Too much data is as much of an obstacle as not enough data. Left unstructured it can lead to poor decisions, but when it’s carefully curated with innovative technologies, it can provide a rich source of insight and lay the foundation for agile decision-making.
Some would say you can never have too much data. After all, nobody wants to delete data, just in case it’s needed in the future. However, an overabundance of data can be a barrier to understanding. It can be difficult to extract meaningful insights from too much data, especially when there are doubts about its quality and lineage.
Only 22% of CFOs claim to have mastered their data—that is, their data is actively managed as a corporate asset and the finance function has the tools and resources needed to provide a competitive edge with insights, according to research from FSN, a UK-based research company focused on the global finance community. The remaining 78% complain they have too many conflicting data sources, or they don’t have the technology-savvy resources and tools to fully exploit the data they possess.
Data volumes are growing exponentially, but it’s not always clear why. Few organizations regularly monitor data volumes, which doesn’t help the problem. For example, FSN’s research into data health reveals that only 36% or finance organizations can explain why data volumes are changing and plan for it.
In broad terms, data volumes are rising because of business complexity, an inability to rationalize legacy systems, and the relentless pursuit of more granular and diverse analysis to gain a competitive edge.
Regulation has also added to the volume of data in the finance function. In the last year alone, new regulations have been introduced for environmental, social, and governance (ESG) and the global minimum tax, all of which require businesses to gather and incorporate additional information.
“Being able to respond swiftly to new information requirements is a major concern for finance functions,” says Gary Simon, FSN CEO and leader of the Modern Finance Forum. “Many are shackled to outdated legacy ERP [enterprise resource planning] systems that are inflexible to change.”
Simon adds, “In recent FSN research, 58% of finance functions say that the ability to extend the data set as required is one of the most important characteristics for agility in financial reporting systems.”
So how is it possible for organizations to possess a wealth of data, despite struggling to glean valuable insights?
This data dilemma is propelled by three principal challenges:
Data capture: New data sources that include operational and nonfinancial data, such as weather forecasts, web analytics, and industry-specific data, can be unstructured and uncodified. Add to which traditional extract, transform, and load technologies were designed with IT professionals in mind rather than finance professionals. So finance functions often find it difficult to transform and integrate nonfinancial data without the help of IT specialists.
“In recent FSN research, 58% of finance functions say that the ability to extend the data set as required is one of the most important characteristics for agility in financial reporting systems.”
Gary Simon
CEO of FSN and Leader of the Modern Finance Forum
Also, because this data is unlike codified financial data, errors frequently arise at the point of data capture. Indeed, FSN research finds that 58% of finance functions consider data capture to be where the risk of material misstatement is highest. If not trapped and corrected, errors can rapidly undermine confidence in management reporting, financial forecasts, insights, and business decision-making.
Simon notes, “75% of finance functions encounter a material accounting error—one that requires restatement of the accounts—every month. But when enhancements are made in finance systems, they tend to focus on the end stages, like improving the appearance of reports, rather than addressing fundamental data capture issues that undermine confidence in reports and insights.”
“75% of finance functions encounter a material accounting error—one that requires restatement of the accounts—every month.”
This is where innovation in Workday Accounting Center, a specific application of Workday Prism Analytics, comes in. It puts data handling capabilities back into the hands of the finance function. Once incorporated, the integrated data works just like any other data, and uses the same security, hierarchies, and analysis. When accounting teams need sudden or urgent changes, they can configure those changes for themselves, ensuring accuracy and accelerating an agile response to changed circumstances.
Having delivered AI and machine learning (ML) capabilities for more than a decade, it’s no surprise Workday has also introduced innovation around AI-infused automation over a number of years, embedding it into the very fabric of accounting processes to make them more dependable, predictive, and intelligent. Whether it’s Journal Insights, matching customer payments to invoices, or the expense-to-reimburse process, Workday can rely on intelligent AI to identify anomalous transactions before they become a problem.
“AI-infused anomaly detection is a major step forward in the struggle to contain data errors, against the background of rapidly increasing volumes and variety of data,” Simon adds.
“AI-infused anomaly detection is a major step forward in the struggle to contain data errors.”
Data blending: Go back a couple of decades and business insight was derived mainly from the general ledger and very minimally from external sources. Now, almost the reverse is true, as organizations often find their most valuable insights nested in external data sources, especially nonfinancial data. The ability to blend financial and nonfinancial data is a powerful driver of business insight and plays a vital role in supporting the growing disciplines of finance planning and analysis (FP&A) and business partnering within the modern finance function.
Underpinning blended data is the Workday single object data model, which remains at the forefront of innovation even though it was introduced several years ago. It’s a unified architecture that brings together the transactional and informational aspects of data management into a seamless solution. This integrated approach enables reporting, inquiry, and presentation tools to instantly leverage the underlying data structures. That means every change is reflected in real time as transactions occur, providing users with the most up-to-date, accurate view of the business and insights.
Data visualization: FSN’s research among finance business partners underscores the importance of data visualization in generating insight. Not all business managers (especially non-accountants) are comfortable with masses of rows and columns displayed in two-dimensional spreadsheets. Many respond with more understanding to graphical presentations, dials, charts, and scoreboards to manage performance. Data visualizations allow finance and non-finance professionals to converse in a common language—and it is this meeting of the minds that stimulates discussion, encourages information to be shared, and crystallizes business insight that neither party could achieve completely on their own.
When organizations collect varied data sources accurately, blend it seamlessly with other data held in a financial management system, and visualize it in real time, this sets the ideal framework for rich data insights and agile decision-making.
Read FSN’s 2023 “Workday Innovation Showcase” to learn how the Workday innovative financial management system can improve data insights and boost organizational agility.
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