOs has been the thirsty demand for data by management, market, and regulators,” she said. “In some instances, regulators have taken data to interpret themselves, which can lead to different conclusions. Some regulators are also looking to publish data before the standard reporting season, creating potential market disclosure issues. In this environment, accuracy has become paramount.”
Ghosh gives another example. “I am supporting a National Health Service (NHS) partnership in improving digitally enabled care,” she said. “This involves reporting key performance indicators across the NHS, such as the number of COVID patients being cared for in wards. This concerns the CFO because of the costs associated with running additional COVID-related services. So, finance must work closely with operations to ensure that data is captured at the right time and is complete and accurate.”
Ghosh said to achieve this, CFOs must make accuracy a key part of their overall data management strategy, with policies and frameworks to ensure quality across the organisation. They might also have to provide resources for regular data audits.
Slaying the bad data beast
Unless you are the CFO of a startup with unlimited investment, the idea of perfect data is a fairy tale. Organisations of all sizes are grappling with myriad systems that do not talk clearly to one another, which makes managing data a serious challenge.
Ensuring quality requires a huge effort to manipulate, validate, reconcile data, and correct errors — even before you start combining it with external information.
“The thought of owning master data management and integration may bring flashbacks to long-winded or failed IT projects,” Cotter said. “Thankfully, cloud systems today offer more flexibility and integration tools that will bring new insights from the beasts that are structured and unstructured data.
“In a previous role, we had a cloud hybrid offering that enabled easier data collection, organisation, and analysis. Combining this with analytical tools simplified data consolidation and cleaning, instead of trying to do it the old-fashioned way in spreadsheets. Off-the-shelf business intelligence systems can do much the same.”
To handle these tools, the CFO may not need new skills themselves, but they must understand the new mix of skills they need to train or bring into the finance team.
“The ideal is a data scientist or analyst who also has strong business knowledge,” Cotter said. “The need to identify people with such skills is urgent and a major roadblock, due to the lack of such talent available. If there are data analyst skills in another business function, offering a rotation into finance and vice versa for a period may help cross-pollination.”
CFOs are looking to build the optimal mix of expertise and tools to form data governance and management teams with a framework for quality monitoring and support, Pearson said. This requires an understanding of governance structures, such as how to establish a network of data stewards.
This is supported by a central data management team; plus framework fundamentals such as the data management lifecycle, key control points, and how the various tools support each phase, he said. Understanding these structures will enable the CFO to build teams and budget appropriately to deliver control improvements and efficiency returns, without needing more in-depth technical knowledge.
One benefit and challenge of taking on the data quality role is that teams have an opportunity to expand their technological, analytical, and presentation skills. If they can get all these aspects right, it allows CFOs to lead their businesses confidently into exciting new territory.
— Tim Cooper is a freelance writer based in the UK. To comment on this article or to suggest an idea for another article, contact Neil Amato, an FM magazine senior editor, at Neil.Amato@aicpa-cima.com.