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.
Why Is There So Much Data?
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 “Many are shackled to outdated legacy ERP [enterprise resource planning] systems that are inflexible to change.”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.”
The Paradox: Rich in Data, Poor in Insights
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:
- First, capturing new financial and nonfinancial data sources, understanding their structure, and incorporating them without introducing errors.
- Second, the difficulty of blending structured and unstructured data in a way that elevates understanding and promotes insight.
- Third, rendering the data in a way that is amenable to data visualization techniques and analytical tools.
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.