How Finance Leaders Can Leverage Operational Data Analytics

For a lot of us, sci-fi films like The Avengers or The Matrix are a fun look into what the future might hold. But we’re also seeing big shifts in what’s possible right now. By leveraging operational data that’s collected throughout the organization, finance leaders are transforming the finance function and extending the value they offer to their organizations far beyond reporting and compliance. With the sheer volume of data available and the recent advancements in corporate performance management (CPM) software, finance teams now (finally) have the capability to deliver on advanced analytics.

The Financial Data Landscape

Although we’re able to collect vast amounts of organizational data, access to raw data is ultimately meaningless without the capability to interpret that data and understand the impact on financial results. Typically, the finance department has been slow to adopt newer, advanced technology, but with advanced analytics delivered as part of modern CPM software, we now have the technology in place to analyze large volumes of operational data and predict what will happen with a high degree of accuracy.

Identifying key trends and signals in financial and operational data are critical to driving more informed decisions across the enterprise. However, if finance teams spend most of their time moving and reconciling data and building reports, there’s little time left to analyze data and guide critical business decisions. With built-in, advanced analytics, finance teams can shift a larger portion of their time to value-driving activities, such as forecasting revenue or evaluating key capital investment decisions.

The Ability To Achieve Advanced Predictive Analytics At Scale

Although advanced analytics have been around for over 20 years, the technology available today has progressed to the point in which increasingly large volumes of operational data can be processed regularly to drive day-to-day business decisions. According to the results presented in the Dresner Advisory 2021 “Data Science and Machine Learning Market Study,” only 39% of finance teams are deploying the kind of technologies that enable predictions about future, or otherwise unknown, events today. Advancements in CPM software combined with operational data analytics now have the potential to deliver deeper and more detailed insights that impact more business functions.

How so? Finance teams can now leverage purpose-built CPM software with built-in analytics to help supplement traditional period-end reporting and planning processes with frequent views into financial signals in high volumes of operational data, as well as statistically significant, predictive forecasts. Finance teams can drill down into key financial signals and KPIs and review them on a weekly or even daily basis, analyze key trends and work across the organization to take action as needed. For example, advanced analytics applied to corporate financial planning and analysis (FP&A) can create daily financial signals on sales, gross margin and working capital drivers.

Here’s an example: A global professional services firm downloads over 10 million records of operational data nightly into its CPM platform, then processes and delivers this data to its line managers through interactive, graphical dashboards. These dashboards provide the managers with visibility into key trends and signals regarding their clients, projects, resource consumption, billings and collections and days sales outstanding (DSO) to enable more agile decision-making on a daily and weekly basis that can impact the results in advance of the month-end or quarter-end.

What Does This Mean For Business?

As a result of pandemic pressures and ongoing evolution, CFOs are being tasked with taking on a more strategic role, simultaneously focused on the longer, big-picture view while providing line managers with a more immediate view into the pulse of the business. When integrated into existing financial reporting and planning systems and processes, advanced analytics (including machine learning and AutoAI) can combine macroeconomic factors and internal data to arm finance teams with better forecasts, improved decision-making and increased collaboration across the business.

As CFOs and finance teams become more strategic and their roles continue to evolve within organizations, they’ll face a growing need to assess, model and predict future scenarios to support agile decision-making. Tapping into the large volumes of data available in the enterprise and implementing advanced analytics represents a significant opportunity for the office of finance to make a real business difference and become better strategic business partners.